Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM50584
Volume:
9 |
6 |
Jun 2025
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.
The main objective of the Project is Abstract Wild Animal Detection and Alert System: A Technological Solution for Human-Wildlife Conflict Mitigation. The escalating issue of human-wildlife conflict necessitates innovative and effective solutions to protect both human and animal populations. In response, the Wild Animal Detection and Alert System emerges as a pioneering technological endeavor, integrating advanced sensors, high-resolution cameras, and sophisticated machine learning algorithms to detect and identify wild animals in real-time. This comprehensive system is designed to provide timely alerts to relevant stakeholders, including authorities, farmers, and conservationists, thereby enabling proactive measures  to prevent conflicts and safeguard human and animal well-being. By leveraging cutting-edge technology, this system has the potential to significantly contribute to wildlife conservation, human safety, and the mitigation of economic losses resulting from human-wildlife conflict. As a groundbreaking solution, the Wild Animal Detection and Alert System represents a substantial advancement in the field of wildlife management and conservation, offering a promising avenue for addressing the complex challenges associated with human-wildlife conflict. A wild animal detection and alert system is a technology-based solution designed to detect and alert authorities or individuals when wild animals are present in a particular area, such as near human settlements, agricultural fields, or protected areas. The system typically uses a combination of sensors, cameras, and machine learning algorithms to detect and identify wild animals.
KEYWORDS
Publication Date
6/18/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
0
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...