The Industrial Internet of Things

A Beginners Guide to the Next Industrial Revolution

What Is The Internet of Things? The Industrial Internet? The Industrial Internet of Things?

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And how about Big Data, Machine Learning, Machine to Machine (m2m) Communication, Industry 4.0? Read on.

The Internet of Things

The Internet of things (IoT) is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to connect and exchange data.[1][2][3] Each thing is uniquely identifiable through its embedded computing system but is able to inter-operate within the existing Internet infrastructure. Experts estimate that the IoT will consist of about 30 billion objects by 2020.[4]

References

  1. Brown, Eric (13 September 2016). “Who Needs the Internet of Things?”. Linux.com. Retrieved 23 October 2016.
  2. Brown, Eric (20 September 2016). “21 Open Source Projects for IoT”. Linux.com. Retrieved 23 October 2016.
  3. “Internet of Things Global Standards Initiative”. ITU. Retrieved 26 June 2015.
  4. Nordrum, Amy (18 August 2016). “Popular Internet of Things Forecast of 50 Billion Devices by 2020 Is Outdated”. IEEE.

This section excerpted from Wikipedia (here), governed by CC-BY-SA.

The Industrial Internet

The Industrial Internet is a term coined by GE [1] and refers to the integration of complex physical machinery with networked sensors and software.

The industrial Internet draws together fields such as machine learning, big data, the Internet of things and machine-to-machine communication to ingest data from machines, analyze it (often in real-time), and use it to adjust operations.

Examples

The Google driverless car takes in environmental data from roof-mounted LIDAR, uses machine-vision techniques to identify road geometry and obstacles, and controls the car’s throttle, brakes and steering mechanism in real-time.[2]

The Union Pacific Railroad mounts infrared thermometers, microphones and ultrasound scanners alongside its tracks. These sensors scan every train as it passes and send readings to the railroad’s data centers, where pattern-matching software identifies equipment at risk of failure.[3][4] Falling prices for computing power and networked sensors mean that similar techniques can be applied to small, common devices like machine tools.[5]

References

  1. Leber, Jessica (2012-11-28). “General Electric’s San Ramon Software Center Takes Shape | MIT Technology Review”. Technologyreview.com. Retrieved 2013-08-18.
  2. Steve Lahor. “The Internet Gets Physical”The New York Times. Retrieved 2013-08-18.
  3. Chris Murphy (2012-08-08). “Union Pacific Delivers Internet Of Things Reality Check – Global Cio”. Informationweek.com. Retrieved 2013-08-18.
  4. Chris Murphy (2012-12-07). “Silicon Valley Needs To Get Out More – Global Cio – Executive”. Informationweek.com. Retrieved 2013-08-18.
  5. Jon Bruner (2012-10-29). “Listening for tired machinery – O’Reilly Radar”. Radar.oreilly.com. Retrieved 2013-08-18.

This section excerpted from Wikipedia (here; no longer available), governed by CC-BY-SA.

The Industrial Internet of Things

The term industrial Internet of things (IIoT) is often encountered in the manufacturing industries, referring to the industrial subset of the IoT. IIoT in manufacturing could generate so much business value that it will eventually lead to the fourth industrial revolution, so the so-called Industry 4.0. It is estimated that in the future, successful companies will be able to increase their revenue through Internet of things by creating new business models and improve productivity, exploit analytics for innovation, and transform workforce.[1] The potential of growth by implementing IIoT will generate $12 trillion of global GDP by 2030.[1]

References

  1. Daugherty, Paul; Negm, Walid; Banerjee, Prith; Alter, Allan. “Driving Unconventional Growth through the Industrial Internet of Things” (PDF). Accenture. Retrieved 17 March 2016.

This section excerpted from Wikipedia (here), governed by CC-BY-SA.

Industry 4.0

Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things, cloud computing[1][2][3][4] and cognitive computing.

Industry 4.0 creates what has been called a “smart factory”. Within the modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real time, and via the Internet of Services, both internal and cross-organizational services are offered and used by participants of the value chain.[1]

References

  1. Hermann, Pentek, Otto, 2016: Design Principles for Industrie 4.0 Scenarios, accessed on 4 May 2016
  2. Jürgen Jasperneite:Was hinter Begriffen wie Industrie 4.0 steckt in Computer & Automation, 19 December 2012 accessed on 23 December 2012
  3. Kagermann, H., W. Wahlster and J. Helbig, eds., 2013: Recommendations for implementing the strategic initiative Industrie 4.0: Final report of the Industrie 4.0 Working Group
  4. Heiner Lasi, Hans-Georg Kemper, Peter Fettke, Thomas Feld, Michael Hoffmann: Industry 4.0. In: Business & Information Systems Engineering 4 (6), pp. 239-242

This section excerpted from Wikipedia (here), governed by CC-BY-SA.

Big Data

Big data[1][2] is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.

The challenges include capture, curation, storage,[3] search, sharing, transfer, analysis,[4] and visualization. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to “spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions.”[5][6][7]

References

  1. White, Tom (10 May 2012). Hadoop: The Definitive Guide. O’Reilly Media. p. 3.
  2. “MIKE2.0, Big Data Definition”.
  3. Kusnetzky, Dan. “What is “Big Data?”. ZDNet.
  4. Vance, Ashley (22 April 2010). “Start-Up Goes After Big Data With Hadoop Helper”New York Times Blog.
  5. “Data, data everywhere”The Economist. 25 February 2010. Retrieved 9 December 2012.
  6. “E-Discovery Special Report: The Rising Tide of Nonlinear Review”. Hudson Global. Retrieved 1 July 2012. by Cat Casey and Alejandra Perez.
  7. “What Technology-Assisted Electronic Discovery Teaches Us About The Role Of Humans In Technology — Re-Humanizing ”. Forbes. Retrieved 1 July 2012.

This section excerpted from Wikipedia (here), governed by CC-BY-SA.

Machine Learning

Machine learning, a branch of artificial intelligence, concerns the construction and study of systems that can learn from data.

For example, a machine learning system could be trained on email messages to learn to distinguish between spam and non-spam messages. After learning, it can then be used to classify new email messages into spam and non-spam folders.

This section excerpted from Wikipedia (here), governed by CC-BY-SA.

Machine to Machine (m2m) Communication

Machine to machine (M2M) refers to technologies that allow both wireless and wired systems to communicate with other devices of the same type.[1][2]

M2M can include the case of industrial instrumentation – comprising a device (such as a sensor or meter) to capture an event (such as temperature, inventory level, etc.) that is relayed through a network (wireless, wired or hybrid) to an application (software program) that translates the captured event into meaningful information (for example, items need to be restocked). [3]

References

  1. “Machine-to-Machine (M2M) Communication Challenges Established (U)SIM Card Technology” – GD
  2. “Machine to Machine (M2M) Technology in Demand Responsive Commercial Buildings”
  3. “M2M: The Internet of 50 Billion Devices”WinWin Magazine, January 2010.

This section excerpted from Wikipedia (here), governed by CC-BY-SA.

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