Automating agricultural aspects is a mechanical process with or without human intervention in agriculture. Due to less space of domestic lands, it has become an important area of choosing the most suitable crops based on prevailing factors in the selected area. In Sri Lankan even though there are enough knowledge, techniques, and methods which are done manually available in agriculture, there is not any system in which the environmental factors are detected and suggests the user which crop type is best for farming. This paper is consisting of a theoretical and conceptual platform of Recommendation system through integrated models of collecting environmental factors using Arduino microcontrollers, Machine learning techniques such as Naïve Bayes (Multinomial) and Support Vector Machine (SVM), Unsupervised machine learning algorithm such as K-Means Clustering and also Natural Language Processing (Sentiment Analysis) concerned with the Artificial Intelligence to recommend a crop for the selected land with site-specific parameters with high accuracy and efficiency. It has been a major problem to identify what to grow, any man has adequate space in the owner’s land. Not only domestic lands but also for farming lands. Why it has become a problem is that environmental factors such as temperature, water levels, and soil conditions are uncertain as they change from time to time. Due to these problems, this solution of crop recommendation system predicts the user, what crop type would be the most suitable for the selected area by collecting the environmental factors for plant growth and processing them with the trained sub-models of the main of the system.

Agriculture Machine Learning Arduino Natural Language processing Farming