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. 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.
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The Industrial Internet
The Industrial Internet is a term coined by GE  and refers to the integration of complex physical machinery with networked sensors and software.
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.
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. Falling prices for computing power and networked sensors mean that similar techniques can be applied to small, common devices like machine tools.
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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. The potential of growth by implementing IIoT will generate $12 trillion of global GDP by 2030.
- Daugherty, Paul; Negm, Walid; Banerjee, Prith; Alter, Allan. “Driving Unconventional Growth through the Industrial Internet of Things” (PDF). Accenture. Retrieved 17 March 2016.
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 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.
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- 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
- Heiner Lasi, Hans-Georg Kemper, Peter Fettke, Thomas Feld, Michael Hoffmann: Industry 4.0. In: Business & Information Systems Engineering 4 (6), pp. 239-242
Big data 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, search, sharing, transfer, analysis, 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.”
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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.
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.
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). 
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- “M2M: The Internet of 50 Billion Devices”, WinWin Magazine, January 2010.