Nex-G Innovations

The industrial internet of things (IIoT) is the use of smart sensors and actuators to enhance manufacturing and industrial processes. Also known as the industrial internet or Industry 4.0, IIoT leverages the power of smart machines and real-time analytics to take advantage of the data that dumb machines have produced in industrial settings for years. The driving philosophy behind IIoT is that smart machines are not only better than humans at capturing and analyzing data in real time, they are better at communicating important information that can be used to drive business decisions faster and more accurately.

Code: NES_SK_22489

Duration: 80 Hrs / 8 Weeks / Customized

Mode: Online / Offline / Onsite

+91-8826900551

• Concept and definitions
• Embedded Systems, Computer Networks, M2M (Machine to Machine Communication), Internet of Everything (IoE), Machine Learning, Distributed Computing, Artificial Intelligence, Industrial automation
• Interoperability, Identification, localization, Communication, Software Defined Assets
• Understanding IT and OT convergence: Evolution of IIoT
• OT Components: Industrial control system, PLC, SCADA, DCS
• IT Components: Hardware, Software, People ,Processes
• IIoT Adoption
• Market statistics, Early adopters, Roadmap
• Business opportunities: Product + Service model
• Development, deployment and monetization of applications as service

Module 2 - Industrial Internet Of Things - Use Cases

• Smart factory applications and smart warehousing.
• Predictive and remote maintenance.
• Freight, goods and transportation monitoring.
• Connected logistics.
• Smart metering and smart grid.
• Smart environment solutions.
• Smart city applications.
• Smart farming and livestock monitoring.
• Industrial security systems
• Energy consumption optimization
• Industrial heating, ventilation, and air conditioning
• Manufacturing equipment monitoring.
• Asset tracking and smart logistics.
• Ozone, gas and temperature monitoring in industrial environments.
• Safety and health (conditions) monitoring of workers.
• Asset performance management
• Remote service, field service, remote maintenance and control use cases.

Module 3 - Industrial Automation: PLC and SCADA

• History and evolution of automation: Plants to Parts
• Concept of Data, Information, Knowledge and Wisdom
• Knowledge discovery process
• DIKW pyramid and relevance with IoT
• PLC vs Microcontrollers: cost, performance, and power consumption
• Commercial microcontroller based development boards
• Selection criteria and tradeoffs
• Industrial networks, M2M networks

Module 4 - Design And Development of IIoT systems

• IIoT reference architectures
• Standardization initiatives
• Interoperability issues
• Industrial Internet Reference Architecture from Industrial Internet Consortium(IIC)
• IIoT design considerations
• Architectures Device, Network and Cloud
• Centralized vs distributed architectures
• Networks, communication technologies and protocols

Module 5 - Steps To Optimize Industrial Internet Of Things Projects

• Build partnerships
• Clarify business outcomes and ROI
• Start small
• Security first
• Architect for analytics

Module 6 - Industry 4.0: Smart Factory & Cyber-physical systems (CPS)

• Function blocks and interfaces
• Top-down control and design

Module 7 - The Industrial Internet Of Things And Connectivity

• Multiple communication mechanisms (WiFi, 5G, Zigbee, Bluetooth3.0, 6lopan, Nb-IOT)

Module 8 - Cloud Computing

• Industrial Gateways
• Commercial Gateways solutions from Intel, Cisco
• Cloud based Gateway solutions
• IaaS, SaaS, PaaS models
• Cloud components and services
• Device Management, Databases, Visulization, Reporting, Notification/Alarm management, Security management, Cloud resource monitoring and management
• Example platforms: AWS IoT, Microsoft Azure
• Overview: GE Predix and PTC Thingworx
• AWS IoT Services
• Device Registry
• Authentication And Authorization
• Device Gateway
• Rules Engine
• Device Shadow

Module 9 - Sensor Data Mining And Analytics

• Transducer: Sensor and Actuator
• Sensors – Types of sensors, sampling, analog to digital conversion, selection criteria of sensor and ADC
• Data acquisition, storage and analytics
• Real time analytics
• Understanding fundamental nuances between IoT and Big data
• Usage of IoT data in various business domains to gain operational efficiency
• Edge analytics
• Data Aggregation on Edge gateway

Module 10 - Industrial IOT Security

• Standards and Best practices
• Common vulnerabilities
• Attack surfaces
• Hardware and Software solutions
• Open source initiatives
• Device (Application and OS hardening)
• Network and protocol security features
• Cloud security