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Energy-Oriented Wireless Communication Platform Selection System in the Internet of Things
Konrad Gac1, Jakub Gorski1, Grzegorz Gora1
1AGH University of Krakow, Faculty of Mechanical Engineering and Robotics, Department of Robotics and Mechatronics, Al. Mickiewicza 30, 30-059 Krakow, Poland.
Sensors (Basel, Switzerland)
|May 27, 2026
Summary
This study offers a framework to select energy-efficient wireless platforms for the Internet of Things (IoT). Simple regression models accurately predict energy use, aiding hardware and technology choices for IoT systems.
Area of Science:
- Computer Science
- Electrical Engineering
- Embedded Systems
Background:
- The Internet of Things (IoT) enables large-scale interconnection of devices.
- Selecting energy-efficient wireless communication platforms is crucial for IoT sustainability.
- Existing methods may lack practicality for real-world IoT deployments.
Purpose of the Study:
- To present a decision-oriented framework for selecting energy-sensitive wireless communication platforms in IoT.
- To enable informed choices between hardware and wireless technologies based on energy consumption.
- To provide a practical tool for optimizing IoT system design.
Main Methods:
- Systematic measurement of energy consumption and current demand.
- Structured feature engineering for hardware and wireless parameters.
- Development and application of lightweight regression models for prediction.
Main Results:
- Accurate prediction of energy consumption for ESP32 and NORA devices.
- Evaluation of Wi-Fi, Bluetooth Low Energy (BLE), and LoRa communication technologies.
- Demonstration of model effectiveness in realistic scenarios.
Conclusions:
- Lightweight regression models offer robust guidance for IoT platform selection.
- The proposed framework simplifies the choice of energy-sensitive wireless technologies.
- Practical, interpretable models are effective without complex simulations.
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