Decades ago, we connected computers and got today’s powerful Internet. Now we have started to connect everyday objects using internet, to create the Internet of Things. World will have 50 bilion connected devices by 2020. As these IoT devices come online, the industry will face some formidable challenges, such as ensuring the security of its devices, powering billions of sensors and analyzing the data generated by these devices. Therefore it is important to understand underlying components and the entire eco- system and integration issues , various use cases or applications of IoT and its data analytics. The objectives of this course is to learn about Basics of IoT, Components of IoT including Sensors and actuators, computing and communication systems. It will also cover IoT Protocols, Security of IoT, Cloud based design and AI/Deep learning based analytics. Intended Audience: Post-Graduate Students, and final year undergraduate students Prerequisites: Basic courses on communication, computer networks and signal processing
Unit I – Basics of IoTIntroduction to Internet of things, Various sensors and sensing techniques. Technological trends in IoT. impact of IoT on society. Review of various IoT application domain including agriculture, healthcare, manufacturing, device management, and vehicle to vehicle communication and wearable computing devices.
Unit II – Microcontroller and Interfacing Techniques for IoT DevicesIntroduction to IoT and architecture layers, IoT smart devices, Typical embedded computing systems, Introduction to ARM architecture and programming method, Embedded system development: a case study, Introduction to interfacing techniques.
Unit III – IoT Protocols & SecurityNetworking and basic networking hardware. Networking protocols, Interaction between software and hardware in an IoT device. IoT components and technologies to secure systems and devices.Various security issues related to the IoT and security architectures. Hardware security threats and security vulnerabilities; protecting physical hardware Week 4:
Unit IV – Location TrackingIntroduction to device localization and tracking; different types of localization techniques: time-of-arrival (TOA) based, time-difference-of-arrival (TDOA) based, angle-of-arrival (AOA) based, received signal strength (RSS) based, Radio-Frequency IDentification (RFID) based and fingerprinting based; Monte-Carlo tracking; Kalman filter based tracking; Cramer-Rao lower bound (CRLB) for device location estimator; Device diversity/heterogeneity issue in IoT networks.
Unit V – Deep learning for IoTThis topic will focus how to build good model from the past data so as to predict correctly when the system is provided with a data-point. In this course mostly, supervised learning will be considered. Basics of neural network, activation functions, back-propagation, etc. will be covered. At the end some of the challenges in the context of IoT will be mentioned. Week 6:
Unit VI - IoT Applications:Smart grid: Introduction to smart grid, Integration of IoT into smart grid, Standardization activities for IoT aided smart grid, Applications of IoT aided smart grid, Architectures for IoT sided smart grid, Prototypes, Applications of big data and cloud computing, Open Issues and challenges. Week 7:
Unit VI - IoT Applications:IoT-based Smart Home and Nano-grid Monitoring SystemSensor-Controller Coordination of a DC Microgrid in IoT Platform, Cyber physical system, dc microgrid, dc–dc power converter, distributed energy generator, sensor control and controller design. Low Cost DC Nano-grid with Smart Remote Monitoring Unit, DC-DC converter modeling, closed loop control, placement of IoT devices, sensors, micro grid, solar energy, low cost communication system design.Introduction, objective, components of home monitoring system, control and management, Zigbee, Wireless Sensor Network (WSN), Internet of Things (IoT). Week 8:
Unit VI - IoT Applications:Internet of Robotic Things (IoRT): Introduction to stationary and mobile robots; Brief introduction to localization, mapping, planning, and control of robotic systems; Introduction to cloud-enabled robotics; Applications of IoT in robotics; Architectures for IoRT; Examples and case studies; Open issues and challenges.