AI and Data Analytics for Precision Agriculture: Current Progress and Future Directions

Ahmad Jamal (Department of Poultry Science, FV&AS, Muhammad Nawaz Shareef University of Agriculture, Multan 25000, Pakistan)
Hassan Raza (Washington university of science and technology, USA)
Tsendayush Erdenetsogt (University of the Potomac, USA)
A Singh (University of North America (UoNA), USA)
Mazhar Farooq (Southern New Hampshire University)
Muhammad Mohsin Kabeer (Gannon University)
Muhammad Shahrukh Aslam (Concordia University, USA)

JATAED: Journal of Appropriate Technology for Agriculture, Environment, and Development
Vol. 2 No. 2 (2025): JATAED: Journal of Appropriate Technology for Agriculture, Environment, and Dev

The application of artificial intelligence (AI) and data analytics to support farming operations and ensure a higher complexity of farming practices is what underlies precision agriculture with the purpose of promoting sustainability, higher productivity, and optimization of farming practices. Through the combination of sensor, drone, and satellite data, along with the use of IoT devices, AI-driven systems enable real-time monitoring, prediction, and decision-making. Its current applications are crop monitoring, yield prediction, pest and disease detection, soil nutrient management and optimization of irrigation. Despite the challenges of high costs, data constraints, and technological hurdles, new trends such as edge AI, digital twins, autonomous machinery, and climate-smart solutions will enable widespread adoption. The present review indicates the recent advances, issues, and perspectives of AI-enabled precision agriculture.