Agriculture-based Automation with Recommendation Systems based on AI Models

Abstract

Agriculture automation is the main concern and an emerging subject across the globe. The populations are increasing, and the demand for agricultural products is increasing rapidly. However, in real time, 35% of the agricultural products are wasted due to several reasons. The traditional method is not sufficient to manage the demands. Increasing the fertilisers for a high yield and using harmful pesticides will affect the soil. Therefore, this paper comes with an application created based on different techniques like artificial intelligence, machine learning, and deep learning. There are certain areas that affect agriculture, like crop disease, water resources, crop monitoring, lack of storage space, and warehouse storage space. This application can solve this problem by utilising the aforementioned technologies. Pesticides have altered the majority of agricultural soils for the worse. New technologies will be beneficial to agriculture in terms of increasing soil productivity and fertility. This paper has surveyed many researchers to get a brief overview of the new technologies in current agriculture. It also discussed a proposed system that implemented ML, DL, and AI for disease classification, crop monitoring, crop and fertiliser recommendation, and warehouse spaces.