IOT-BASED APPLICATIONS FOR INTELLIGENT SYSTEMS

• Knowledge and Understanding: On completion of the course, the student shall 1) Know the key technological components underpinning IoT, 2) Understand IoT Architectures and the application of IoT in various domains, 3) Know the difference among networking protocols in the context of resource-constrained IoT devices, and 4) Know how Big Data can be exploited in the context of Smart Spaces.
• Applying Knowledge and Understanding: On completion of the course, the student shall be able to analyze and select the appropriate technological solutions for Smart Spaces enabled by IoT and Big Data collection and analysis. 
• Making Judgements: Completing the course, the student will be able to judge the suitability, the capabilities, and the limitations of IoT based applications in the context of Smart Spaces. Further, the student will be able to identify issues, problems, or misleading results.
• Communication Skills: On completion of the course, the student will be able to illustrate the theoretical and technical properties which characterize IoT based Smart Environments. The student will be able to interact and collaborate with peers and experts in the realization of a project or research.
• Learning Skills: On completion of the course, the student will be able to autonomously extend the knowledge acquired during the study course by reading and understanding scientific and technical documentation.

Basic notions in computing, database and data analytics, basics on Knowledge discovery

Introduction to IoT Systems

• Definition of the Internet of Things (IoT): IoT examples; IoT devices; IoT devices vs. computers.
• Trends in the Adoption of the Internet of Things (IoT): Trends; Potentiality and pervasiveness.
• The Importance of the Internet of Things (IoT) in Society: Societal benefits of IoT; Risk, privacy and security.

IoT Components and Protocols

• Features and Constraints of Embedded Systems: What are embedded systems; Generic embedded systems structure; Main components overview; Specific components examples; Microcontrollers, Sensor and Actuators; Analog/Digital conversion
• Architectures for IoT data storage and processing: cloud/fog/edge computing.
• Hands-on with KNIME Data Analytics Platform

Trusteless Decentralized environments  for Machine-to-Machine transactions:

• Physical vs Digital assets: the double spending problem, Exchange of value in human history
• Math fundamentals of a blockchain: Hash Functions and Asymmetric Cryptography
• Proof-of-work in Bitcoin, Difficulty Adjustment, Mining, Blocks and Transactions
• Tools visualizing and exploring the blockchain, Bitcoin as a Platform: the Lightning Network
• Bitcoin and altcoins: the trilemma, Ethereum and Smart Contracts
• Blockchain and IoT, Proof-of-existence, NFT