Smart Sustainable Agriculture Using Machine Learning and AI: A Review

Artificial intelligence and machine learning are all about using data for efficient inferences and predicting the future and decisions. These decisions are made human-like, by machines; machine learning and big data are having a greater impact on the way we live. Scholars and scientists are looking at machine learning as a pioneer opportunity to create a positive impact in our day-to-day life, especially in the field of agriculture domains. The research reviews and project popular machine learning models used in the field of agriculture such as (a) crop management (crop yielding, fruit picking weed, and diseases detection), (b) soil management, (c) water management; the paper aims to introduce different types of machine learning methods and algorithms used in machine learning, and how machine learning reaches the agriculture, by implementing the machine learning into farmers by a remote sensor. The farmers will get benefited in decision-making such as risk reduction, quality seed selection, and easy monitoring with software. At the same time, the present study also focuses on the way artificial intelligence and IoT, if introduced in the agricultural sector, can boost the productivity of the sector sustainably.