VAPECA - Smart Agricultural and Analysis Monitoring System

Abstract

Agriculture dramatically contributes to the economy by creating a monetary future for developing nations. However, in Sri Lanka, the farmers have confined resources and encounter numerous challenges to enrich their crop productivity and prevail in the competitive business world. In the directive, the farmers' knowledge about export crops and weak decision- making needs to be exposed [1]. This study has built a mobile application with budget planning, determining plant conditions, weather forecasting, analyzing harvest quality, and a price prediction system to mitigate these hardships. This application would be utilized to manage three critical plants in Sri Lanka t for extraction and export. Those are Vanilla, Pepper, and Cardamom. The key technologies used for the system are deep learning and machine learning. The overall system obtained desirable outcomes with an accuracy rate higherthan 94%-97%. The ultimate intent of this study is to achieve the optimal growth of the agriculture sector by navigating the farmers to get maximum crop yield, quality, and effective decision-making through reliable market trends and to enhance the farmers' profit