Context based expert system for diagnosing tomato pests

Abstract

An expert system is a decision support system for a specific domain. It has been applied in different fields. In the agriculture domain in Egypt, we have developed many systems for different crops since the late 1990s. However, those systems need to be updated to match current advances in technologies. Traditional expert systems statically interact with end users, there is a need to make it smarter to be adaptable based on user context. We utilize a context knowledge base; hence the expert system will be more intelligent by expecting user complaints. For diagnosing pests of tomatoes, we added knowledge that correlates between the current month and potential pests. So, the questions that relate to the current date will have a high rate of being asked by the grower. Also, we used weather services to get weather data and correlate it with potential pests. The result ensures that the proposed system outputs are as expected, and it displays symptoms of pests that are related to the grower context data.