International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI and IoT-Based Real-Time Wild Animal Detection and Automated Alert System for Enhancing Safety in Forest Border and Agricultural Regions |
|---|---|
| ABSTRACT | The dangers that animals now face have dramatically escalated over time. L live-animal marketplaces, animal-human disputes, animal-vehicle collisions, and other unintentional deaths as a result of inadequate animal monitoring are some of the serious risks to animals. An automated animal monitoring system that uses both animal detection and categorization methods is a dependable response to all of these dangers. In the paper, we propose a number of animal classification and detection algorithms that are targeted at various image modalities for a number of applications related to animal conservation. Initially, the "Convolutional Neural Network" (CNN), a method for classifying animal breeds, is shown. Then, we demonstrate various animal detection methods using various visual modalities. An autonomous ground vehicle-based livestock monitoring system called "EfficientNetB4" is suggested for the third image modality—fusion images. Using "EfficientNetB4", the system combines visual and thermal pictures. The proposed solutions handle a number of camera trap issues as well as difficult animal traits to ensure robustness. |
| AUTHOR | SOLOMON MATHEW S, RONALDO JUDE J, DHASARATHAN M, RAJA MONSING R Department of Artificial Intelligence and Data Science, Christ The King Engineering College Karamadai, Karamadai, Coimbatore, Tamil Nadu, India. Assistant Professor, Department of Artificial Intelligence and Data Science, Christ The King Engineering College Karamadai, Karamadai, Coimbatore, Tamil Nadu, India. |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405019 |
| pdf/19_AI and IoT-Based Real-Time Wild Animal Detection and Automated Alert System for Enhancing Safety in Forest Border and Agricultural Regions.pdf | |
| KEYWORDS | |
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