Abstract

The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies has revolutionized biodiversity assessment practices in recent years. This comprehensive review explores the various applications of AI and IoT in biodiversity assessment, highlighting their contributions to data collection, analysis, and conservation efforts. The synergy between AI algorithms and IoT sensors enables real-time monitoring of species diversity, habitat health, and environmental changes, thereby enhancing our understanding of ecosystem dynamics and supporting effective conservation strategies. Key methodologies discussed include automated species identification, species distribution modeling, wildlife monitoring and tracking, ecological forecasting, environmental DNA (eDNA) analysis, and data integration and visualization. The review also addresses challenges such as data quality and standardization, ethical and privacy concerns, and the need for capacity building. Future directions emphasize advancements in sensor technology, AI algorithms, IoT networks, data integration, and public participation. This manuscript underscores the transformative potential of AI and IoT in advancing biodiversity science, promoting sustainable resource management, and safeguarding biodiversity for future generations. 

Keywords

biodiversity assessment, artificial intelligence (AI), internet of things (IoT), species monitoring, habitat health, conservation strategies, machine learning, real-time data, ecological research, environmental monitoring