Internet of Things and Industrial Analytics

The Industrial Internet of Things (IIoT) is a wave of innovation impacting the way the world connects and optimizes machines. IIoT, through use of sensors, advanced analytics and intelligent decisioning, is profoundly transforming the way field assets connect and communicate with the enterprise. Forrester Research reports that the market for Big Data was approximately $31 Billion in 2018 1. Part of this growth is due to the fact that the IIoT data is Big Data, made up of billions of events and data points, to support some of the fastest-growing areas in global business analytics, BI and predictive analytics.

More demanding than either consumer IoT or traditional machines-to-machines are Industrial IoT applications because they emphasis more on communications where the application uses autonomous, peer-to-peer distributed control. Data communications or transfers are frequent, but typically do not convey large amounts of data. Besides performing their main task, these systems also connect to an enterprise system to issue alarms, archive historical data, and store a basis of performing analytics on the data. This connection can work via a local IP connection or can be hosted in the cloud.

Systems performing these demanding industrial applications have been available for some time. However, they have often depended on hard wiring and purpose-built communications protocols for exchanging data and status between nodes. Advances in low power wireless, power line, and high-speed multi-drop twisted-pair communications technologies, coupled with more compact implementations of IP, are enabling a migration to IP-based nodes for even the smallest and most cost-sensitive nodes within these systems. As with the broader IoT market, it is important for the IIoT to have services in an IP-based protocol stack, that allows IP protocol stack to be used across the entire IIoT application space, so that application developers can depend on a common set of communications services as they implement IIoT applications. Because the stakes are high when industry is involved, the IIoT space has a very specific set of performance and reliability requirements that must be satisfied, including resilience in the face of failures, security, physical connectivity requirements, control services, etc.

Variety of use cases fall under IIoT analytics including:

1) Measurement, Verification and Constant Commissioning: Ensure that devices in the field operate as intended

2) Capacity Planning: Monitor data for risk of unplanned device or system downtime

3) Root-Cause Analysis and Remote Troubleshooting: Better understand the cause of a particular failure on a particular device and improve efficiency

4) Anomaly and Outlier Detection: Identify outliers that may be an early indicator of issues in device production or deployment

5) Safety and Compliance: Gain visibility into system performance or set points that could put machines or people at risk; quickly develop and access reports for compliance purposes

6) Cyber-Security: Improve security posture across industrial systems to mitigate emerging cyber security threats, etc.

The economic and scientific implication of IIoT and the digital economy is creating much discussion and speculation. The conceptual framework of both are vast and encompass many cutting-edge technologies like big data, predictive analytics, quantum computing, cloud, mobility. To win in the digital economy and IIoT, companies must recognize that the time to act is now. Business and technology leaders must be willing to explore and innovate new approaches and learn by experimentation.

Some IIoT real-world examples:

1) Medical Informatics enable Connected Hospitals: Due to introduction of connected devices in hospitals, informatics is becoming key for healthcare IT. A hospital chain with over 150 hospitals is using IIoT analytics to monitor and gain insight from data generated by over 4,000 mobile devices that collect various patient vital signs.

2) Telematics Data enhances Transportation Safety and Fuel Efficiency: New York Air Brake (NYAB), a leading provider of rail technology is using IIoT analytics to gather operational insights from the big data produced by train management systems.

3) Check on the Baby: Aimed at helping to prevent SIDS, the Mimo monitor is a type of infant monitor that provides parents with real-time information about their baby’s breathing, skin temperature, body position, and activity level on their smartphones.

4) Get the most out of your Medication: The Proteus ingestible pill sensor is powered by contact with your stomach fluid and communicates a signal that determines the timing of when you took your meds and the identity of the pill. This information is transferred to a patch worn on the skin to be logged for you and your doctor’s reference. Heart rate, body position and activity can also be detected.

1 Forrester, Midyear Global Tech Market Outlook for 2017 to 2018, Sept. 25, 2017.

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