Review on Various Techniques for Wildlife Monitoring and Alerting Systems

Monitoring wildlife is crucial for understanding animal movement patterns, habitat utilization, population demographics, human-wildlife conflicts, incidents of vehicle-animal collisions, occurrences of snares and poaching, as well as outbreaks of epidemics. In recent times, the frequency of accidents involving wildlife and vehicles has risen, particularly on rural roads and highways in hilly terrain. The identification and classification of animals through image and video sequences represent a widely studied field. This paper provides a comprehensive overview of recent advancements in wildlife monitoring technologies and alerting systems. The review encompasses a wide spectrum of methodologies, including Internet of Things (IOT), camera traps etc. The paper begins by exploring the fundamental objectives of wildlife monitoring. It then delves into the evolution of monitoring technologies, highlighting the shift from traditional methods to state-of-the-art, automated systems such as deep neural networks, different versions of YOLO and the Internet of Things (IOT), which have transformed data processing and decision-making in wildlife monitoring. A critical aspect of wildlife monitoring is the development of efficient alerting systems that enable rapid response to threats. Overall this survey identifies gaps in existing knowledge, outlines future research directions, and advocates for the adoption of integrated, technology-driven solutions to address the problem.