IoT for Power Utility: Fundamentals, Frontiers and Strategy
Dr Biplab Pal, CEO and Co-Founder Machinesense

Overview of the Course:

Connected device is disrupting many business, power utility being no exception. Power Utility companies are essentially faced with four challenges from growth of IoT

1. Machines, Controllers, HMI, SCADA systems are increasingly becoming cloud connected by the vendors who promise to offer more analytics and insight via their data for predictive and preventative maintenance. But quarantine policy of the critical assets means these new IoT features from the Machine/Controller Vendors can’t be utilized by the Power Companies .

2. With the ever decreasing cost of solar and wind power microgrid, Utility companies will soon see declining revenue from power generation. To compensate for the lost revenue of power production, the company has to aggressively pursue new areas of revenues such as Energy management of Home as a service, Energy storage as a service, offering grid service for EV charging, grid service for P2P energy trading between the homes, home and microgrid, microgrid to microgrid, microgrid to battery, home to battery etc. All of this need to be facilitated via smart metering, smart grid and smart & secured transactions only possible via DLT ( distributed ledger technology) like IOTA. Also Utilities are exploring to offer some of the smart city services to the city authority.

3. For critical infrastructure like dams, ICOLD ( International Committee Of Large Dams) want to see Structural Health Monitoring (SHM) of the dams real time so that any impending danger of collapse of the dam or rock or tunnel can be informed in advance to vacate the people who may be affected .

4. Also a new emerging area of revenue will be EV charging in Parking-How IoT can facilitate smart charging and smart parking?

Over the last three years, engineering in IoT has seen massive changes primarily driven by Microsoft, Google and Amazon. These large behemoths have invested billions of dollars to develop IoT platforms that are more easy to manage and secure. Also IoT edge has gained a lot of momentum in both research and deployment as only means for practical IoT implementation. 5G is promising to transform the business of IoT. This has led to an unprecedented large swath of new areas of research funding in IoT. This is why right now for any practicing engineer it is absolutely essential to understand IoT platforms developed for major players like AWS, Google and Specially Microsoft.

However, neither of the above platform offers exhaustive or a totally comprehensive solution for a scalable IoT. Just for Smart Metering to be deployed to millions of homes, additional technology to secure the smart meter, radio networks, IoT management technology and many other additional secured services will be required. Strategy, Price and Security of any IoT deployment must be optimal and acceptable. Given so much of interdisciplinary knowledge, it is almost difficult for any company to deploy a team which can meet all the requirements.

This course is a modest attempt to educate the key decision makers, developers, security experts about what are the challenges, risks and practical way to deploy IoT for their next generation power utility business.

In addition, with scalable deployment, managing IoT services for thousands of sensors and connections are emerging as a separate engineering subject of research. This area , formally known as managed IoT services is experiencing rapid growth as challenges for scalable IoT are much bigger than building them. This includes security of over the top firmware/software update, managing calibration of the sensors and systems, auto-diagnosis of any connection issue, narrowing down on root cause of API failures, tracking the hardware and service health of the distributed system etc.

Course objectives:

Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in Power Utility Companies - Smart Metering, Smart Car, SHM ( structural health monitoring), Power Quality Diagnosis and Smart Contracts. Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and control plane applications.

1. Technology Stacks: Devices, Gateways, Edge, Edge Cloud, Public Cloud, IoT databases, Web & Mobile Applications for IoT, Centralized vs Decentralized IoT.

2. IoT ecosystem for Business, third party device management, risk management of entire IoT ecosystem.

3. M2M Wireless protocols for IoT- WiFi, SigFox,LORA, LPWAN, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one.

4. Fundamentals of IoT Gateways- Risks, Management and Ecosystem

5. Mobile/Desktop/Web app - for registration, data acquisition and control –Available M2M data acquisition platform for IoT—AWS IoT, Azure IoT, Google IoT.

6. Security issues and solutions for IoT- Review of security of all the technology stacks.

7. Enterprise IoT platforms such as Microsoft Azure IoT suites, AWS IoT, Google IoT , Siemens MindSphere

8. Smart Metering, Open Smart Grid Protocols (OSGP), ANSI C 2.18 Protocols , NIST Standard for HAN ( Home Area Network), Home Plug Powerline Alliance , Security Standard for Smart Meter- IEC 62056

9. Distributed Ledge Technology ( DLT) such as Blockchain, HyperLedger and DAG ( Direct Acyclic Graph) for smart contract, P2P transactions, smart car charging

10. IoT for critical infrastructure like DAM, Transformer, Sub-station, High Tension Wire

Target Audience:

1. Decision makers/strategist/Policy makers.

2. Engineering Leaders, Lead developers, Security Experts.


1. Should have basic knowledge of business operation, devices, electronics systems and data systems.

2. Must have basic understanding of software and systems .

3. Basic understanding of Statistics ( in Excel levels)

Duration:   Breakdown of the Module ( Each module 2 hours, customers can ask for any number of modules): Total 22 hours, 3 days.

Session 1:Introduction, Basics and Case Studies from Power Utility Companies
  • Fundamentals of all technology stacks in IIoT
  • IoT adaptation rate in Power Utility Market & how they are aligning their future business model and operation around IoT
  • Broad Scale Application AreaEdge database- MongoDB for edge, HarperDB Smart Meter, Smart Car, Smart Grid- brief definition, adoption and challenges Business Rule generation for IoT
  • 3 layered architecture of Big Data –Physical (Sensors), Communication and Data IntelligenceOther Edge management layers like Calibration of Sensors
  • Evolving standards and platform players like Azure, AWS and Google-brief introductions. What they offer and what they don’t.
  • Session 2:Sensors, Hardware & Sensor Networks
  • Basic function and architecture of a sensor –Sensor body, sensor mechanism, sensor calibration, sensor maintenance, cost and pricing structure, legacy and modern sensor network- All basics about the sensors
  • Development of sensor electronics- IoT vs legacy and open source vs traditional PCB design style
  • Development of Sensor communication protocols –history to modern days. Legacy protocols like Modbus, relay, HART to modern day Zigbee, Zwave, X10,Bluetooth, ANT, 6LoPAN, WiFi-x, NB-IoT, SignalFx, LORA Powering options for sensors-Battery, solar, Mobile and PoE
  • Energy harvesting solutions for wearables
  • SoC( Sensors on Chips) and MEMS based sensors
  • Sampling rate matching with application – why it matters in business?
  • What is a sensor network? What is Ad-hoc network ?
  • Wireless vs. Wireline network
  • Autopairing and reconnection
  • Which applications to use
  • and where
  • Mathematical exercise to find out which network to pick up and where
  • Session 3:Key Security and Risk Concerns in IoT
  • Firmware Patching risk- the soft belly of IoT
  • Detailed review of security of IoT communication protocols- Transport layers ( NB-IoT, 4G, 5G, LORA, Zigbee etc. ) and Application Layers – MQTT, Web Socket etc.
  • Vulnerability of API end points -list of all possible API in IoT architecture
  • Vulnerability of Gate way devices and Services
  • Vulnerability of connected sensors -Gateway communication
  • Vulnerability of Gateway- Server communication
  • Vulnerability of Cloud Database services in IoT
  • Vulnerability of Application Layers
  • Vulnerability of Gateway management service- Local and Cloud based
  • Risk of log management in edge and non-edge architecture
  • Session 4:Machine learning, AI , Analytics for intelligent IoT
  • What is return of investment on Intelligent IoT?
  • In Utility- Power Quality, Energy management, Other analytic as service (AAS)
  • Introduction to Analytic Stacks in IoT- Feature extraction, Signal Processing, Machine learning
  • Introduction to digital signal processing
  • Fundamentals of analytics stacks in IoT applications
  • Learning classification techniques
  • Bayesian Prediction-preparing training file
  • Support Vector Machine
  • Image and video analytic for IoT
  • Fraud and alert analytic through IoT
  • Real Time Analytic/Stream Analytic
  • Scalability issues of IoT and machine learning
  • FOG computing
  • Edge architecture
  • Session 5:Smart Metering- Standards, Security and Future
  • Smart Metering
  • Open Smart Grid Protocols (OSGP)
  • ANSI C 2.18 Protocols
  • NIST Standard for HAN ( Home Area Network)
  • Home Plug Powerline Alliance
  • Security Standard for Smart Meter- IEC 62056
  • Security vulnerability of smart metering- case studies
  • Session 6:Cloud Platform for IoT / Iaas/Paas/Saas for IoT
  • Iaas : Infrastructure as a service-evolving models
  • Mechanism of security breach in IOT layer for Iaas
  • Middleware for Iaas business implementation in healthcare, homeautomation and farming
  • Iaas case study for vehicular information for Auto-insurance and Agriculture
  • Paas: Platform as a service in IoT. Case studies of some of the IoT middleware
  • Saas : Software/System as service for IoT business models
  • Updates and patches via web-OTA mechanism
  • Google IoT, AWS IoT PaaS platform
  • Session 7:Future of Smart Grid and Smart Metering
  • EV charging as a service
  • EV as a Mobile battery and charger wallet
  • Large Battery storage – Hydro Battery, Lithium Battery and other initiative
  • Charging and storage as service
  • Grid as a service for P2P energy trading
  • Use of distributed ledger technology in P2P energy trading- Blockchain, HyperLedger and DAG
  • IOTA/TIANGLE in P2P charging
  • IOTA/TANGLE in smart energy and smart contract
  • Session 8:A few common IoT systems for Utility monetization
  • Hoem Automation
  • Smart Parking
  • Energy optimization
  • Automotive-OBD /Iaas/Paas for Insurance and Car parking
  • Mobile parking ticketing system
  • Indoor location tracking
  • Smart lighting for smart city
  • Smart Waste Disposal system
  • Smart pollution control in city
  • Session 9:Mobile IoT Modem, 4G, 5G, NB-IOT
  • 4G IoT standards for IoT : LTE-M applications, NB-IoT, UNB standard for 3GPP, 4G , LTE CAT-1 IoT
  • 5G IoT standard for IoT : LPWA, eMTC , IMT 2020 5G
  • Detailed architecture of IoT Mobile Modem
  • Security Vulnerability of 4G/5G and Radio Networks
  • IoT gateways -architecture, classification and security issues
  • Session 10:Managed IoT Service : IoT management layers
  • Sensor onboarding
  • Sensor mapping
  • Digital Twin
  • Asset management
  • Managing third party device and gateways
  • Managing sensor connectivity, gateway connectivity
  • Managing device and gateway health
  • Managing sensor calibration and QC
  • Managing OTA/Patching on bulk scale
  • Managing Firmware, Middleware and analytic builds in distributed system
  • Security and risk management
  • API management
  • Log management
  • Session 11: Managing Critical Assets
  • Review of existing Fiber Optical Network, SCADA, PLC for Power Plants, Sub-station and critical transformers.
  • SHM (Structural Health Monitoring) of DAM system -ICOLD standard for Dam monitoring
  • Upgrading from SCADA to local cloud based system ( not public cloud)
  • SCADA/PLC to intelligent local cloud for more efficient management of Critical Assets
  • Strategy for new policy for adopting smart devices