<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this study, we explore innovative strategies for enhancing energy efficiency in Wireless Sensor Networks (WSNs), with a focus on the IQRF network. Our approach integrates dynamic sleep scheduling and data collection methods to optimize battery usage and extend the network’s operational lifespan. We introduce a battery life estimation model, taking into account various factors such as data collection frequency and network size. This model is instrumental in predicting battery longevity under different operational scenarios. Additionally, we develop a practical tool in the form of an API and an online calculator, aimed at assisting network designers in planning and maintaining energy-efficient WSNs. Our results, derived from a case study involving a CO2 sensor network, demonstrate the effectiveness of our methodologies in real-world applications. The study concludes that implementing dynamic data collection and sleep scheduling significantly enhances battery life, offering a valuable contribution to the sustainability and reliability of WSNs.</p>
</abstract>

In this study, we explore innovative strategies for enhancing energy efficiency in Wireless Sensor Networks (WSNs), with a focus on the IQRF network. Our approach integrates dynamic sleep scheduling and data collection methods to optimize battery usage and extend the network’s operational lifespan. We introduce a battery life estimation model, taking into account various factors such as data collection frequency and network size. This model is instrumental in predicting battery longevity under different operational scenarios. Additionally, we develop a practical tool in the form of an API and an online calculator, aimed at assisting network designers in planning and maintaining energy-efficient WSNs. Our results, derived from a case study involving a CO2 sensor network, demonstrate the effectiveness of our methodologies in real-world applications. The study concludes that implementing dynamic data collection and sleep scheduling significantly enhances battery life, offering a valuable contribution to the sustainability and reliability of WSNs.

Dynamic Data Enhancing Battery Efficiency Through Collection Scheduling in IQRF Wireless Sensor Networks

Acta Electrotechnica et Informatica

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this study, we explore innovative strategies for enhancing energy efficiency in Wireless Sensor Networks (WSNs), with a focus on the IQRF network. Our...

Dynamic Data Enhancing Battery Efficiency Through Collection Scheduling in IQRF Wireless Sensor Networks

Data publikacji: 28 lut 2024

Zakres stron: 3 - 9

Otrzymano: 13 sty 2024

Przyjęty: 11 lut 2024

DOI: https://doi.org/10.2478/aei-2023-0016

Słowa kluczowe
IQRF, FRC, flooding routing, wireless sensor network, dynamic deep sleep, dynamic data collecting schedule

© 2023 Gergely Sebestyen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Dynamic Data Enhancing Battery Efficiency Through Collection Scheduling in IQRF Wireless Sensor Networks

Data publikacji: 28 lut 2024

Zakres stron: 3 - 9

Otrzymano: 13 sty 2024

Przyjęty: 11 lut 2024

DOI: https://doi.org/10.2478/aei-2023-0016

Słowa kluczoweIQRF, FRC, flooding routing, wireless sensor network, dynamic deep sleep, dynamic data collecting schedule

© 2023 Gergely Sebestyen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
IQRF, FRC, flooding routing, wireless sensor network, dynamic deep sleep, dynamic data collecting schedule