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 manufacturing professional, most critical aspect is to understand the advancement in the area of Industrial Internet of things, which includes predictive and preventative maintenance, condition based monitoring of the machines, production optimization, energy optimization, supply-chain optimization and uptime of manufacturing utilities etc.
- An advanced training program covering the current state of the art in Internet of Things in Smart Factories.
- Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help manufacturing managerial professionals
- Live demo of model IIoT applications for smart factories
- Managers responsible for business and operational processes within their respective manufacturing organizations and want to know how to harness IoT to make their systems and processes more efficient.
Duration 3 Days ( 8 hours / day)
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: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.
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.
This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business.
Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in smart factories for manufacturing sectors.
- Studies of business and technology of some of the common IIoT platform like Siemens MindSphere and Azure IoT.
- Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT, Mindsphere IIoT cloud in addition to other minor IoT clouds
- Open source/commercial electronics platform for IoT-Raspberry Pi, Arduino , ArmMbedLPC etc
- Security issues and security solutions for IIoT
- Mobile/Desktop/Web app- for registration, data acquisition and control –
- M2M Wireless protocols for IoT- WiFi, LoPan, BLE, Ethernet, Ethercat, PLC : When and where to use which one?
- 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
Session 1: Business Overview of Why IoT is So Important
- Case Studies from Nest, CISCO and top industries
- IoT rate in North American & how they are aligning their future business model and operation around IoT
- Broad Scale Application Area
- Smart Factory of 2020
- Industrial Internet
- Predictive and Preventative Maintenance of a Machine
- Tracking the utilization and productivity of the machine
- Energy and cost optimization of manufacturing plants
- Business Rule Generation for IoT
- 3 layered architecture of Big Data - Physical (Sensors), Communication, and Data Intelligence
Session 2: Introduction to IoT : All About Sensors
- 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.
Demo : Logging data from a temperature sensor
Session 3: Fundamentals of M2M Communication : Sensor Network and Wireless Protocols
- 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 Piconet by BLE
- Protocol stacks and packet structure 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, reliability, PER, QoS, LOS
- Sensor networks for WAN deployment using LPWAN. Comparison of various emerging protocols such as LoRaWAN, NB-IoT etc.
- Hands on training with sensor network
Demo : Device control using BLE
Session 4: Review of Electronics Platform, Production and Cost Projections
- PCB vs FPGA vs ASIC design-how to take decision
- Prototyping electronics vs Production electronics
- QA certificate for IoT- CE/CSA/UL/IEC/RoHS/IP65: What are those and when needed?
- Basic introduction of multi-layer PCB design and its workflow
- Electronics reliability-basic concept of FIT and early mortality rate
- Environmental and reliability testing-basic concepts
- Basic Open source platforms: Arduino, Raspberry Pi, Beaglebone, when needed?
Session 5: Hardware/Protocol Elements of IIOT for manufacturing
- State of the present art and review of existing technology in the market place
- PLC – architecture
- Cloud integration of PLC data
- Visualization of PLC data
- Digital Twin
- PLC protocols ( Modbus, Field bus, Profibus) and its integration with Cloud
- Concept of Industrial Gatway
Session 6: Introduction to Mobile App Platform for IoT
- Protocol stack of Mobile app for IoT
- Mobile to server integration –what are the factors to look out
- What are the intelligent layer that can be introduced at Mobile app level ?
- iBeacon in IoS
- Window Azure
- Amazon AWS-IoT
- Web Interfaces for Mobile Apps ( REST/WebSockets)
- IoT Application layer protocols (MQTT/CoAP)
- Security for IoT middleware- Keys, Token and random password generation for authentication of the gateway devices.
Demo : Mobile app for tracking IoT enabled trash cans
Session 7: Machine Learning for Intelligent IIoT
- Introduction to Machine learning
- Learning classification techniques
- Bayesian Prediction-preparing training file
- Support Vector Machine
- Predicting failure of the machines -vibrational analysis
- Current signature analysis
- Time series data and prediction
Demo : Using KNN Algorithm for regression analysis
Demo : SVM based classification for image and video analysis
Session 8: Analytic Engine for IIoT
- Insight analytic
- Visualization analytic
- Structured predictive analytic
- Unstructured predictive analytic
- Recommendation Engine
- Pattern detection
- Root cause discovery for electrical failures in factory
- Root cause of machine failure
- Logistic supply chain analysis for manufacturing
Session 9: Security in IoT Implementation
- Why security is absolutely essential for IoT
- Mechanism of security breach in IOT layer
- Privacy enhancing technologies
- Fundamental of network security
- Encryption and cryptography implementation for IoT data
- Security standard for available platform
- European legislation for security in IoT platform
- Secure booting
- Device authentication
- Firewalling and IPS
- Updates and patches
Session 10: Database Implementation for IoT Cloud
- SQL vs NoSQL-Which one is good for your IoT application
- Open sourced vs. Licensed Database
- Available M2M cloud platform
- Cassandra -Time Series Data
- Siemens MindSphere
- GE Predix
- IBM BlueMix
- AWS IoT
Session 11: A few Common IIoT Systems for manufacturing
- Energy Optimization in Manufacturing
- Vibration analysis to build predictive maintenance
- Power Quality analysis to build Preventative maintenance
- Recommendation system for logistic supply chain
- IIoT system for Industrial Safety
- IIoT system asset identification
- IIoT system for Utilities in Manufacturing plants ( Chiller, Aircompressor, HVAC)
Demo : Retail, Transportation & Logistics Use case for IoT
Session 12: Big Data for IoT
- 4V- Volume, velocity, variety and veracity of Big Data
- Why Big Data is important in IoT
- Big Data vs legacy data in IoT
- Hadoop for IoT-when and why?
- Storage technique for image, Geospatial and video data
- Distributed database- Cassandra as example
- Parallel computing basics for IoT
- Micro services Architecture
Demo : Apache Spark