Integrating IoT sensors and machine learning for sustainable precision agroecology: enhancing crop resilience and resource efficiency through data-driven strategies, challenges, and future prospects

The integration of Internet of Things (IoT) sensors and Machine Learning (ML) technologies has transformed precision agriculture by enabling data-driven, adaptive, and efficient farming practices. IoT sensors provide continuous, high-resolution monitoring of critical agricultural parameters, including soil health, crop growth, and environmental conditions. Coupled with advanced ML algorithms, this data facilitates predictive analytics and real-time decision-making, optimizing resource utilization for irrigation, pest control, and yield prediction. Recent innovations, such as edge computing, Reinforcement Learning (RL), and Transfer Learning, have further enhanced the scalability and adaptability of IoT-ML…