Modeling Energy Losses in a Wireless Sensor Network for Monitoring Environmental Parameters in a Livestock Building

This article presents a study related to the determination of the energy losses in the nodes of a wireless sensor network during its operation. The sensor network is designed to collect real-time data on some environmental parameters in a livestock building. Measurements of the charge level of the batteries powering the network nodes were carried out and models describing the process of battery discharge over time were obtained. It was found that the most suitable for describing the process of battery discharge over time is the linear model, with the coefficient of determination R2 in this case varying between 0.96 and 0.99.

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Published
2025-08-27
DOI
https://doi.org/10.3390/engproc2025104049
Primary Topic
IoT-based Smart Home Systems
Type
article
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article

Modeling Energy Losses in a Wireless Sensor Network for Monitoring Environmental Parameters in a Livestock Building

Tsvetelina Georgieva, Plamen Daskalov, Belma Gaazi, Stanislav Penchev et al.
IoT-based Smart Home Systems
article

Modeling Energy Losses in a Wireless Sensor Network for Monitoring Environmental Parameters in a Livestock Building

Tsvetelina Georgieva, Plamen Daskalov, Belma Gaazi, Stanislav Penchev, Eleonora Nedelcheva
article en

Abstract

This article presents a study related to the determination of the energy losses in the nodes of a wireless sensor network during its operation. The sensor network is designed to collect real-time data on some environmental parameters in a livestock building. Measurements of the charge level of the batteries powering the network nodes were carried out and models describing the process of battery discharge over time were obtained. It was found that the most suitable for describing the process of battery discharge over time is the linear model, with the coefficient of determination R2 in this case varying between 0.96 and 0.99.

Angel Kanchev University of Ruse (BG)
Affordable and clean energy
Openalex Percentile: Top 78%
IoT-based Smart Home Systems
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