Non-invasive Tagging for Smart IoT-based Wildlife Management System: A Comprehensive Review

Abstract

The integration of Internet of Things (IoT) technology with non-invasive tagging systems has revolutionized wildlife management and conservation efforts. This review examines the current state of non-invasive tagging technologies for smart IoT-based wildlife management systems, highlighting their applications, advantages, and challenges. Traditional wildlife monitoring methods often involve invasive procedures that can stress animals and alter their natural behaviors. Non-invasive tagging approaches, including RFID tags, GPS collars, acoustic sensors, and camera traps, combined with IoT infrastructure, provide real-time monitoring capabilities while minimizing human intervention and animal disturbance. This paper analyzes various non-invasive tagging technologies, their integration with IoT platforms, data collection and processing methodologies, and their effectiveness in wildlife conservation. The review also discusses challenges such as battery life, data transmission range, environmental durability, and cost-effectiveness. Recent advancements in sensor miniaturization, energy harvesting, and machine learning algorithms have significantly enhanced the capabilities of these systems. The findings suggest that IoT-based non-invasive wildlife monitoring systems offer promising solutions for large-scale conservation efforts, enabling researchers to gather comprehensive data on animal behavior, migration patterns, and habitat utilization while maintaining ethical standards in wildlife research.