SE-DiagEnf: An Ontology-Based Expert System for Cattle Disease Diagnosis

Abstract

Cattle husbandry industry is an important development sector in many countries around the world. One of the main problems in this sector concerns cattle diseases which result in low productivity. A rapid diagnosis of the disease is particularly important for its prevention, control, and treatment. However, the main players on cattle husbandry industry highly depend on veterinarians to cope with this problem. Unfortunately, the number of veterinarians in some cities is very limited or they live far away from the farm. In this sense, it is necessary to provide farmers tools that help them to correctly diagnose the cattle diseases. Nowadays, there are technologies that can help to address this issue. On the one hand, expert systems are an active research area for medical diagnosis and recommending treatments. On the other hand, ontologies can be used for modeling the domain of cattle diseases diagnosis and for generating the knowledge base that is required by the expert system to perform its corresponding tasks. In this work, we present SE-DiagEnf, an ontology-based expert system that diagnoses cattle diseases based on a set of symptoms and provides recommendations for tackling the disease diagnosed. The main goal of this system is to decrease the dependency of farmers on veterinarians to cope with cattle diseases diagnosis and treatment. SE-DiagEnf was evaluated by farmers from Ecuador. In this evaluation, farmers had to provide a set of symptoms to allows the system to diagnose the cattle disease. The evaluation results seem promising based on the F-measure metric.