Energy-Oriented Wireless Communication Platform Selection System in the Internet of Things

Abstract

The Internet of Things (IoT) has become a fundamental paradigm in modern communication systems, enabling the large-scale interconnection of sensors, actuators, and embedded computing platforms. This paper presents a decision-oriented framework for the selection of energy-sensitive wireless communication platforms in IoT systems. The proposed approach combines systematic measurement, structured feature engineering, and lightweight regression models to predict energy consumption and current demand for different hardware platforms and wireless technologies, including ESP32- and NORA-based devices utilizing Wi-Fi, Bluetooth Low Energy (BLE) and LoRa communication. The results confirm that simple and interpretable regression models can provide robust guidance for platform and technology selection in realistic real-world scenarios, without incurring the complexity associated with detailed physical-layer or protocol-level simulations.