First Technology Transfer

Standard and Advanced Technical Training, Consultancy and Mentoring

IIoT (Industrial Internet of Things) a Comprehensive Exploration and Analysis of the Technologies and Applications

For Entrepreneurs, Investors and Technical Managers

Duration: 3 Days

Synopsis

This course uses a strategic and systems based approach to describe the various components that make up the IIoT and how they can fit together, and the various current and future developments in this area. . Examples of real world IIoT systems will be used to illustrate what has been accomplished and what may be accomplished. Additionally the course will cover the various standards and regulations which need to be taken into account when planning to develop applications or individual IoT components. The course will also discuss Industry 4 the new standard for IIoT as well as OPC UA and the role it plays in IIoT.

This course is suitable for a fairly wide technically literate audience spanning technical managers, strategic decision makers, entrepreneurs and investors. A key objective of this course, beyond providing a sound introduction to the various technologies involved is to explore some of the emerging trends and applications in the IoT "Ecosystem".

Course Outline

  • Overview of IIoT , its economic significance and areas where it is being applied
    • The Smart factory of the 2020s
    • Automation and optimisation of logistics systems
    • Industrial Manufacturing Process optimisation
    • Predicting faults and scheduling maintenance downtimes
    • Industrial manufacturing and logistics
    • Next generation CIM (Computer Integrated Manufacturing)
    • Agriculture
    • Defence and Security
    • Energy and production cost minimisation in Manufacturing Plants
  • Sensors, Microcontrollers and Networks
    • Microprocessors, Microcontrollers and SoC (System on a Chip) devices
    • Analog and Digital sensors
    • SoC devices with integrated radio
    • SoC devices with integrated ethernet
    • Overview of sensor technologies for measuring temperature, pressure, gas concentrations, humidity, mechanical stresses and strains.
    • RFID, PIR, LIDAR sensors
    • Sensor communication protocols HART, RS485, Modbus, I2C, SPI, CAN bus, Bluetooth, BLE and LORA.
    • Business drivers for sensor deployment such as quality control and process management, detection of tampering, FDA and EPA regulations.
    • Sensor accuracy and calibration
  • Wireless Sensor Networks and M2M Communication
    • Overview of sensor networks and ad-hoc networks
    • Wireless vs. Wired networks
    • WiFi- 802.11 families
      • Zigbee and Zwave and low power mesh networking.
      • Bluetooth/BLE
    • Wireless protocols and the kinds of networks that they can give rise to
    • Long distance RF communication links
    • Design, Planning and Modeling of large scale deployments
    • Capacity and throughput calculation
    • Power consumption, reliability, PER, QoS, and LOS issues
    • Wide AreaSensor networks using Low Power WAN (LPWAN), LoRaWAN, for WAN deployment using LPWAN, Narrow Ban Iot (NB-IoT)
  • Designing, Prototyping and Manufacturing IIoT Devices
    • Essential concepts and terminology - PCB, FPGA, ASIC, Microcontroller vs. Microprocessor, 8 bit, 16 bit and 32 bit systems
    • Prototyping vs Production electronics
    • QA and IoT - CE/CSA/UL/IEC/RoHS/IP65
    • Manufacturing and testing
    • Overview of multi-layer PCB design and associated workflows
    • FIT (Failure in Time) and measurment of failure rates
    • Environmental and reliability testing
    • Prototyping using cheap open source platforms - e.g. Arduino, Raspberry Pi, Beaglebone Black
  • IIoT and IIoT Application - Project and Product Lifecycle Considerations
    • Study phase - Review state of the art at present and use of existing technology in the market place
    • Invention phase - proposing new features and technologies based on market analysis and patent issues
    • Detailing phase - Developing the technical specs for the new products at the hardware, firmware, application software, mechanical, installation, deployment levels.
    • Analysis and Implementation of Packaging and documentation requirements
    • Analysis and Implementation of Servicing and customer support requirements
    • High level design (HLD) - developing and better understanding the design concepts
    • Release plan for phase wise introduction of the new features
    • Identifying skill sets for the development team.
    • Developing a project plan and estimating project cost and duration
    • Estimating a target manufacturing price
  • Hardware and Protocol Elements used in IIoT for manufacturing
    • State of the present art and review of existing technology in the market place
    • PLC (Programmable Logic Controller) – architectures and standards
    • PLCs as sources of data
    • Integration of PLC data with Cloud based applications
    • OPC, UA and SCADA
    • PLC protocols ( Modbus, Fieldbus, Profibus) and "joining them up" with the Cloud
    • Industrial Gateways - concepts and emerging standards
  • Mobile app Platforms and their Role in IIoT
    • Protocol stacks used in Mobile apps for IoT - BLE and WiFi
    • Integrating Mobile apps into IIoT systems
    • BLE (Bluetooth Low Energy) in IIoT
    • Web Interfaces that can be used in implementing Mobile IIoT Apps ( REST/WebSockets)
    • IIoT Application layer protocols (MQTT/CoAP) on Mobile platforms
    • Security aspects IIoT middleware- Keys, Token and random password generation for authentication of the gateway devices.
  • Data Processing, Machine Learning and IIoT
    • Structuring and Organising IoT Data
    • Data analysis and visualisation - an overview
    • Linking IIoT Data with Models and Simulations
    • Machine learning concepts and strategies
    • Overview of Machine Learning, Neural Networks, Genetic Algorithms and Probabilistic Graph Modeling (Bayesian Prediction)
    • High Performance Computing architectures for Machine Learning - Intel, NVidia
    • Applications of Machine Learning in IoT
    • Image and video analytics and IoT
    • Fraud and alert analytics and IoT
    • Biometric ID integration and IoT
    • GIS (Geographic Information Systems) and IoT
    • Real Time Analytics/Stream Analytics and Intelligence at the Edg
    • Scalability issues of IoT and machine learning
  • Security Aspects of IIoT
    • The need for IIoT security
    • IoT Security Breach attack scenarios
    • Fundamentals of network security
    • Encryption and cryptography in IIoT systems
    • European legislation for security in IoT platforms
    • Secure booting
    • Device authentication
    • Firewalling and IPS
    • Secure application of updates and patches
  • Databases and IIoT and Cloud based IIoT platforms
    • Overview of SQL and NoSQL
    • Open source vs. Licensed Database
    • Cassandra and analysis of Time Series Dat
    • Mongo-DB
    • CISCO M2M platform
    • Google M2M platform
  • IIoT system applications - Case Studies and Examples
    • Energy Optimization of Manufacturing Processes
    • Vibration analysis tracking of machinery and using it for predictive maintenance scheduling
    • Power Quality analysis and its application to Preventative maintenance
    • Recommending policies and schedules in logistic supply chain applications
    • IIoT system applications in the area of Industrial Safety
    • IIoT system asset identification using NFC (Near Field Communication) and RFID technologies
    • IIoT systems for monitoring Utilities in Manufacturing plants ( Chillers, Aircompressors, HVAC equipment)
  • Big Data and IIoT
    • Characteristics of Big Data the 4Vs - Volume, velocity, variety and veracity
    • Overview of Big Data handling and processing technologies
    • Hadoop and Cassandra
    • Approaches for storing large amounts of image, Geospatial and video data
    • Distributed databases and database replication
    • Overview of HPC (High Performance Computing) in IoT big data processing
    • Micro services Architectures and Big Dat