IoT Explained: Smart Systems, Connected Devices & Intelligent Technologies

Abstract

IoT Explained: Smart Systems, Connected Devices & Intelligent Technologies is a publication-grade Open Educational Resource (OER) module covering the microarchitectural, wireless network, edge computing, and cybersecurity principles governing distributed smart environments. Serving as an integral core module within the Electrical and Electronic Engineering curriculum on Prep4Uni.Online, this text bridges physical wireless transceivers (LoRaWAN, Zigbee, NB-IoT, 5G) and cloud analytics with contemporary AI-era edge inference, digital twins, and cyber-physical security. Key Features & Pedagogical Additions:• Theoretical Grounding & Contemporary Paradigms: Integrates classical distributed networking (RF propagation path loss, CSMA/CA MAC backoff, duty-cycle regulations) with Physics-Informed Neural Networks (PINNs) solving 1D fluid dynamics for municipal leak detection, Fourier Neural Operators (FNOs) for municipal flood and thermal digital twins, and Lie-group SE(3) Invariant Extended Kalman Filters (IEKF) for multi-agent swarm localization.• Systems Engineering Architecture & Trade-Off Analysis: Structured comparison matrix contrasting LoRaWAN LPWAN against Zigbee mesh, cellular NB-IoT/LTE-M, and private industrial 5G URLLC.• Worked Numerical Engineering Application: A complete, multi-step engineering calculation detailing an 8.5 km LoRaWAN telemetry link budget, free-space path loss (FSPL), packet airtime duration, duty-cycle compliance, and battery lifespan projection factoring in usable capacity derating and annual self-discharge.• Curricular Assessment & Analytical Inquiries: Contains 25 fully resolved foundational review questions, deep analytical design inquiries, and step-by-step numerical problems spanning LoRaWAN airtime limits, battery operational lifetime derivations, MQTT network bandwidth savings, edge vs. cloud latency profiling, Wi-Fi free-space path loss calculations, supercapacitor solar charging duration, and multi-hop mesh network transmission latency.