Smart and Connected, Internet of Things(IoT), and Industrial IoT.

The progression from Mechanization (Industry 1.0) to Electrification (Industry 2.0) to Computation (Industry 3.0) and to Connectivity (Industry 4.0, IoT, and IIoT) is evident today. Information technology has not only enhanced efficiency at the individual level, both for humans or machines but, has brought effectiveness to a new level through connectivity. Human is connected with Human and machines on a real-time basis and so do the machines with human and peer machines.

Thing-to-thing or machine-to-machine connectivity i.e. Internet of Things OR Industrial Internet of Things (IoT and IIoT) has shown a future path wherein the life of humans (is)/will be surrounded with smart machines/gadgets and a huge amount of data and information communication happening all around the world.

This is evident today in terms of Home Automation and industrial automation occurring around the globe. COVID-19 has triggered it both at the planning level and at the implementation level. You may soon witness huge investments from governments and corporations towards IoT and IIoT applications.

In the above context, you may find it useful to review the following conceptual knowledge on IoT and IIoT.

Basic Concepts of IoT and IIoT

  • Lean: Refers to Better Quality (continuous improvement), Less Time (Integrated operations), Less cost (More profit through better value add), and less wastage (all types of wastage of FOP)
  • Smart & Connected: Smartness means awareness (in real-time/near real-time) of the current state (or historical states) and the capability to make informed decisions. A machine is smart if it can sense the current situation, is able to communicate it with a network, and ultimately receive the instructions and act upon them. Connected refers to passing the ongoing state information (with other machines, smart devices, and humans) of all/certain machines with a central location for analysis and decision-making. Connectivity is also vital to increase the efficiency and effectiveness of the whole system through the integration and manage machines’ inter-dependencies…
  • Monitoring (awareness of current status using sensors), Control (Actions to bring back on track through actuators), Optimisation (determining the best-operating conditions and maintaining it dynamically using specialized algorithms), Automation (use of IT in monitoring, controlling, and optimization processes)
  • Embedded systems: Computational systems + Communication systems + Control systems; meant to perform certain predefined functions only.
  • Cyber-Physical systems: Integrated network of embedded systems. A more comprehensive system to provide a solution. Includes Sensing, communicating, analyzing, decision-making, and actuating/action.
  • CPS Architecture: 5Cs: Connection, configuration & communication (Sensing; Physical connection, configuration to establish communication including device register, device identity & access management settings; data integration through interoperability), Conversion & Collection [converting/transforming data into information (adding context like time series, GPS location, date, etc..), data filtering and interpretation, ADC to DAC and vice versa, data collection], Cyber (gateways, filtering, Transmission, security, transformation & storage, rules, knowledge & Applications), Cognition (Intelligence, Judgements, reporting, training…), Control, Configuration & Command (Autonomy/Actionable/Actuation/ feedback i.e. who does what)
  • Intelligent System(presence of RAM, ROM, Microcontroller, Flash))= Smart system (sensors + Embedded system)
  • Productivity in collaboration: Coordination (Functional alignment), Single source of truth (goal alignment or Integration of various functions), IT Advancements/Innovations/Proliferation (Computational capacity and capability), Industrialization (Strategy/planning/conceptualization/framework).
  • Artificial Intelligence = Knowledge-base + Heuristic search (relationships along with certain Thumb rules for decision making/option selection)


  • Facts and evidence are data
  • The data with time and context becomes information
  • Rules/regulations/codes are knowledge {procedural, operational, declarative, relational or heuristic (thumb rule)}
  • Judgment/Decision making is the intelligence

Industrial Internet of Things (IIOT): IOT in Industrial Applications

 IIOT= Traditional automation + Networked decision making {i.e. sensors + actuators + Analytics + scalability + Connectivity}

Benefits of IoT and IIOT

Efficiency improvement: Less cost, less time, fewer wastages, optimization’

Asset Optimisation to Facility optimization to Fleet optimization to network optimization

Effectiveness: Innovation, Human resources can do higher-order tasks and can make informed decisions, flexibility & agility, change management

IoT and IIOT Challenges: Non-standardization (proprietary technologies and processes), Integration (volume, variety, and velocity), Security (data privacy, information, and system security), Legacy systems (Vulnerable due to old technology), skill deficiency

IOT and IIoT Sensing

  • Gas Sensing Methods
  • Electrical methods: assessment and calibration of DeltaV, Delta i, and Delta R.
  • Non-electrical methods: Optic, Acoustic, Chromatographic, calorimetric

IoT and IIOT Analytics

Knowledge is the rules, regulations, heuristics, limits, tolerances, best practices, design parameters, operational guidelines, etc. which are known/decided/targeted in advance as favorable/functional parameters (lagging indicators or Delta/proportions of lagging indicators to quantify the impact of leading indicators), which needs to be met/adhere to in order the process to be under control and outcome is as planned (as per process).

The data is raw values collected by sensors, these values when added with context becomes information, and when the sequences/bulk of the information is processed to identify useful patterns to obtain process insights and current status provides intelligence (apparent values of Lagging indicators or change of lagging indicators as an impact of leading indicators). On comparing these insights with the knowledge the process status can be determined and desired action can be taken in order to improve the process performance; such continued improvement cycles help in process optimization and increase in throughput i.e. more output with the same inputs…)

Type of IoT and IIOT Analytics

  • Descriptive Analytics: Analysis of historical data to determine current performance.
  • Predictive Analytics: Analysis of historical data to project future performance.
  • Prescriptive Analytics: Projecting future performance & indicative failures along with measures/actions to manage the performance.

Other Important Concepts

Machine Learning: Identification of vital parameters (Lagging/leading indicators) in advance and analyzing historical streams of their values to create relational heuristics (Statistical methods like regression & correlations and other machine learning modeling techniques) depicting machine performance is Machine learning.

Deep learning: Deep learning includes setting/obtaining even the vital parameters from the data streams itself by the computing device and then creating certain correlations depicting the machine performance and being able to extrapolate to predict futuristic performance also.

Augmented Reality (AR): Amplification of the present perception of reality (physical environment). Augmented reality facilitates a mixed reality environment, wherein, the person is able to see reality (through natural senses) along with computer-generated visualizations enabling a better perception of reality (allowing the person to go beyond the natural senses’ perceived reality).

Virtual Reality (VR): The person is not present in the target environment physically; rather he is surrounded by the virtual environment (target environment) to have an experience of virtual reality from his natural senses and cognition. The virtual environment is a result of projections of graphics of reality.

Software-Defined Network (SDN): SDN configuration is based on OpenFlow Protocol (versions 1.1-1.5). SDN separates the data layer (routers etc) from the control layer(controller). SDN helps in efficient and effective network management:

Efficiency: Load balancing, removing bottlenecks at routers due to low computing capability (now allowing them to do only the task they are efficient to do rest decision making and directing is done by the controller).

Effectiveness: Handle dynamism in the network which is not possible in hardware/routers as they have preconfigured and hard-winded/predefined/preconfigured process rules within the hardware.

Security Requirements of IIOT: Vulnerabilities of IT+ Vulnerabilities of OT+ Vulnerabilities due to the unique integration of IT &OT

IoT/IIOT network has its own individual technologies, devices, network, Protocols, etc.. and it also uses the existing traditional IT/internet infrastructure which has its own standardized technologies and protocols, with the inclusion of IIOT, heterogeneity has been increased to a large extent and these networks are now getting exposed to threats due to the convergence of IIOT network into the existing internet network.

IoT/IIOT devices/machines, data collecting & transfer technologies & channels, edge devices, aggregating devices, and computing devices including the cloud are providing the gateways to security threats and add vulnerabilities to the overall system. So the security issue has to be managed at all the layers viz. the data layer, control layer, and application layer.

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