IoT and Embedded Systems for Energy-Efficient and Sustainable Computing

Abstract: The rapid proliferation of IoT and embedded systems across critical sectors agriculture, energy, and transportation demands a shift toward sustainable computing. These systems must operate with minimal energy overhead while delivering accurate, timely data and control. This paper explores energy-efficient design principles, including low-power sensor architectures, lightweight communication protocols such as Zigbee, BLE, LoRaWAN, and NB-IoT, as well as battery-aware management strategies and edge-level intelligence. Applications in smart farming, grid optimization, and intelligent mobility are examined to demonstrate how embedded platforms enable environmentally responsible computation. The study identifies major gaps in existing designs, such as inconsistent protocol integration and underutilized renewable energy harvesting methods. A battery-aware, event-driven, and modular design approach is proposed, and validated using a case implementation. The results affirm that IoT systems, when thoughtfully designed, can significantly reduce carbon footprint while maintaining performance. Future directions include AI-assisted scheduling and cross-layer protocol optimization.

Keywords: IoT Embedded Systems, Energy Harvesting, Smart Grid, Green Mobility, Sustainable Computing