Abstract: Wildlife observation is essential for biodiversity conservation and ecological research. However, traditional methods of wildlife monitoring often disrupt natural habitats and pose safety challenges to researchers. A wildlife observation robot offers a non-intrusive, efficient, and automated solution to address these limitations. Equipped with advanced sensors, cameras, and GPS modules, the robot can navigate diverse terrains and monitor animal behavior, environmental conditions, and habitat changes in real-time. Integration with AI-powered image and sound recognition systems allows for accurate species identification and behavioral analysis. This autonomous system reduces human intervention, minimizes habitat disturbance, and enhances data collection accuracy. Additionally, remote operation and data transmission capabilities enable researchers to monitor wildlife from a safe distance, making it an invaluable tool for conservation efforts and ecological studies.The conservation of wildlife and the study of ecosystems are critical for maintaining biodiversity and ensuring ecological balance. Effective monitoring of wildlife is essential for understanding species behavior, habitat dynamics, and the impacts of environmental changes. However, traditional observation methods, such as manual surveys, stationary cameras, and tracking devices, often face limitations including habitat disturbance, high operational costs, limited geographic coverage, and risks to researchers. These challenges highlight the need for innovative, automated solutions, leading to the conceptualization and development of wildlife observation robots.A wildlife observation robot is an autonomous or semi-autonomous system designed to monitor and study wildlife with minimal human intervention. Equipped with advanced sensors, cameras, GPS modules, and artificial intelligence, these robots can collect real-time data on animal behavior, environmental parameters, and habitat conditions. AI-driven capabilities enable accurate species identification, behavioral analysis, and anomaly detection, providing researchers with valuable insights while maintaining the integrity of natural ecosystems.Theoretical foundations for this innovation draw from fields such as robotics, machine learning, and environmental science. Robotics offers a means to traverse diverse and challenging terrains autonomously, while AI enhances the robot's ability to interpret visual and auditory data with high precision. The integration of IoT (Internet of Things) technology enables seamless data transmission and remote monitoring, ensuring continuous observation even in remote or inaccessible locations.By minimizing ecological disturbance and offering scalability, wildlife observation robots contribute to the global conservation agenda. They provide a sustainable, efficient, and ethical alternative to traditional methods, ensuring comprehensive data collection without compromising the well-being of wildlife. This project bridges the gap between technology and conservation science, fostering innovative approaches to preserving biodiversity and supporting ecological research for future generations.

| DOI: 10.17148/IARJSET.2024.111224