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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM31933
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This paper proposes an innovative approach to address the pressing challenges of forest monitoring and fire detection by leveraging the synergistic capabilities of Internet of Things (IOT) devices and drones. By integrating these cutting-edge technologies, our approach aims to revolutionize traditional forest management practices by facilitating real-time data collection, analysis, and decision-making. Through the strategic deployment of IOT sensors across forested areas, we can gather comprehensive environmental data, including temperature, humidity, air quality, and vegetation health. This extensive dataset, combined with the aerial surveillance capabilities of drones equipped with thermal imaging cameras, enables early detection and rapid response to potential fire incidents .Moreover, the proposed approach holds significant potential for enhancing collaboration and coordination among stakeholders involved in forest management, including government agencies, environmental organizations, and local communities. By providing access to timely and accurate information, it fosters greater transparency, accountability, and stakeholder engagement in decision-making processes related to forest conservation and sustainability. In conclusion, our innovative approach to forest monitoring and fire detection represents a paradigm shift in ecosystem management, offering a powerful toolkit for preserving biodiversity, mitigating climate change, and promoting sustainable forestry practices. Through continued research, development, and implementation, we can harness the full potential of IOT and drone technology to safeguard our forests for future generations.
KEYWORDS
Publication Date
12/31/45408
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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