smart meter

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pages: 433 words: 127,171

The Grid: The Fraying Wires Between Americans and Our Energy Future by Gretchen Bakke

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Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, back-to-the-land, big-box store, Buckminster Fuller, demand response, dematerialisation, distributed generation, energy security, energy transition, full employment, illegal immigration, indoor plumbing, Internet of things, laissez-faire capitalism, Menlo Park, Negawatt, new economy, post-oil, profit motive, Ronald Reagan, self-driving car, Silicon Valley, smart grid, smart meter, the built environment, too big to fail, washing machines reduced drudgery, Whole Earth Catalog

like a cash grab: Jack Danahy, “Smart Grid Fallout: Lessons to Learn from PG&E’s Smart Meter Lawsuit,” Smart Grid News, November 13, 2009, http://www.smartgridnews.com/story/smart-grid-fallout-lessons-learn-pge-s-smart-meter-lawsuit/2009-11-13, for individual customer complaints see: https://sites.google.com/site/nocelltowerinourneighborhood/home/wireless-smart-meter-concerns/smart-meter-consumers-anger-grows-over-higher-utility-bills. digital smart meters: Jesse Wray-McCann, “Householders Shielding Homes from Smart Meter Radiation,” Herald Sun, April 9, 2012, http://www.heraldsun.com.au/ipad/householders-shielding-homes-from-smart-meter-radiation/story-fn6bfm6w-1226321653862. commissioners’ residences: Anjeanette Damon, “Smart Meters Spawn Conspiracy Talk: They Know What You’re Watching on TV!,” Las Vegas Sun, March 8, 2012, http://m.lasvegassun.com/news/2012/mar/08/smart-meters-spawn-conspiracy-theories-they-know-w/.

CHAPTER 6: Two Birds, One Stone station after the event: Charlie Wells, “Houston Woman Thelma Taormina Pulls Gun on Electric Company Worker for Trying to Install ‘Smart Meter,’ ” New York Daily News, July 19, 2012, http://www.nydailynews.com/news/national/houston-woman-thelma-taormina-pulls-gun-electric-company-worker-install-smart-meter-article-1.1118051. which were watching Shrek 2: “Researchers Claim Smart Meters Can Reveal TV Viewing Habits,” Metering.com, September 21, 2011, http://www.metering.com/researchers-claim-smart-meters-can-reveal-tv-viewing-habits/. For the research conducted at the University of Washington, see Antonio Regalado, “Rage Against the Smart Meter,” MIT Technology Review, April 26, 2012, http://www.technologyreview.com/news/427497/rage-against-the-smart-meter/. And for readers of German: Prof. Dr.-Ing U. Greveler, Dr. B. Justus, and D. Löhr, “Hintergrund und Experimentelle Ergebnisse Zum Thema ‘Smart Meter und Datenschutz’ ” (Fachhochschule Münster University of Applied Sciences, September 20, 2011), https://web.archive.org/web/20121117073419/http://www.its.fh-muenster.de/greveler/pubs/smartmeter_sep11_v06.pdf.

The question remains the same in Boulder as in Bakersfield and Houston and Maine (with residents’ worries about the well-being of their ball-shaped organs): If smart meters or even a whole smart grid can’t be proved to benefit customers even by the very utility undertaking the upgrade, whom, then, do they benefit? Why did Xcel go to the trouble and expense of building a citywide smart grid? Why did CenterPoint visit the Taorminas seven times in attempting to give them a smart meter? Why did PG&E risk a class-action lawsuit to ensure that all the people of Bakersfield also got their new meters? The answer, of course, is that smart meters don’t benefit us, the customers. At least they don’t directly. Smart meters, and to a lesser extent other grid-smartening investments, benefit them, the utility companies. The level of expense and of risk for the utility companies is only suspicious until one realizes the stakes.


pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

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23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, mobile money, more computing power than Apollo, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, offshore financial centre, optical character recognition, pattern recognition, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, WikiLeaks, Y Combinator, zero day

Smith, “Hacking and Attacking Automated Homes,” Network World, June 25, 2013. 50 Hilton Hotels too: Nancy Trejos, “Hilton Lets Guests Pick Rooms, Use Smartphones as Keys,” USA Today, July 29, 2014. 51 Worldwide nearly ninety million: Michael Wolf, “3 Reasons 87 Million Smart TVs Will Be Sold in 2013,” Forbes, Feb. 25, 2013. 52 Many brands have been found: Lorenzo Franceschi-Bicchierai, “Your Smart TV Could Be Hacked to Spy on You,” Mashable, Aug. 2, 2013; Dan Goodin, “How an Internet-Connected Samsung TV Can Spill Your Deepest Secrets,” Ars Technica, Dec. 12, 2012. 53 “750,000 malicious spam”: Ellie Zolfagharifard, “Criminals Use a Fridge to Send Malicious Emails in First Ever Home Hack,” Mail Online, Jan. 17, 2014. 54 Refrigerator spam: “Spam in the Fridge,” Economist, Jan. 25, 2014. 55 In early 2014, researchers: Dan Goodin, “ ‘Internet of Things’ Is the New Windows XP—Malware’s Favorite Target,” Ars Technica, April 2, 2014. 56 As of mid-2013: Utility-Scale Smart Meter Deployments, IEE report, Aug. 2013, 3; Chris Choi, “Smart Meters Are Heading to Every Home in Britain,” ITV News, July 8, 2014. 57 Researchers in Germany: Jordan Robertson, “Your Outlet Knows: How Smart Meters Can Reveal Behavior at Home, What We Watch on TV,” Bloomberg, June 10, 2014. 58 According to an investigation: Brian Krebs, “FBI: Smart Meter Hacks Likely to Spread,” Krebs on Security, April 9, 2012. 59 Like all computers: Katie Fehrenbacher, “Smart Meter Worm Could Spread like a Virus,” Gigaom, July 31, 2009. 60 Nest’s thermostats: Rolfe Winkler, “What Google Gains from Nest Labs,” Wall Street Journal, Jan. 15, 2014. 61 “conscious home”: Marcus Wohlsen, “What Google Really Gets out of Buying Nest for $3.2 Billion,” Wired, Jan. 14, 2014. 62 Google’s Nest thermostat: Richard Lawler, “Nest Learning Thermostat Has Its Security Cracked Open by GTVHacker,” Engadget, June 23, 2014. 63 Nest’s other main product: Edward C.

In doing so, hackers can keep your appliances running at full speed, generating virtual currencies for them while sticking you with the electric bill for spinning your devices 24/7. In theory, the new smart meter in your home might catch the excessive electricity use, but of course it too can be hacked. What the Outlet Knows Smart meters will be at the core of the global IoT, and their two-way communications abilities will record and track details of electricity usage in homes and businesses in order to increase the overall efficiency and reliability of an outdated and overburdened electrical grid. As of mid-2013, smart meters had been installed in over forty-six million homes in the United States, and the U.K. anticipates their deployment throughout all of Britain by 2020. Smart-meter information, much of which is transmitted in an unencrypted format, can actually reveal details such as the brand and age of your appliances and when you are using them in which rooms of your home.

Indeed, in May 2014, WPP, the world’s largest advertising agency, announced it was teaming up with the London-based data analytics company Onzo to study ways to collect smart-meter data in order to finally “open the door of the home” to advertisers. The threats from smart meters extend well beyond their deep privacy implications, and criminals have attacked insecure smart utility devices for a variety of purposes, in particular financial fraud. In Puerto Rico, for example, Crime, Inc. employed large teams of techno-thugs to take advantage of the widespread deployment of smart meters on the island. Using software widely available in the digital underground and a simple laptop, criminal hackers began making “service calls” to both businesses and the general public. For fees ranging from $300 to $1,000 for residential customers and $3,000 for commercial clients, Crime, Inc. successfully reprogrammed the smart meters in order to save its “clients” up to 75 percent off their monthly electricity bills.


pages: 464 words: 127,283

Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia by Anthony M. Townsend

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1960s counterculture, 4chan, A Pattern Language, Airbnb, Amazon Web Services, anti-communist, Apple II, Bay Area Rapid Transit, Burning Man, business process, call centre, carbon footprint, charter city, chief data officer, clean water, cleantech, cloud computing, computer age, congestion charging, connected car, crack epidemic, crowdsourcing, DARPA: Urban Challenge, data acquisition, Deng Xiaoping, East Village, Edward Glaeser, game design, garden city movement, Geoffrey West, Santa Fe Institute, George Gilder, ghettoisation, global supply chain, Grace Hopper, Haight Ashbury, Hedy Lamarr / George Antheil, hive mind, Howard Rheingold, interchangeable parts, Internet Archive, Internet of things, Jacquard loom, Jacquard loom, Jane Jacobs, jitney, John Snow's cholera map, Khan Academy, Kibera, knowledge worker, load shedding, M-Pesa, Mark Zuckerberg, megacity, mobile money, mutually assured destruction, new economy, New Urbanism, Norbert Wiener, Occupy movement, openstreetmap, packet switching, patent troll, place-making, planetary scale, popular electronics, RFC: Request For Comment, RFID, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, social graph, social software, social web, special economic zone, Steve Jobs, Steve Wozniak, Stuxnet, supply-chain management, technoutopianism, Ted Kaczynski, telepresence, The Death and Life of Great American Cities, too big to fail, trade route, Tyler Cowen: Great Stagnation, Upton Sinclair, uranium enrichment, urban decay, urban planning, urban renewal, Vannevar Bush, working poor, working-age population, X Prize, Y2K, zero day, Zipcar

John on the GigaOM blog, it’s “one of the few corporations out there that can lay claim to almost every share of the world’s current grid infrastructure, building everything from gas and wind turbines to high-voltage transmission cables to sensors and controls that monitor and manage the delivery of power to homes and businesses.”45 Targeting nearly $8.5 billion (€6 billion) in annual smart grid business by 2014, CEO Peter Löscher boasted, “We’re on the threshold of a new electric age.”46 As consumers, we think of the smart grid mostly through our growing experience with smart meters. Smart meters are to your old electric meter what a smartphone is to your grandmother’s Bakelite 1950s rotary phone. It’s a souped-up, networked upgrade that constantly reports back to the electric company a stream of data about your power consumption, including when it detects blackouts and brownouts. The more advanced models can manage power-hungry appliances in your home. In-Stat, a market research firm, projects that by 2016 fully three-quarters of American electric meters will have been converted to smart meters.47 While these are the most visible endpoints of the emerging new grid, Siemens actually sold off its smart-meter business a decade ago. Its true ambition is to become a Cisco for electricity, providing the brains inside the smart grid, the software and switches that manage the behind-the-scenes balancing act that keeps the juice flowing.

If only the peaks could be evened out, fewer peaking plants would be needed and utilities could focus more on ruthlessly fine-tuning base load plants to be as lean and clean as possible.48 Smart grids offer two tricks to even out the peaks: load shifting and load shedding. Load shifting, the gentler of the two, tries to spread demand for power away from peak periods of demand through price incentives. In their simplest form, smart meters allow businesses and consumers to see the true cost of generating electricity during periods of high demand. As they fire up those costly peaking plants, utilities simply pass the higher generating cost along to consumers. Dynamic pricing can dramatically reduce swings in demand for power and increase overall generating efficiency, but load shifting can also be automated and proactive. Smart meters that communicate directly with smart appliances might automatically reschedule a load of wash for later in the day when demand and prices are likely to fall. Even the most sophisticated load-shifting scheme will one day meet its limit.

John, “How Siemens is Tackling the Smart Grid,” GigaOM, last modified June 24, 2010, http://gigaom.com/cleantech/how-siemens-is-tackling-the-smart-grid/. 46“Siemens CEO Peter Löscher: We’re on the threshold of a new electric age,” Siemens press release, December 15, 2010, http://www.siemens.com/press/en/pressrelease/?press=/en/pressrelease/2010/corporate_communication/axx20101227.htm. 47“75% of US Electric Meters to be Smart Meters by 2016,” In-Stat press release, March 5, 2012, http://www.fiercetelecom.com/press-releases/75-us-electric-meters-will-be-smart-meters-2016. 48Chris Nelder, “Why baseload power is doomed,” SmartPlanet, blog, last modified March 28, 2012, http://www.smartplanet.com/blog/energy-futurist/why-baseload-power-is-doomed/445. 49Massoud Amin, “North American Electricity Infrastructure: System Security, Quality, Reliability, Availability, and Efficiency Challenges and their Societal Impacts,” in Continuing Crises in National Transmission Infrastructure: Impacts and Options for Modernization, National Science Foundation (NSF), June 2004. 50Fitze, “No Longer A One-Way Street,” 23. 51Tim Schröder, “Automation’s Ground Floor Opportunity,” Pictures of the Future, Spring 2011, 19, http://www.siemens.com/innovation/apps/pof_microsite/_pof-spring-2011/_pdf/pof_0111_strom_buildings_en.pdf. 52Eric Paulos, lecture, “Forum on Future Cities,” MIT SENSEable City Lab and the Rockefeller Foundation, Cambridge, MA, April 13, 2011, http://techtv.mit.edu/collections/senseable/videos/12305-changing-research; For a thorough treatment see Eric Paulos and James Pierce, “Citizen Energy: Towards Populist Interactive Micro-Energy Production,” n.d., http://www.paulos.net/papers/2011/Citizen_Energy_HICSS2011.pdf. 53James R.


pages: 402 words: 110,972

Nerds on Wall Street: Math, Machines and Wired Markets by David J. Leinweber

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AI winter, algorithmic trading, asset allocation, banking crisis, barriers to entry, Big bang: deregulation of the City of London, butterfly effect, buttonwood tree, buy low sell high, capital asset pricing model, citizen journalism, collateralized debt obligation, corporate governance, Craig Reynolds: boids flock, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Danny Hillis, demand response, disintermediation, distributed generation, diversification, diversified portfolio, Emanuel Derman, en.wikipedia.org, experimental economics, financial innovation, Gordon Gekko, implied volatility, index arbitrage, index fund, information retrieval, Internet Archive, John Nash: game theory, Khan Academy, load shedding, Long Term Capital Management, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, market fragmentation, market microstructure, Mars Rover, moral hazard, mutually assured destruction, natural language processing, Network effects, optical character recognition, paper trading, passive investing, pez dispenser, phenotype, prediction markets, quantitative hedge fund, quantitative trading / quantitative finance, QWERTY keyboard, RAND corporation, random walk, Ray Kurzweil, Renaissance Technologies, Richard Stallman, risk tolerance, risk-adjusted returns, risk/return, Ronald Reagan, semantic web, Sharpe ratio, short selling, Silicon Valley, Small Order Execution System, smart grid, smart meter, social web, South Sea Bubble, statistical arbitrage, statistical model, Steve Jobs, Steven Levy, Tacoma Narrows Bridge, the scientific method, The Wisdom of Crowds, time value of money, too big to fail, transaction costs, Turing machine, Upton Sinclair, value at risk, Vernor Vinge, yield curve, Yogi Berra

(Notice that “Innovative” appears twice in the figure, indicative of the rapid pace of change, and note the foundation level position for smart end-use devices.) These so-called smart meters are the enabling technology for intelligent engineering and market solutions to electric energy problems. Recall that electronic market access (first seen in the NYSE’s DOT) was the enabling technology for disintermediation, and later, the use of information technology for algorithmic trading. Similarly, these smart meters will allow utilities, small producers, and consumers to bring the benefits of ubiquitous computation and market solutions to creating a more efficient, less polluting, low-carbon electric industry. These smart meters exist now. GridPoint in Arlington, Virginia, is the lead dog firm in this space. It was selected as a technology pioneer by the heavies at the Davos World Economic Forum in 2007, as a top innovator by MIT’s Technology Review, and by the Department of Energy for its model energy-efficient homes.

., plug-in hybrid electric vehicles [PHEVs] and fuel cells). For consumers, the platform provides protection from power outages, increases energy efficiency through online energy management, and integrates renewable energy, paving the way for the commercial success of solar and wind energy sources. The initial application for smart meters was simple: remote meter reading. This was the motivation for the utility vendors to install them to the limited extent that this has been done. But with greater capabilities in the newer versions the smart meters enable a much greater and more sophisticated set of applications. This could lead to savings to customers, as well as utilities, and for reductions in emissions that benefit everyone. From Efficiency to Control to Markets The first wave of energy conservation technologies was about energy efficiency, reducing the power demand by building better machines to plug into the wall, but with the same dumb old meter spinning outside.

It was selected as a technology pioneer by the heavies at the Davos World Economic Forum in 2007, as a top innovator by MIT’s Technology Review, and by the Department of Energy for its model energy-efficient homes. What Apple is to music players, GridPoint is to smart meters. An overview for the controller is shown in Figure 14.3. Figure 14.3 GridPoint’s smart grid platform is designed to align the interests of electric utilities, consumers, and the environment through an intelligent network of distributed energy resources that controls load, stores energy, and produces power. Algo trading for electrons is coming. Source: GridPoint (www.gridpoint.com). 334 Nerds on Wall Str eet GridPoint explains how its simple blue box on the wall addresses all the key issues in our electricity future: The platform applies information technology to the electric grid to enable distributed energy resources to perform the same as central-station generation.


pages: 492 words: 153,565

Countdown to Zero Day: Stuxnet and the Launch of the World's First Digital Weapon by Kim Zetter

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Ayatollah Khomeini, Brian Krebs, crowdsourcing, data acquisition, Doomsday Clock, Edward Snowden, facts on the ground, Firefox, friendly fire, Google Earth, information retrieval, Julian Assange, Loma Prieta earthquake, Maui Hawaii, pre–internet, RAND corporation, Silicon Valley, skunkworks, smart grid, smart meter, South China Sea, Stuxnet, uranium enrichment, Vladimir Vetrov: Farewell Dossier, WikiLeaks, Y2K, zero day

Emergency generators would kick in at some critical facilities, but generators aren’t a viable solution for a prolonged outage, and in the case of nuclear power plants, a switch to generator power triggers an automatic, gradual shutdown of the plant, per regulations. One way to target electricity is to go after the smart meters electric utilities have been installing in US homes and businesses by the thousands, thanks in part to a $3 billion government smart-grid program, which has accelerated the push of smart meters without first ensuring that the technology is secure. One of the main problems security researchers have found with the system is that smart meters have a remote-disconnect feature that allows utility companies to initiate or cut off power to a building without having to send a technician. But by using this feature an attacker could seize control of the meters to disconnect power to thousands of customers in a way that would not be easily recoverable.

But by using this feature an attacker could seize control of the meters to disconnect power to thousands of customers in a way that would not be easily recoverable. In 2009, a researcher named Mike Davis developed a worm that did just this. Davis was hired by a utility in the Pacific Northwest to examine the security of smart meters the company planned to roll out to customers. As with the Siemens PLCs that Beresford examined, Davis found that the smart meters were promiscuous and would communicate with any other smart meters in their vicinity as long as they used the same communication protocol. They would even accept firmware updates from other meters. All an attacker needed to update the firmware on a meter was a network encryption key. But since all the meters the company planned to install had the same network key embedded in their firmware, an attacker only had to compromise one meter to extract the key and use it to deliver malicious updates to other meters.

Some vendors now use multiple network keys on their meters, assigning a different key for different neighborhoods to limit the damage an attacker could do with a single key. But the remote disconnect is still a problem with most smart meters, since an attacker who breaches a utility’s central server could do what Davis’s worm did, but in a much simpler way. “Were [the remote disconnect] not in there, none of this would really be all that much of an issue,” Davis says. “In my opinion, if it’s got the remote disconnect relay in it, whether it’s enabled or not … it’s a real big, ugly issue.” Going after smart meters is an effective way to cut electricity. But an even more effective and widespread attack would be to take out generators that feed the grid or the transmission systems that deliver electricity to customers.


pages: 219 words: 61,720

American Made: Why Making Things Will Return Us to Greatness by Dan Dimicco

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, Affordable Care Act / Obamacare, American energy revolution, American Society of Civil Engineers: Report Card, Bakken shale, barriers to entry, Bernie Madoff, carbon footprint, clean water, crony capitalism, currency manipulation / currency intervention, David Ricardo: comparative advantage, decarbonisation, fear of failure, full employment, Google Glasses, hydraulic fracturing, invisible hand, job automation, knowledge economy, laissez-faire capitalism, Loma Prieta earthquake, manufacturing employment, oil shale / tar sands, Ponzi scheme, profit motive, Report Card for America’s Infrastructure, Ronald Reagan, Silicon Valley, smart grid, smart meter, sovereign wealth fund, The Wealth of Nations by Adam Smith, too big to fail, uranium enrichment, Washington Consensus, Works Progress Administration

Sharan noted how the Obama administration allocated a little over $4 billion in stimulus money to building the smart grid, which is an important piece of infrastructure for our future. The plan was to install 20 million “smart meters” over five years. Smart meters are simply digital versions of the old spinning electric meter. Power companies nationwide employ tens of thousands of people who do nothing but read the meters. With smart meters, utility companies don’t need meter readers anymore. As Sharan put it: “In five years, 20 million manually read meters are expected to disappear, taking with them some 28,000 meter-reading jobs. In other words, instead of creating jobs, smart metering will probably result in net job destruction.”25 Sharan calculated that installing 20 million new smart meters over five years would create about 1,600 new installation jobs. Unfortunately, most of the smart meters are made overseas. The meters will require people who know how to maintain and service them, but that would create a few hundred jobs at most.


pages: 565 words: 151,129

The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism by Jeremy Rifkin

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3D printing, additive manufacturing, Airbnb, autonomous vehicles, back-to-the-land, big-box store, bioinformatics, bitcoin, business process, Chris Urmson, clean water, cleantech, cloud computing, collaborative consumption, collaborative economy, Community Supported Agriculture, computer vision, crowdsourcing, demographic transition, distributed generation, en.wikipedia.org, Frederick Winslow Taylor, global supply chain, global village, Hacker Ethic, industrial robot, informal economy, intermodal, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Julian Assange, Kickstarter, knowledge worker, labour mobility, Mahatma Gandhi, manufacturing employment, Mark Zuckerberg, market design, means of production, meta analysis, meta-analysis, natural language processing, new economy, New Urbanism, nuclear winter, Occupy movement, oil shale / tar sands, pattern recognition, peer-to-peer lending, personalized medicine, phenotype, planetary scale, price discrimination, profit motive, RAND corporation, randomized controlled trial, Ray Kurzweil, RFID, Richard Stallman, risk/return, Ronald Coase, search inside the book, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, smart grid, smart meter, social web, software as a service, spectrum auction, Steve Jobs, Stewart Brand, the built environment, The Nature of the Firm, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, transaction costs, urban planning, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog, Whole Earth Review, WikiLeaks, working poor, Zipcar

New studies, however, including one conducted by my global consulting group, show that with the shift to a Third Industrial Revolution infrastructure, it is conceivable to increase aggregate energy efficiency to 40 percent or more in the next 40 years, amounting to a dramatic increase in productivity beyond what the economy experienced in the twentieth century.8 The Internet of Things The enormous leap in productivity is possible because the emerging Internet of Things is the first smart-infrastructure revolution in history: one that will connect every machine, business, residence, and vehicle in an intelligent network comprised of a Communications Internet, Energy Internet, and Logistics Internet, all embedded in a single operating system. In the United States alone, 37 million digital smart meters are now providing real-time information on electricity use.9 Within ten years, every building in America and Europe, as well as other countries around the world, will be equipped with smart meters. And every device—thermostats, assembly lines, warehouse equipment, TVs, washing machines, and computers—will have sensors connected to the smart meter and the Internet of Things platform. In 2007, there were 10 million sensors connecting every type of human contrivance to the Internet of Things. In 2013, that number was set to exceed 3.5 billion, and even more impressive, by 2030 it is projected that 100 trillion sensors will connect to the IoT.10 Other sensing devices, including aerial sensory technologies, software logs, radio frequency identification readers, and wireless sensor networks, will assist in collecting Big Data on a wide range of subjects from the changing price of electricity on the grid, to logistics traffic across supply chains, production flows on the assembly line, services in the back and front office, as well as up-to-the-moment tracking of consumer activities.11 As mentioned in chapter 1, the intelligent infrastructure, in turn, will feed a continuous stream of Big Data to every business connected to the network, which they can then process with advanced analytics to create predictive algorithms and automated systems to improve their thermodynamic efficiency, dramatically increase their productivity, and reduce their marginal costs across the value chain to near zero.

It is estimated that IT solutions—using social media—could drive the cost of solar down by 75 percent, making it cheaper than coal.31 The Cleanweb Movement in the United States is getting Big Data help from a new federal government initiative called Green Button. The program, which was launched in 2011, encourages power and utility companies to voluntarily provide easy access to real-time energy usage data now available for the first time because of the installation of millions of smart meters in homes and businesses. Smart meters are vital data collection points in the Energy Internet infrastructure. That data can be downloaded by the companies’ customers so they can have the information they need to more efficiently manage their energy use. In less than a year, the number of customers with instant access to their own energy use data ballooned to 31 million.32 Companies like Opower, Itron, First Fuel, Efficiency 2.0, EcoDog, Belkin, and Honest Buildings are scurrying to develop new applications and Web services that can use Green Button data to empower users to take control of their own energy future.33 This wealth of data on individual energy usage is now being leveraged through social media.

The local electricity microgrid is powered by a bank of solar panels connected to a brick substation. Inside the substation are batteries that allow the village to store power during the night or when there is cloud cover. A small computer transmits data back to the company’s offices in Jaipur. Wires on wooden poles transmit the electricity from the substation to scores of homes around the village, providing green electricity for more than 200 residents. Each home is equipped with a smart meter that informs the user how much electricity is being used and what it is costing at different times of the day.38 Green electricity is far less expensive than electricity from India’s national grid, and it eliminates the burning of highly polluting kerosene that is responsible for respiratory and heart diseases common throughout India. A local mother interviewed by the Guardian described how electricity has transformed the life of the village.


pages: 304 words: 82,395

Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schonberger, Kenneth Cukier

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23andMe, Affordable Care Act / Obamacare, airport security, AltaVista, barriers to entry, Berlin Wall, big data - Walmart - Pop Tarts, Black Swan, book scanning, business intelligence, business process, call centre, cloud computing, computer age, correlation does not imply causation, dark matter, double entry bookkeeping, Eratosthenes, Erik Brynjolfsson, game design, IBM and the Holocaust, index card, informal economy, Internet of things, invention of the printing press, Jeff Bezos, Louis Pasteur, Mark Zuckerberg, Menlo Park, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, obamacare, optical character recognition, PageRank, performance metric, Peter Thiel, Post-materialism, post-materialism, random walk, recommendation engine, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, smart grid, smart meter, social graph, speech recognition, Steve Jobs, Steven Levy, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Watson beat the top human players on Jeopardy!

On data used by Nazis in the Netherlands—William Seltzer and Margo Anderson, “The Dark Side of Numbers: The Role of Population Data Systems in Human Rights Abuses,” Social Research 68 (2001), pp. 481–513. [>] On IBM and the Holocaust—Edwin Black, IBM and the Holocaust (Crown, 2003). On the amount of data smart meters collect—See Elias Leake Quinn, “Smart Metering and Privacy: Existing Law and Competing Policies; A Report for the Colorado Public Utility Commission,” Spring 2009 (http://www.w4ar.com/Danger_of_Smart_Meters_Colorado_Report.pdf). See also Joel M. Margolis, “When Smart Grids Grow Smart Enough to Solve Crimes,” Neustar, March 18, 2010 (http://energy.gov/sites/prod/files/gc prod/documents/Neustar_Comments_DataExhibitA.pdf) [>] Fred Cate on notice and consent—Fred H. Cate, “The Failure of Fair Information Practice Principles,” in Jane K.

Washington Post, July 19, 2010 (http://projects.washingtonpost.com/top-secret-america/articles/a-hidden-world-growing-beyond-control/print/). Query, Tim. “Grade Inflation and the Good-Student Discount.” Contingencies Magazine, American Academy of Actuaries, May-June 2007 (http://www.contingencies.org/mayjun07/tradecraft.pdf). Quinn, Elias Leake. “Smart Metering and Privacy: Existing Law and Competing Policies; A Report for the Colorado Public Utility Commission.” Spring 2009 (http://www.w4ar.com/Danger_of_Smart_Meters_Colorado_Report.pdf). Reshef, David, et al. “Detecting Novel Associations in Large Data Sets.” Science (2011), pp. 1518–24. Rosenthal, Jonathan. “Banking Special Report.” The Economist, May 19, 2012, pp. 7–8. Rosenzweig, Phil. “Robert S. McNamara and the Evolution of Modern Management.” Harvard Business Review, December 2010, pp. 87–93 (http://hbr.org/2010/12/robert-s-mcnamara-and-the-evolution-of-modern-management/ar/pr).


pages: 133 words: 42,254

Big Data Analytics: Turning Big Data Into Big Money by Frank J. Ohlhorst

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algorithmic trading, bioinformatics, business intelligence, business process, call centre, cloud computing, create, read, update, delete, data acquisition, DevOps, fault tolerance, linked data, natural language processing, Network effects, pattern recognition, performance metric, personalized medicine, RFID, sentiment analysis, six sigma, smart meter, statistical model, supply-chain management, Watson beat the top human players on Jeopardy!, web application

Thanks to the consolidation of global trading environments and the increased use of programmed trading, the volume of transactions being collected and analyzed is doubling or tripling. Transaction volumes also fluctuate much faster, much wider, and much more unpredictably. Competition among firms is creating more data, simply because sampling for trading decisions is occurring more frequently and at faster intervals. Smart instrumentation. The use of smart meters in energy grid systems, which shifts meter readings from monthly to every 15 minutes, can translate into a multithousandfold increase in data generated. Smart meter technology extends beyond just power usage and can measure heating, cooling, and other loads, which can be used as an indicator of household size at any given moment. Mobile telephony. With the advances in smartphones and connected PDAs, the primary data generated from these devices have grown beyond caller, receiver, and call length.

Many industries fall under the umbrella of new data creation and digitization of existing data, and most are becoming appropriate sources for Big Data resources. Those industries include the following: Transportation, logistics, retail, utilities, and telecommunications. Sensor data are being generated at an accelerating rate from fleet GPS transceivers, RFID (radio-frequency identification) tag readers, smart meters, and cell phones (call data records); these data are used to optimize operations and drive operational BI to realize immediate business opportunities. Health care. The health care industry is quickly moving to electronic medical records and images, which it wants to use for short-term public health monitoring and long-term epidemiological research programs. Government. Many government agencies are digitizing public records, such as census information, energy usage, budgets, Freedom of Information Act documents, electoral data, and law enforcement reporting.

See Data mining Mobile devices Modeling Moore’s Law Mozenda N NAS National Oceanic and Atmospheric Administration (NOAA) National Science Foundation (NSF) Natural language recognition New York Times Noisy data NoSQL (Not only SQL) O Object-based storage systems OLAP systems OOZIE OpenHeatMap Open source technologies availability options pilot projects See also Hadoop Organizational structure Outsourcing P Parallel processing Patents Pentaho Performance measurement Performance-security tradeoff Perlowitz, Bill Pharmaceutical companies Pig Pilot projects Planning Point-of-sale (POS) data Predictive analysis Privacy Problem identification Processing Project management processes Project planning Public information sources Purging of data Q Queries R RAM-based devices Real-time analytics Recruitment of data analytics personnel Red Hat Relational database management system (RDBMS) Research and development (R&D) Resource description framework (RDF) Results Retailers anomalies Big Data use click-stream data data sources goal setting in-memory processing technology organizational culture Retention of data Return on investment (ROI) Risk analysis S SANS SAP Scale-out storage solutions Scaling Scenarios Schmidt, Erik Science Scope of project Scrubbing programs Security backup systems challenges compliance issues data classification data retention intellectual property rules technologies Semantics event-driven data distribution support mapping of technologies trends Semistructured data Sensor data filtering growth of types Silos Sloan Digital Sky Survey Small and medium businesses (SMBs) Smart meters Smartphones Snapshots Social media Software. See Technologies Sources of data. See Data sources Space program Specificity of information Speed-accuracy tradeoff Spring Data SQL limitations NoSQL Integration scaling Stale data Statistical applications Storage Storm Structured data Success, measurement of Supplementary information Supply chain T Tableau Public Taxonomies Team members Technologies application platforms Cassandra cloud computing commodity hardware decision making processing power security storage Web-based tools worst practices See also Hadoop Telecommunications Text analytics Thin provisioning T-Mobile Training Transportation Trends Trusted applications Turk Twitter U United Parcel Service (UPS) Unstructured data complexity of defined forms growth of project goal setting social media’s collection technologies varieties of U.S. census User analysis Utilities sector V Value, extraction of Variety Velocity Vendor lock-in Veracity Videos Video surveillance Villanustre, Flavio Visualization Volume W Walt Disney Company Watson Web-based technologies Web sites click-stream data logs traffic distribution White-box systems Worst practices Wyle Laboratories X XML Y Yahoo


pages: 525 words: 142,027

CIOs at Work by Ed Yourdon

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8-hour work day, Apple's 1984 Super Bowl advert, business intelligence, business process, call centre, cloud computing, crowdsourcing, distributed generation, Flash crash, Googley, Grace Hopper, Infrastructure as a Service, Innovator's Dilemma, inventory management, Julian Assange, knowledge worker, Mark Zuckerberg, Nicholas Carr, rolodex, shareholder value, Silicon Valley, six sigma, Skype, smart grid, smart meter, software as a service, Steve Ballmer, Steve Jobs, Steven Levy, the scientific method, WikiLeaks, Y2K, Zipcar

For example, there may be customers that are generating their own power through solar panels. We’re putting smart meters on everyone’s home so we can tell them—in the future—how much electricity they’re using at different times of the day. If customers want to be more efficient, these smart meters have the intelligence to tell them when they’re using a lot and determine what it is that’s driving usage up. Yourdon: I assume that’s just one small part of the overall buzzword of the “smart grid” that you folks in your industry are looking forward to over the next 10 or 20 years? Blalock: Absolutely. There is lots of transformation coming in that area, and we will be leaders in helping move in that direction. I could talk forever about the things that we see coming, but I do think mobility and business analytics are going to be huge. I think the smart meters and the electric vehicles are two technologies, not necessarily in IT that are going to revolutionize our business in the way people are going to use electricity.

Ellyn: Well, the big one, of course, is the “smart grid.” The problem with that title is that it implies that there is a stupid grid. Yourdon: [laughter] Ellyn: The grid is highly automated now. This is a re-automation of the grid. For example, at one time (this predates me) Detroit Edison had 140 engineers that just operated it. Today it’s done with just a dozen or fewer. As we go into more grid automation and smart meters and we can debate how smart they are, but meters to the extent that homeowners adopt a lot of home automation, and that remains to be seen, but there are a lot of people who are juiced about it. And we start to bring on a fair amount of electrical cars; electric vehicles; and the automation, billing, and management that is going to be in here. It’s a big deal for our industry, a big deal. Great opportunities.

For example, the San Diego Fire Department used Twitter as a mechanism for allowing citizens to report in brush fires and these terrible fires that they have in the fall with everything getting very dry. And that’s actionable and it conveys information back to the organization that they would otherwise not have known. Is there anything of that nature that might be relevant for you? Bohlen: I think that is something that is available, because if you think about it today, we typically learn first about outages through telephone services. That’s beginning to change with the smart meters. That’s a whole new revolution beginning to occur, where you get instantaneous data. Our challenge is to figure out, “Do we want it every 15 minutes? Do we want it every 30 minutes?” Then the question is, “If we get that data every 15 minutes from 1.1 million customers, what do we do with it? What do we want them to do with it? How long do we keep it?” That’s where analytics will really come into play.


pages: 422 words: 104,457

Dragnet Nation: A Quest for Privacy, Security, and Freedom in a World of Relentless Surveillance by Julia Angwin

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AltaVista, Ayatollah Khomeini, barriers to entry, bitcoin, Chelsea Manning, clean water, crowdsourcing, cuban missile crisis, data is the new oil, David Graeber, Debian, Edward Snowden, Filter Bubble, Firefox, GnuPG, Google Chrome, Google Glasses, informal economy, Jacob Appelbaum, Julian Assange, market bubble, market design, medical residency, meta analysis, meta-analysis, mutually assured destruction, prediction markets, price discrimination, randomized controlled trial, RFID, Robert Shiller, Ronald Reagan, security theater, Silicon Valley, Silicon Valley startup, Skype, smart meter, Steven Levy, Upton Sinclair, WikiLeaks, Y2K, Zimmermann PGP

companies are building facial recognition technology into phones and cameras: Emily Steel and Julia Angwin, “Device Raises Fear of Facial Profiling,” Wall Street Journal, July 13, 2011, http://online.wsj.com/article/SB10001424052702303678704576440253307985070.html. technology to monitor your location: Keith Barry, “Insurance Company Telematics Trade Perks for Privacy,” Wired, August 19, 2011, http://www.wired.com/autopia/2011/08/insurance-company-telematics-trade-perks-for-privacy/. wireless “smart” meters: Jim Marston and Joshua Hart, “Should Consumers Participate in Their Utility’s Smart-Meter Program?,” Wall Street Journal, April 12, 2013, http://online.wsj.com/article/SB10001424127887323415304578368683701371280.html. Google has developed Glass: “Glass,” Google Inc., accessed July 22, 2013, http://www.google.com/glass/start/. The confidentiality of personal information: “Protecting Your Answers,” United States Census, 2010, https://www.census.gov/2010census/about/protect.php.

Looking up “blood sugar” could tag you as a possible diabetic by companies that profile people based on their medical condition and then provide drug companies and insurers access to that information. Searching for a bra could trigger an instant bidding war among lingerie advertisers at one of the many online auction houses. And new tracking technologies are just around the corner: companies are building facial recognition technology into phones and cameras, technology to monitor your location is being embedded into vehicles, wireless “smart” meters that gauge the power usage of your home are being developed, and Google has developed Glass, tiny cameras embedded in eyeglasses that allow people to take photos and videos without lifting a finger. * * * Skeptics say: What’s wrong with all of our data being collected by unseen watchers? Who is being harmed? Admittedly, it can be difficult to demonstrate personal harm from a data breach. If Sharon or Bilal is denied a job or insurance, they may never know which piece of data caused the denial.


pages: 49 words: 12,968

Industrial Internet by Jon Bruner

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autonomous vehicles, barriers to entry, computer vision, data acquisition, demand response, en.wikipedia.org, factory automation, Google X / Alphabet X, industrial robot, Internet of things, job automation, loose coupling, natural language processing, performance metric, Silicon Valley, slashdot, smart grid, smart meter, statistical model, web application

Reading electricity usage every 15 minutes — a 2,880-fold increase in resolution from the monthly data it was getting from human meter-readers — the utility can detect power outages and quality problems immediately, and have detailed data on scale and location. In one case, Sumner says, meters in one neighborhood started to show voltage drops that suggested a transformer needed to be replaced. It was early spring and electricity demand was low; without smart meters, the problem would have manifested itself in the summertime when customers turned on their air conditioners. “Had we not done anything with it, we would have had a catastrophic failure,” he says. “Previously, we didn’t know what was going on at the customer level,” Sumner says. “Imagine trying to operate a highway system if all you have are monthly traffic readings for a few spots on the road.


pages: 552 words: 168,518

MacroWikinomics: Rebooting Business and the World by Don Tapscott, Anthony D. Williams

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accounting loophole / creative accounting, airport security, Andrew Keen, augmented reality, Ayatollah Khomeini, barriers to entry, bioinformatics, Bretton Woods, business climate, business process, car-free, carbon footprint, citizen journalism, Clayton Christensen, clean water, Climategate, Climatic Research Unit, cloud computing, collaborative editing, collapse of Lehman Brothers, collateralized debt obligation, colonial rule, corporate governance, corporate social responsibility, crowdsourcing, death of newspapers, demographic transition, distributed generation, don't be evil, en.wikipedia.org, energy security, energy transition, Exxon Valdez, failed state, fault tolerance, financial innovation, Galaxy Zoo, game design, global village, Google Earth, Hans Rosling, hive mind, Home mortgage interest deduction, interchangeable parts, Internet of things, invention of movable type, Isaac Newton, James Watt: steam engine, Jaron Lanier, jimmy wales, Joseph Schumpeter, Julian Assange, Kevin Kelly, knowledge economy, knowledge worker, Marshall McLuhan, medical bankruptcy, megacity, mortgage tax deduction, Netflix Prize, new economy, Nicholas Carr, oil shock, online collectivism, open borders, open economy, pattern recognition, peer-to-peer lending, personalized medicine, Ray Kurzweil, RFID, ride hailing / ride sharing, Ronald Reagan, scientific mainstream, shareholder value, Silicon Valley, Skype, smart grid, smart meter, social graph, social web, software patent, Steve Jobs, text mining, the scientific method, The Wisdom of Crowds, transaction costs, transfer pricing, University of East Anglia, urban sprawl, value at risk, WikiLeaks, X Prize, young professional, Zipcar

“If you ask the gas company to do an analysis of people’s water heaters and then to ask me, ‘Robin, do you want us to turn it down and save yourself $40 over the year?’ I’ll say, ‘Of course.’” To date, 8.3 million homes in America have been equipped with smart meters covering 6 percent of the population. The number is set to grow to 33 million by 2011, while the worldwide total will reach about 155 million.12 Cisco Systems estimates that by the time it all gets built out, the energy grid will be one thousand times larger than today’s Internet.13 Meanwhile, a vast and growing number of companies are already lining up to offer consumers tools to help them make sense of the smart meter data. Typically leadership does not come from the companies that dominated the old industrial era of energy, but from a new generation of companies that understand the age of networked intelligence.

Like other tech players in the emerging energy economy, Google is actively lobbying for open standards so that consumers are able to buy smart appliances, thermostats, or energy monitors from different companies and have them talk to each other. Personal Carbon Markets Pilots under way in Europe show how far the open-source grid concept could go. Homes across Europe, including Manchester, Birmingham, Bristol, Ruse (Bulgaria), and Cluj (Romania), have been equipped with advanced smart meters and sensor networks that track energy usage, efficiency, and overall household emissions to generate a real-time carbon footprint. Users pull up a Web-based interface to analyze the sources of their emissions, compare their home with the neighborhood, forecast household savings, or control their energy use remotely from a PC or a mobile phone.14 Like Google’s PowerMeter, the system developed by the Manchester City Council and its partners is an open platform, which means it can be seamlessly integrated with other applications for mobiles, TV, and social networks.

The mere fact that neighborhood trading schemes and personal carbon allowances are even being debated is a sign that the efforts under way to make our infrastructure more intelligent and interactive will pay large dividends. As we argued in the previous chapter, it’s easier to remain aloof about climate change when the connections between our actions and the climate seem vague and hard to measure. But it becomes harder to simply ignore one’s personal responsibility when the smart meter on your wall not only shows you your real-time carbon footprint, but also compares your score to the neighborhood average and offers you tips on how to improve. Coupled with a real price for carbon, this new transparency and interactivity provides the fuel for truly creative responses to some of the world’s great challenges. And while the focus is on energy and climate change today, there are equivalent opportunities in many other sectors.

Big Data at Work: Dispelling the Myths, Uncovering the Opportunities by Thomas H. Davenport

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Automated Insights, autonomous vehicles, bioinformatics, business intelligence, business process, call centre, chief data officer, cloud computing, data acquisition, Edward Snowden, Erik Brynjolfsson, intermodal, Internet of things, Jeff Bezos, knowledge worker, Mark Zuckerberg, move fast and break things, Narrative Science, natural language processing, Netflix Prize, New Journalism, recommendation engine, RFID, self-driving car, sentiment analysis, Silicon Valley, smart grid, smart meter, social graph, sorting algorithm, statistical model, Tesla Model S, text mining

These included: • Telecom firms, which had lots of data, but for some reason did not take advantage of it (perhaps because they had historically been a regulated monopoly or because they were busy with mergers and acquisitions) Chapter_02.indd 43 03/12/13 11:42 AM 44  big data @ work • Media and entertainment firms, which underachieved because they had decision cultures based on intuition and gut feel, and didn’t know how to assess whether people were looking at their content or not • Retailers had great data from point-of-sale systems, but most have underachieved with it until recently; Tesco and to some degree Walmart have been higher achievers • Traditional banks have massive amounts of data on the money their customers consume and save, but for the most part they have been underachievers in helping those customers make sense of it all and presenting targeted marketing offers to them • Electric utilities have been talking about the “smart grid” for a while, but are still a long way from achieving it; apart from some limited rollouts of smart metering devices and time-of-day ­pricing, very little thus far has happened in the United States This environment has changed dramatically with the advent of big data. Many of the also-ran industries in the previous generation of analytics can be leaders in the big data race, although in order to do so they need to change their behaviors and attitudes. Big data will be available in their business and industry, but the laggards need to work harder to take advantage of it than they did with traditional analytics.

Companies adopting production-class big data environments need faster and lower-cost ways to process large amounts of Chapter_05.indd 126 03/12/13 1:04 PM Technology for Big Data   127 Figure 5-3 A big data technology ecosystem Web logs HDFS Images and videos Operational systems Social media Documents and PDFs MapReduce Data warehouses Data marts and ODS Source: SAS Best Practices. atypical data. Think of the computing horsepower needed by energy companies to process data streaming from smart meters, or by retailers tracking in-store smartphone navigation paths, or LinkedIn’s ­reconciliation of millions of colleague recommendations. Or consider a gaming software company’s ability to connect consumers with their friends via online video games. “Before big data, our legacy architecture was fairly typical,” an executive explained in an interview. “Like most companies, we had data warehouses and lots of ETL programs and our data was very latent.


pages: 606 words: 157,120

To Save Everything, Click Here: The Folly of Technological Solutionism by Evgeny Morozov

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3D printing, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, augmented reality, Automated Insights, Berlin Wall, big data - Walmart - Pop Tarts, Buckminster Fuller, call centre, carbon footprint, Cass Sunstein, choice architecture, citizen journalism, cloud computing, cognitive bias, crowdsourcing, data acquisition, Dava Sobel, disintermediation, East Village, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, Firefox, Francis Fukuyama: the end of history, frictionless, future of journalism, game design, Gary Taubes, Google Glasses, illegal immigration, income inequality, invention of the printing press, Jane Jacobs, Jean Tirole, Jeff Bezos, jimmy wales, Julian Assange, Kevin Kelly, Kickstarter, license plate recognition, lone genius, Louis Pasteur, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Narrative Science, Nicholas Carr, packet switching, PageRank, Paul Graham, Peter Singer: altruism, Peter Thiel, pets.com, placebo effect, pre–internet, Ray Kurzweil, recommendation engine, Richard Thaler, Ronald Coase, Rosa Parks, self-driving car, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, Slavoj Žižek, smart meter, social graph, social web, stakhanovite, Steve Jobs, Steven Levy, Stuxnet, technoutopianism, the built environment, The Chicago School, The Death and Life of Great American Cities, the medium is the message, The Nature of the Firm, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, transaction costs, urban decay, urban planning, urban sprawl, Vannevar Bush, WikiLeaks

But ought we to consider other aspects of the Santa Monica initiative? To return to Albert Hirschman’s futility-perversity-jeopardy triad, the first of those concerns doesn’t seem to be a problem. Unless they find a way to easily circumvent it, drivers will likely comply with the smart metering system; there’s no good reason to deem the scheme futile—at least not yet. A charge of perversity, too, is hard to substantiate: it’s not obvious how smart sensor-based metering could worsen the parking situation. What about jeopardy? Is there a “previous, precious accomplishment,” to use Hirschman’s language, that smart metering endangers? There is, of course, the standard set of criticisms associated with situational crime prevention discussed at length in Chapter 6. Perhaps, if we universalize this scheme and prohibit citizens from breaking the law everywhere, we’ll end up with morally deficient citizens who won’t do the right thing unless the technological infrastructure explicitly robs them of the opportunity to do the wrong thing.

Victorian Trains and Montana Huts In a way, various smart systems like the one in Santa Monica suffer from the same problem as self-tracking: if quantification gives us an opportunity to save three gallons of water without questioning how this water gets into our bathrooms to begin with, then perhaps the savings are not as significant as we believe and maybe they even detract from our seeking more innovative ways of reforming the water system. In this sense, the Santa Monica scheme is futile (in Hirschman’s sense) in that it doesn’t really alter how drivers and citizens relate to the problems of parking and congestion. Potentially, the scheme is also perverse, especially if it gives us citizens who no longer feel the need to show concern for other drivers, the city, or the environment whenever smart meters and other forms of policing are missing. Such schemes thwart the development of what we earlier called “narrative imagination” and what some design theorists call “system thinking”—an intellectual approach that grants complexity to both the causes and effects of a problem and, instead of reducing the roots of that problem to a handful of easily identifiable and controllable factors, seeks to redescribe them in the language of relations, structures, and processes.

The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences by Rob Kitchin

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business intelligence, business process, cellular automata, Celtic Tiger, cloud computing, collateralized debt obligation, conceptual framework, congestion charging, corporate governance, correlation does not imply causation, crowdsourcing, discrete time, George Gilder, Google Earth, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, late capitalism, linked data, Masdar, means of production, Nate Silver, natural language processing, openstreetmap, pattern recognition, platform as a service, recommendation engine, RFID, semantic web, sentiment analysis, slashdot, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, software as a service, statistical model, supply-chain management, the scientific method, The Signal and the Noise by Nate Silver, transaction costs

There are several ways in which automated data are being generated, some of which are a by-product of a system rather than its primary purpose. Automated surveillance As surveillance technologies have become digital in nature and networked together it has become possible to automate various aspects of monitoring systems, and to add new techniques, to more effectively and efficiently track and trace the usage of different systems and places. An example of a manual form of surveillance that is increasingly becoming automated is smart metering. Here, automatic meter reading (AMR) technology is used to monitor and communicate utility usage without the need for manual reading (Hancke et al. 2013). Moreover, it can do these tasks on a continuous basis enabling a supplier to track usage in real-time, which has utility in matching demand with supply and in finding faults/leakage in a system. It also offers a means to undertake automated billing, reducing staff overheads.

They have also proposed: individuals entering into partnerships with developers wherein they can more proactively select what data they are willing to release, to whom, and under what circumstances; companies providing users access to their own data in a usable format for their own benefit; and that companies ‘share the wealth’ in the monetisation of personal data (Tene and Polonetsky 2012; Rubinstein 2013). An example of such a co-beneficial sharing of the wealth of data are smart grids where data generated by smart meters concerning household electricity consumption are used by the power company to produce supply efficiencies, with households supplied with apps that enable them to monitor their own use and adapt behaviour to save money. Industry, by and large, wants either the present provisions to continue or to be relaxed, with privacy administered through market-led regulation that does not stifle the economic leveraging of data.


pages: 118 words: 35,663

Smart Machines: IBM's Watson and the Era of Cognitive Computing (Columbia Business School Publishing) by John E. Kelly Iii

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AI winter, call centre, carbon footprint, crowdsourcing, demand response, discovery of DNA, Erik Brynjolfsson, future of work, Geoffrey West, Santa Fe Institute, global supply chain, Internet of things, John von Neumann, Mars Rover, natural language processing, optical character recognition, pattern recognition, planetary scale, RAND corporation, RFID, Richard Feynman, Richard Feynman, smart grid, smart meter, speech recognition, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!

They use probability theory to identify the mostly likely effects of the variables then perform a series of analyses or simulations, based on a subset of the possibilities, to determine the most likely outcomes. Previously, using less sophisticated techniques, it might take days of computation to arrive at a useful result; now it can be done in seconds. In addition, as models are tested against real-world outcomes, they learn and get better over time. To see how stochastic optimization works, consider an electricity grid. Today, many electrical-distribution systems are outfitted with smart meters that make it possible for consumers and operators of the system to know how much energy is being used in real time. Based on that information, consumers can make informed choices about their consumption levels, and operators can predict with a reasonable certainty what demand will be at a specific time. But what happens if the weather changes suddenly or there’s a failure in the system and power is in short supply?


pages: 443 words: 112,800

The Third Industrial Revolution: How Lateral Power Is Transforming Energy, the Economy, and the World by Jeremy Rifkin

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3D printing, additive manufacturing, Albert Einstein, barriers to entry, borderless world, carbon footprint, centre right, collaborative consumption, collaborative economy, Community Supported Agriculture, corporate governance, decarbonisation, distributed generation, en.wikipedia.org, energy security, energy transition, global supply chain, hydrogen economy, income inequality, informal economy, invisible hand, Isaac Newton, job automation, knowledge economy, manufacturing employment, marginal employment, Martin Wolf, Masdar, megacity, Mikhail Gorbachev, new economy, oil shale / tar sands, oil shock, open borders, peak oil, Ponzi scheme, post-oil, purchasing power parity, Ray Kurzweil, Ronald Reagan, Silicon Valley, Simon Kuznets, Skype, smart grid, smart meter, Spread Networks laid a new fibre optics cable between New York and Chicago, supply-chain management, the market place, The Wealth of Nations by Adam Smith, Thomas Malthus, too big to fail, transaction costs, trickle-down economics, urban planning, urban renewal, Yom Kippur War, Zipcar

These employment estimates are small, however, in comparison to the jobs that will be created with the €1 trillion the European Commission now projects is needed for public and private investment over the next ten years to bring the distributed smart grid network online across the world’s largest economy.41 Today’s idea of a distributed smart grid was not what most of the major ICT companies had in mind when they first began to talk about intelligent utility networks. Their early vision was for a centralized smart grid. The companies foresaw digitalizing the existing power grid, with the placement of smart meters and censors, to allow utility companies to collect information remotely, including keeping up-to-the-minute information on electricity flows. The goal was to improve the efficiency of moving electricity across the grid, reduce the costs of maintenance, and keep more accurate records on customer usage. Their plans were reformist but not revolutionary. As far as I knew, there was little discussion about using Internet technology to transform the power grid into an interactive info-energy network that would allow millions of people to generate their own renewable energy and share electrons with one another.

CPS and the city have already saved 142 megawatts of electricity in the past two years and have set a target of a 771-megawatt reduction in electricity use by 2020. Building on their already significant achievement in renewable energy generation of 910 megawatts, San Antonio expects to generate 1,500 megawatts of renewable energy by 2020.30 CPS is also beginning to assemble a smart grid, with a two-year initiative to install 40,000 smart meters in buildings across the metropolitan region. CPS has also entered into an agreement with GM to provide power charging stations for the Chevy Volt.31 All in all, San Antonio is on its way toward a TIR economy. COUNTERINTUITIVE COMMERCE The most important challenge facing CPS is transforming its business model and management style to accommodate the requirements of a new distributed-energy era managed by Internet communication technology.


pages: 219 words: 63,495

50 Future Ideas You Really Need to Know by Richard Watson

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23andMe, 3D printing, access to a mobile phone, Albert Einstein, artificial general intelligence, augmented reality, autonomous vehicles, BRICs, Buckminster Fuller, call centre, clean water, cloud computing, collaborative consumption, computer age, computer vision, crowdsourcing, dark matter, dematerialisation, digital Maoism, Elon Musk, energy security, failed state, future of work, Geoffrey West, Santa Fe Institute, germ theory of disease, happiness index / gross national happiness, hive mind, hydrogen economy, Internet of things, Jaron Lanier, life extension, Marshall McLuhan, megacity, natural language processing, Network effects, new economy, oil shale / tar sands, pattern recognition, peak oil, personalized medicine, phenotype, precision agriculture, profit maximization, RAND corporation, Ray Kurzweil, RFID, Richard Florida, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Skype, smart cities, smart meter, smart transportation, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, supervolcano, telepresence, The Wisdom of Crowds, Thomas Malthus, Turing test, urban decay, Vernor Vinge, Watson beat the top human players on Jeopardy!, web application, women in the workforce, working-age population, young professional

the condensed idea Locally produced and distributed energy timeline 1816 First energy company established in USA 1821 First electric motor 1839 Discovery of photovoltaic effect 1882 First hydroelectric power plant 1888 Tesla invents AC alternator 1892 General Electric founded 1980 First US wind farm 2030 Wind farms start to be demolished 2035 Most homes engaged in local energy trading 2040 Personal energy harvesters become mandatory 13 Smart cities Stuff that was once “dumb” is becoming smart. Pipes, roads, buildings and even whole cities are no exception. Whether it’s smart meters for water supply, appliances that work out when it’s best to be switched on, or dynamic tolling for roads, we can expect more efficiency, less waste, faster fixing and more pricing that’s responsive to real-time demand. Back in the 1990s, David Gelernter, a professor of computer science at Yale University, wrote a book called Mirror Worlds. In it he described a world that had a digital reflection.


pages: 252 words: 70,424

The Self-Made Billionaire Effect: How Extreme Producers Create Massive Value by John Sviokla, Mitch Cohen

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Cass Sunstein, Colonization of Mars, Daniel Kahneman / Amos Tversky, Elon Musk, Frederick Winslow Taylor, game design, global supply chain, James Dyson, Jeff Bezos, John Harrison: Longitude, Jony Ive, loss aversion, Mark Zuckerberg, market design, paper trading, RAND corporation, randomized controlled trial, Richard Thaler, risk tolerance, self-driving car, Silicon Valley, smart meter, Steve Ballmer, Steve Jobs, Steve Wozniak, Tony Hsieh, Toyota Production System, young professional

You know when you have a Producer in the room. We conducted an interview recently with a candidate whose Producer status was unmistakable. When asked about a business he would like to pursue, he outlined a consulting practice aimed at helping organizations manage the risks of damage to the electric grid. Over the course of a twenty-minute conversation, he explained his view that the current thrust of investment in smart meters and at-the-source energy use management was overemphasized (as he put it, a relatively small problem with relatively limited profit potential) and that the real opportunity centered around the aging utilities’ infrastructure, grid damage caused by intensifying natural disasters, security concerns, and the risks that massive failure poses to all types of organizations—federal governments, local municipalities, insurance companies, as well as utilities, and other businesses.


pages: 903 words: 235,753

The Stack: On Software and Sovereignty by Benjamin H. Bratton

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1960s counterculture, 3D printing, 4chan, Ada Lovelace, additive manufacturing, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Berlin Wall, bioinformatics, bitcoin, blockchain, Buckminster Fuller, Burning Man, call centre, carbon footprint, carbon-based life, Cass Sunstein, Celebration, Florida, charter city, clean water, cloud computing, connected car, corporate governance, crowdsourcing, cryptocurrency, dark matter, David Graeber, deglobalization, dematerialisation, disintermediation, distributed generation, don't be evil, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, Eratosthenes, ethereum blockchain, facts on the ground, Flash crash, Frank Gehry, Frederick Winslow Taylor, future of work, Georg Cantor, gig economy, global supply chain, Google Earth, Google Glasses, Guggenheim Bilbao, High speed trading, Hyperloop, illegal immigration, industrial robot, information retrieval, intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, Jony Ive, Julian Assange, Khan Academy, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, performance metric, personalized medicine, Peter Thiel, phenotype, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Sand Hill Road, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, smart cities, smart grid, smart meter, social graph, software studies, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Startup school, statistical arbitrage, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, Superbowl ad, supply-chain management, supply-chain management software, TaskRabbit, the built environment, The Chicago School, the scientific method, Torches of Freedom, transaction costs, Turing complete, Turing machine, Turing test, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, WikiLeaks, working poor, Y Combinator

As discussed in the Cloud chapter, the interweaving of multiple and incongruous sovereign claims often hinges on how emergent platforms problematize and repurpose existing platforms (such as the intercontinental highway network and its federal stewards), and by how existing platforms steer that emergence toward its own publics. Moreover, the psychological anguish of relinquishing driver status would likely ensure whatever policies are initially put in place may be irrational and absurd. Today the populist backlash against smart meters installed in residences as end points of more efficiently managed energy networks is nothing compared to the resistance (both legitimate and delusional) that will meet the sunsetting of human-driven automobiles. In important ways, however, the moral high ground may be with the robots. Gary Marcus writes, “Eventually (though not yet) automated vehicles will be able to drive better, and more safely than you can; no drinking, no distraction, better reflexes, and better awareness (via networking) of other vehicles.

See also land versus sea beyond the line, 30 French versus English concepts of, 380n15 search, 112, 118, 136–138, 202–203, 332, 342 “Search for Artificial Stellar Sources of Infra-Red Radiation” (Dyson), 106 Seasteading Institute, 180 secession, 177, 306–307, 309–314, 336, 447n43 second planetary computer, 300–301 secular disenchantment, 426n46 Securities and Exchange Commission, Regulation National Market System, 451n63 securitized entertainment, 156 security imagine no lines/imagine nothing but lines, 324, 355 interfacial security regimes, 345 post-Oklahoma City Bombing architecture, 322–323 trading for, 445n37 utopia of, 311, 321–325 security Apps, 241 seeing like a state, 8, 106, 120, 333 self, the care of, 126, 261 dissolution of, 263 fabrication of, 126 mirror reflection of, 253, 264 quantification of, 258–263 self-knowledge through numbers, 261 technologies of, 348 self-identity of the User, 258, 261, 263, 274, 345, 362 self-image geographic, 144 human, 71, 253 of the User, 253, 261 self-knowledge through numbers, 261 self-mapping swarms, 265 self-realization, 129 self-reflection of the User, 252–253 semantics of the address, 193 semantic web, 202–203 “sensing like a state,” 340 sensing networks, 303 sensors blanketing Earth, 97, 180, 192, 198, 295 design questions, 342 forming a Cloud of machine sensation, 340 future of, 342 mobile phones as, 342 as User/User as, 340 September 11, 2001, terrorist attacks, 321, 363 Serres, Michel, 1, 19, 75, 210, 222–223, 238 Shanghai World Expo (2010), 257–258, 285, 289 Shannon information, 205, 296–297 Shannon's law (Shannon-Hartley Theorem), 92, 393n52 Shaping Things (Sterling), 201 signaling, 148 “Silicon Valley's Ultimate Exit” (Srinivasan), 312–314 Simondon, Gilbert, 272, 405n26 Singleton, Benedict, 43–44, 288 singularity, 401n51 Siri for iOS, 277, 286 skeuomorphic interface designs, 139, 224, 339 skin. See also Earth designability of, 352–353 everywhere is, 355 human, 88 question of, 392n42 Sky Ear (Haque), 392n40 SkyGrabber, 401n45 Sleep Dealer (Rivera), 308 Smarr, Larry, 267–270, 285, 288 smart cities, 147–148, 160–162, 179, 181 smart dust, 201 smart grids, 92–96, 393n53 smart meters, resistance to, 283 smart space design questions, 201 smart surfaces, 198 Smart2020 (Climate Group), 93–94 Smithson, Robert, 53, 86, 178 Snow Crash (Stephenson), 400n42 Snowden, Edward, 35, 121, 287, 405n16 social body, inside/outside of, 22 social capital/social debt, 127 social imaginary, 233 socialism, 332 socialist pricing problem, 333, 369 social media, 9, 262–263, 428n58, 431n70 social nudity, 285 social space, 125–128, 169, 424n41 social systems City layer as, 157–159 classlessness in, 439n65 inclusion/exclusion in, 308–309, 311–312, 317 social-technical form, emergence of a new, 176 social Turingism, 80 social wallet, 127 software architecture, 166 constructing new civilizations, 181 design, 254–255 envelopes, 167 interfaciality, 167 language versus technology dichotomy, 60 law as code, 327 mixed programs, designing for, 168–172 and sovereignty, 20, 303 translegal forms, 355–356 software espionage, 398n21 software program, 43 software-space coprogramming, 237–238 solar energy, 106 Soleri, Paolo, 178–179 solidification and liquefaction, 379n9.


pages: 471 words: 109,267

The Verdict: Did Labour Change Britain? by Polly Toynbee, David Walker

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banking crisis, Big bang: deregulation of the City of London, call centre, central bank independence, congestion charging, Corn Laws, Credit Default Swap, decarbonisation, deglobalization, deindustrialization, Etonian, failed state, first-past-the-post, Frank Gehry, gender pay gap, Gini coefficient, high net worth, hiring and firing, illegal immigration, income inequality, knowledge economy, labour market flexibility, market bubble, millennium bug, North Sea oil, Northern Rock, offshore financial centre, pension reform, Plutocrats, plutocrats, Ponzi scheme, profit maximization, purchasing power parity, shareholder value, Skype, smart meter, stem cell, The Spirit Level, too big to fail, University of East Anglia, working-age population, Y2K

The geopolitics of carbon shifted east and the EU became sensitive to its dependency after Russia started using its gas and oil as a diplomatic tool: why manoeuvre tanks when you can turn off the taps? By 2015 the UK would depend on imports of gas for 75 per cent of supply, and the regulator Ofgem said the UK gas market faced a cliff edge in 2015. To secure supply and cut carbon, Ofgem said the UK should invest £200 billion by 2020 in smart meters, transmission, renewable heating, wind and nuclear. The challenge was ideological as much as practical because cutting carbon meant more state action. Liberalized gas markets simply did not give firms enough incentive to invest – even the CBI agreed with that. Of course the UK still sat on top of millions of tonnes of potentially usable carbon. Coal was a sore subject for Labour. They wanted to mine it, as a gesture to their heartlands, but only ‘cleanly’.

Industry 4.0: The Industrial Internet of Things by Alasdair Gilchrist

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3D printing, additive manufacturing, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, business intelligence, business process, chief data officer, cloud computing, connected car, cyber-physical system, deindustrialization, fault tolerance, global value chain, Google Glasses, hiring and firing, industrial robot, inflight wifi, Infrastructure as a Service, Internet of things, inventory management, job automation, low skilled workers, millennium bug, pattern recognition, platform as a service, pre–internet, race to the bottom, RFID, Skype, smart cities, smart grid, smart meter, smart transportation, software as a service, stealth mode startup, supply-chain management, trade route, web application, WebRTC, WebSocket, Y2K

The networking of these digital things will also provide a huge spinoff for telecom companies and Internet service providers who will have to provide the traffic transportation between devices. Indeed, telecom companies are predicting huge increases in the number of SIMS and data modems integrated into all sorts of remote devices, such as vending machines, connected cars, trucks for fleet management, smart meters, and even remote health monitoring equipment, by 2020. Automation is the way forward and, as we have just seen, it relies heavily on effective M2M in the process chain. M2M should play a large part in the business convergence and digital transformation process, as it not only improves productivity through overall equipment effectiveness but also allows for new and innovative business models.

Frugal Innovation: How to Do Better With Less by Jaideep Prabhu Navi Radjou

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3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, barriers to entry, Baxter: Rethink Robotics, Bretton Woods, business climate, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cloud computing, collaborative consumption, collaborative economy, connected car, corporate social responsibility, crowdsourcing, Elon Musk, financial innovation, global supply chain, income inequality, industrial robot, Internet of things, job satisfaction, Khan Academy, Kickstarter, late fees, Lean Startup, low cost carrier, M-Pesa, Mahatma Gandhi, megacity, minimum viable product, more computing power than Apollo, new economy, payday loans, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, precision agriculture, race to the bottom, reshoring, ride hailing / ride sharing, risk tolerance, Ronald Coase, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, software as a service, Steve Jobs, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, transaction costs, unbanked and underbanked, underbanked, women in the workforce, X Prize, yield management, Zipcar

He believes that, much like the telecoms sector after its liberalisation, Europe’s energy-sector deregulation will create competition, and push firms towards more frugal, distributed energy systems. Digitisation involves the convergence of energy technologies and digital tools that help to create connected homes and buildings. This convergence, Mestrallet believes, will help customers use energy more responsibly and cost-effectively (thanks to smart meters) and even enable some to produce their own energy (with advanced home-energy storage technologies). Deregulation is not the only reason utility firms such as GDF Suez are investing in decentralised and digitised energy-production systems. The bigger motivation is to respond to a structural economic trend not seen since the first world war: the deceleration of energy consumption in developed countries.


pages: 458 words: 135,206

CTOs at Work by Scott Donaldson, Stanley Siegel, Gary Donaldson

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Amazon Web Services, bioinformatics, business intelligence, business process, call centre, centre right, cloud computing, computer vision, connected car, crowdsourcing, data acquisition, distributed generation, domain-specific language, glass ceiling, pattern recognition, Pluto: dwarf planet, Richard Feynman, Richard Feynman, shareholder value, Silicon Valley, Skype, smart grid, smart meter, software patent, thinkpad, web application, zero day

We simply don't have the time or resources to get deeply engaged with industry standards bodies. Those can be all consuming and we've got a company to run. We have a tremendous amount of interaction with customers and the technologists within the customer base. That's where most of our new product ideas come from. S. Donaldson: What are examples of some of the partners that you deal with? Tolnar: Examples would be smart metering companies, they're in our space, but in an adjacent space. Other partners could include Siemens, SAIC, and Schneider Electric. They're in adjacent space with very little overlap. What we always try to do is make a build-buy-partner decision. If we've got a sustainable differentiation in intellectual property, we will typically build. If not, and we see it could become a crowded space or already is a crowded space, then we typically make a partner decision.


pages: 497 words: 150,205

European Spring: Why Our Economies and Politics Are in a Mess - and How to Put Them Right by Philippe Legrain

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3D printing, Airbnb, Asian financial crisis, bank run, banking crisis, barriers to entry, Basel III, battle of ideas, Berlin Wall, Big bang: deregulation of the City of London, Bretton Woods, BRICs, British Empire, business process, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Celtic Tiger, central bank independence, centre right, cleantech, collaborative consumption, collapse of Lehman Brothers, collective bargaining, corporate governance, credit crunch, Credit Default Swap, crony capitalism, currency manipulation / currency intervention, currency peg, debt deflation, Diane Coyle, Downton Abbey, Edward Glaeser, Elon Musk, en.wikipedia.org, energy transition, eurozone crisis, fear of failure, financial deregulation, first-past-the-post, forward guidance, full employment, Gini coefficient, global supply chain, Growth in a Time of Debt, hiring and firing, hydraulic fracturing, Hyman Minsky, Hyperloop, immigration reform, income inequality, interest rate derivative, Irish property bubble, James Dyson, Jane Jacobs, job satisfaction, Joseph Schumpeter, Kenneth Rogoff, labour market flexibility, labour mobility, liquidity trap, margin call, Martin Wolf, mittelstand, moral hazard, mortgage debt, mortgage tax deduction, North Sea oil, Northern Rock, offshore financial centre, oil shale / tar sands, oil shock, open economy, price stability, private sector deleveraging, pushing on a string, quantitative easing, Richard Florida, rising living standards, risk-adjusted returns, Robert Gordon, savings glut, school vouchers, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart grid, smart meter, software patent, sovereign wealth fund, Steve Jobs, The Death and Life of Great American Cities, The Wealth of Nations by Adam Smith, too big to fail, total factor productivity, Tyler Cowen: Great Stagnation, working-age population, Zipcar

But technology also offers exciting new opportunities to make better use of our existing assets. Smart electricity meters in your home could turn the washing machine off and the heating down at peak times when prices are high and also allow you to sell surplus electricity to the grid from solar panels or a wind turbine on your roof. A global pioneer is Italy’s Enel, the state-owned energy utility, which has deployed more than 30 million smart meters to its customers since 2001.552 The internet is also making it easier to connect people who want to rent out rooms, cars and all sorts of other things with those who want to borrow them – a new sharing economy that offers huge potential for growth. Airbnb, a company based in San Francisco, allows people to rent out accommodation for the night; by the end of 2013 ten million people had used its services, many of them in Europe.553 It now has several European rivals: Wimdu and 9flats, both based in Berlin, and London-based onefinestay, which also offers upmarket services.


pages: 510 words: 120,048

Who Owns the Future? by Jaron Lanier

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3D printing, 4chan, Affordable Care Act / Obamacare, Airbnb, augmented reality, automated trading system, barriers to entry, bitcoin, book scanning, Burning Man, call centre, carbon footprint, cloud computing, computer age, crowdsourcing, David Brooks, David Graeber, delayed gratification, digital Maoism, en.wikipedia.org, facts on the ground, Filter Bubble, financial deregulation, Fractional reserve banking, Francis Fukuyama: the end of history, George Akerlof, global supply chain, global village, Haight Ashbury, hive mind, if you build it, they will come, income inequality, informal economy, invisible hand, Jacquard loom, Jaron Lanier, Jeff Bezos, job automation, Kevin Kelly, Khan Academy, Kickstarter, Kodak vs Instagram, life extension, Long Term Capital Management, Mark Zuckerberg, meta analysis, meta-analysis, moral hazard, mutually assured destruction, Network effects, new economy, Norbert Wiener, obamacare, packet switching, Peter Thiel, place-making, Plutocrats, plutocrats, Ponzi scheme, post-oil, pre–internet, race to the bottom, Ray Kurzweil, rent-seeking, reversible computing, Richard Feynman, Richard Feynman, Ronald Reagan, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, smart meter, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, Ted Nelson, The Market for Lemons, Thomas Malthus, too big to fail, trickle-down economics, Turing test, Vannevar Bush, WikiLeaks

Chapter 22. Who Will Do What? 1. http://www.slate.com/articles/technology/technology/2012/05/facebook_ipo_has_social_networking_supplanted_real_innovation_in_silicon_valley_.html. Chapter 26. Financial Identity 1. See Tim Wu’s book The Master Switch (New York: Knopf, 2010). Chapter 28. The Interface to Reality 1. http://www.firstround.com/our_focus/. 2. http://www.naturalnews.com/036476_smart_meters_hacking_privacy.html. Chapter 29. Creepy 1. See http://www.fellowgeek.com/a-US-security-firm-hacked-by-Anonymous-ix1113.html and http://www.esecurityplanet.com/hackers/panda-security-hacked-lulzsec-is-your-website-safe.html. 2. http://cs-www.cs.yale.edu/homes/freeman/lifestreams.html. 3. See http://totalrecallbook.com/. Seventh Interlude: Limits Are for Mortals 1. David Brooks, “The Creative Monopoly,” New York Times, April 23, 2012. 2. http://blakemasters.tumblr.com/post/21169325300/peter-thiels-cs183-startup-class-4-notes-essay. 3. http://www.dailydot.com/society/facebook-mourning-jenna-ness-death/. 4. http://www.slate.com/articles/health_and_science/human_nature/2009/01/night_of_the_living_dad.html. 5. http://www.huffingtonpost.com/2012/08/21/tupac-hologram-elvis-presley-marilyn-monroe_n_1818715.html. 6.


pages: 879 words: 233,093

The Empathic Civilization: The Race to Global Consciousness in a World in Crisis by Jeremy Rifkin

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agricultural Revolution, Albert Einstein, back-to-the-land, British Empire, carbon footprint, collaborative economy, death of newspapers, delayed gratification, distributed generation, en.wikipedia.org, energy security, feminist movement, global village, hydrogen economy, illegal immigration, income inequality, income per capita, interchangeable parts, Internet Archive, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, James Watt: steam engine, Johann Wolfgang von Goethe, labour mobility, Mahatma Gandhi, Marshall McLuhan, means of production, megacity, meta analysis, meta-analysis, Milgram experiment, new economy, New Urbanism, Norbert Wiener, out of africa, Peace of Westphalia, peak oil, planetary scale, Simon Kuznets, Skype, smart grid, smart meter, supply-chain management, surplus humans, the medium is the message, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, transaction costs, upwardly mobile, uranium enrichment, working poor, World Values Survey

The fourth pillar, the reconfiguration of the power grid along the lines of the Internet, allowing businesses and homeowners to produce their own energy and share it with each other, is just now being tested by power companies in Europe, the United States, Japan, China, and other countries. The smart intergrid is made up of three critical components. Mini-grids allow homeowners, small- and medium-size enterprises (SMEs), and large-scale economic enterprises to produce renewable energy locally—through solar cells, wind power, small hydropower, animal and agricultural waste, and garbage—and use it off-grid for their own electricity needs. Smart metering technology allows local producers to more effectively sell their energy back to the main power grid, as well as accept electricity from the grid, making the flow of electricity bidirectional. The next phase in smart grid technology is embedding sensing devices and chips throughout the grid system, connecting every electrical appliance. Software allows the entire power grid to know how much energy is being used, at any time, anywhere on the grid.