Application On Ad Hoc Using Wireless Sensor Networks — Project presentation

Project presentation. This project presents a Wireless Sensor Network (WSN)-based system for early forest fire detection and environmental monitoring. The system uses NI WSN sensor nodes to collect real-time environmental data, including air temperature, soil temperature, soil moisture, carbon monoxide (CO), and carbon dioxide (CO₂). LabVIEW is used for data acquisition and visualization, while Python performs fire detection using a rule-based algorithm. The collected data are transmitted via TCP, stored in Firebase Realtime Database, and automatic Email and SMS alerts are generated when fire conditions are detected. The system provides reliable real-time monitoring, reduces false alarms by combining multiple sensor readings, and is designed to be scalable for future AI and multi-hop network integration.

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Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-27
DOI
https://doi.org/10.5281/zenodo.21631020
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
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Application On Ad Hoc Using Wireless Sensor Networks — Project presentation

Ahmed Taha, Abdelrahman Eid, Ali Ibrahim, Abdelrahman Shaban et al.
Zenodo (CERN European Organization for Nuclear Research)
Fire Detection and Safety Systems
article

Application On Ad Hoc Using Wireless Sensor Networks — Project presentation

Ahmed Taha, Abdelrahman Eid, Ali Ibrahim, Abdelrahman Shaban, Omar Elsettawi
article en

Abstract

Project presentation. This project presents a Wireless Sensor Network (WSN)-based system for early forest fire detection and environmental monitoring. The system uses NI WSN sensor nodes to collect real-time environmental data, including air temperature, soil temperature, soil moisture, carbon monoxide (CO), and carbon dioxide (CO₂). LabVIEW is used for data acquisition and visualization, while Python performs fire detection using a rule-based algorithm. The collected data are transmitted via TCP, stored in Firebase Realtime Database, and automatic Email and SMS alerts are generated when fire conditions are detected. The system provides reliable real-time monitoring, reduces false alarms by combining multiple sensor readings, and is designed to be scalable for future AI and multi-hop network integration.

Zenodo (CERN European Organization for Nuclear Research)
Al-Azhar University (ID)
Openalex Percentile: Top 9%
Fire Detection and Safety Systems
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