Using Environmental Data for IoT Device Energy Harvesting Prediction

Mansour Alzahrani, Alex Weddell, Gary Wills

2022

Abstract

There has been significant innovation in the domain of Internet of Things (IoT) as nowadays wireless data transmission is playing an essential role in various organizations like agriculture, defence, transportation, etc. Batteries are the most common option to power wireless devices. However, using batteries to power IoT devices has drawbacks including the cost and disruption of frequent battery replacement, and environmental concerns about battery disposal. Solar energy harvesting is a promising solution for long-term operation applications. However, solar energy harvesting varies drastically over location and time. Due to fluctuating weather conditions and the environmental effects on PV surface condition, output could be reduced and become insufficient. Environmental conditions including temperature, wind, solar irradiance, humidity, tilt angle and the dust accumulated over time on the photovoltaic (PV) module surface affects the amount of energy harvested. To address this issue, a novel solution is required to autonomously predict the harvested energy and plan the IoT device tasks accordingly, to enhance its performance and lifetime. Using Machine Learning (ML) algorithms could make it possible to predict how much energy can be harvested using weather forecast data. This research is ongoing, and aims to apply ML algorithms on historical weather data including environmental factors to generate solar energy predictions for IoT device energy budget planning.

Paper Citation

in Harvard Style

Alzahrani M., Weddell A. and Wills G. (2022). Using Environmental Data for IoT Device Energy Harvesting Prediction. In Proceedings of the 7th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-564-7, pages 197-204. DOI: 10.5220/0011069700003194

in Bibtex Style

@conference{iotbds22,
author={Mansour Alzahrani and Alex Weddell and Gary Wills},
title={Using Environmental Data for IoT Device Energy Harvesting Prediction},
booktitle={Proceedings of the 7th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2022},
pages={197-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011069700003194},
isbn={978-989-758-564-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Using Environmental Data for IoT Device Energy Harvesting Prediction
SN - 978-989-758-564-7
AU - Alzahrani M.
AU - Weddell A.
AU - Wills G.
PY - 2022
SP - 197
EP - 204
DO - 10.5220/0011069700003194