IoT (Internet of Things) for University Faculties

Purpose:

Unlike other technologies, IoT is far more complex encompassing almost every branch of core Engineering-Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics and Mobile. For each of its engineering layers, there are aspects of economics, standards, regulations and evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering.

For Faculty members, it is of paramount interest that they should have an overall background of evolving IoT standards. To apply for grants in IoT areas, faculties must be exposed to new research directions where they can fit their existing skills. They also need to be aware of overall idea of funding areas in IoT. This course will address those evolving areas where they can attract more research and industrial grants in IoT.

Summary:

  • An advanced training program covering the current state of the art in Internet of Things.
  • Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help faculties to write more project proposals in IoT domain.
  • Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation and use cases around connected devices & things.
  • Introduction to latest areas of IoT which needs more research both from structural and engineering point of view
  • Target Audience:

  • Faculty members and research engineers who are applying for Govt grants in IoT areas- such as smart city, smart manufacturing, 5G-IoT.

  • Duration:    2 Days ( 8 hours / day)-Total 16 hours.

    Prerequisites:

  • Basic knowledge devices, electronics systems and data systems
  • Basic understanding of software and systems
  • Basic understanding of Statistics (in Excel levels)
  • Understanding of Telecommunication Verticals

  • Overview:

    Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 12 B by 2019 and 100B+ by 2025.

    In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.

    However the underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.

    Industrial IoT, or IIoT for manufacturing has been widely in use since 2014 and since then a large number of IIoT innovations have taken place. This course will introduce all the important aspects of innovations in Industrial IoT area.

    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 also promising to transform the business of IoT. This has led to an unprecedented large swath of new areas of research funding in IoT.

    Course Objective:

    Main objective of this course is to introduce emerging technological options, platforms and case studies of IoT implementation in emerging verticals ( smart cities, smart manufacturing, agriculture, public safety etc) and horizontals ( edge computing, PaaS platforms, 5G-IoT etc.) for the University researchers..

    1. 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 Total control plane

    2. M2M Wireless protocols for IoT- WiFi, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one?

    3. Edge Platforms for IoT

    4. Known PaaS clouds for IoT- Azure, Google and AWS

    5. Security issues and security solutions for IoT

    6. Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT cloud in addition to other minor IoT clouds

    7. Emerging research areas in IoT edge computation, 5G-IoT and many other horizontals.

    Course Outline:

    Session 1: Basic and Advanced concepts
  • Basic -1: A brief history of evolution of IoT technologies
  • Basic-2: Wearable, Edge computing, IoT wireless protocols ( Sigfox, Lora etc.) , IoT cloud platforms.
  • Basic-3 : layered architecture of IoT — Physical (Sensors), Communication, and Data Intelligence
  • Advanced-1 : Edge architecture, edge computation and database
  • Advanced-2 : Next Generation IoT Gateways- edge and 5G
  • Advanced-3: managed IoT services like diagnostics, maintenance of IoT infrastructure by bots and automation
  • Session 2:Sensing and Devices: Architectures and Examples
  • 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 the 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, etc.
  • Business driver for sensor deployment — FDA/EPA regulation, fraud/tempering detection, supervision, quality control and process management
  • Different Kind of Calibration Techniques — manual, automation, infield, primary and secondary calibration — and their implication in IoT
  • Powering options for sensors — battery, solar, Witricity, Mobile and PoE
  • Hands on training with single silicon and other sensors like temperature, pressure, vibration, magnetic field, power factor etc.
  • Session 3:Well Known Communication Protocols for IoT Engineering
  • Basic function and architecture
  • What is a sensor network? What is ad-hoc network?
  • Wireless vs. Wireline network
  • WiFi- 802.11 families: N to S — application of standards and common vendors.
  • Zigbee and Zwave — advantage of low power mesh networking. Long distance Zigbee. Introduction to different Zigbee chips.
  • Bluetooth/BLE: Low power vs high power, speed of detection, class of BLE. Introduction of Bluetooth vendors & their review.
  • Creating network with Wireless protocols such as Pionet by BLE
  • Protocol stacks and packet struture for BLE and Zigbee
  • Other long distance RF communication link
  • LOS vs NLOS links
  • Capacity and throughput calculation
  • Application issues in wireless protocols — power consumption, relability, PER, QoS, LOS
  • Sensor networks for WAN deployment using LPWAN. Compariso of various emerging protocols such as LoRaWAN, NB-IoT etc.
  • Hands on training with sensor network
  • Device control using BLE
    Session 4:Review of Standard and Advanced topologies in IoT
  • Reviewing all the basic elements of an IoT system- sensors, automation, gateway, edge gateway, data visualization, data analytics, cloud computation
  • Review of a standard gateway architecture- North and South bound system, critical process, IPC vs IPC internal communication protocols, Batch vs no-batch computation
  • Edge computation and edge database- more detailed architectural lay-outs
  • Gateway to cloud communication – MQTT, Web-socket etc.
  • Real Time vs Near Real time vs Historical visualization
  • Over the top (OTA) architectures for remote update of firmware and software
  • Managing a distributed system and network from event logs more effectively
  • Batch size vs process duty cycle- how to match them
  • Session 5:Data-Mining and Analytic Engine for IoT
  • Insight analytic
  • Visualization analytic
  • Structured predictive analytic
  • Unstructured predictive analytic
  • Recommendation Engine
  • Pattern detection
  • Rule/Scenario discovery — failure, fraud, optimization
  • Root cause discovery
  • Introduction to Machine learning
  • Learning classification techniques
  • Bayesian Prediction-preparing training file
  • Support Vector Machine
  • Image and video analytic for IoT
  • Fraud and alert analytic through IoT
  • Bio –metric ID integration with IoT
  • Geo-fencing in IoT analytics
  • Real Time Analytic/Stream Analytic
  • Scalability issues of IoT and machine learning
  • What are the architectural implementation of Machine learning for IoT
  • Session 6:Cloud computing and platforms for IoT
  • IaaS vs PaaS
  • SaaS models
  • Hybrid IoT clouds
  • On-premise cloud for IoT
  • IoT event hub ( Microsoft)
  • AWS IoT Platform ( with demo and architecture)
  • Microsoft IoT platform (with demo and architecture)
  • Basic concepts of Cloud apps for in
  • Basic concepts of different layers of security in IoT
  • Detailed study of Azure IoT platform architrecture
  • Session 7:Hands-on building a IoT cloud system
  • Build a IoT system using Microsoft Azure IoT central – example will be to build a 3 phase-voltage current sensor in Azure IoT central system
  • Learn the basic concepts of IoT Web app- Fleet manager, data visualization, sensor onboarding, sensor mapping, sensor-system attribute mapping , digital twins - learn it via Azure IoT central and Machinesense Crystal Ball
  • Computation /Machine learning of Data in Edge vs Cloud
  • Concept of IoT Template for replicated IoT system design
  • IoT system and connectivity diagnosis
  • Session 8:Emerging Research Areas and Case Studies for Federal grants in IoT
  • Smart City : Structural health monitoring, Bridge health monitoring, Transportation Monitoring, Air and Water pollution monitoring, Smart Parking etc.
  • Sustainable development goals ( SDG)- defining IoT Scopes in SDG1-16 as defined by UN
  • IoT and Public Safety – Fire hazard, flash floods prevention
  • IoT and 5G
  • IoT in smart agriculture
  • IoT in Oil/Gas
  • IoT and water management
  • IoT and Power management – energy and power quality


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