WASHtsApp -- A RAG-powered WhatsApp Chatbot for supporting rural African clean water access, sanitation and hygiene
This addresses the need for accessible WASH education in rural African communities, but it is incremental as it applies an existing RAG method to a new domain.
The paper tackled the problem of educating rural African communities on clean water access, sanitation, and hygiene (WASH) principles by developing WASHtsApp, a WhatsApp-based chatbot using Retrieval-Augmented Generation (RAG), which achieved high user acceptance and perceived usefulness in community validation.
This paper introduces WASHtsApp, a WhatsApp-based chatbot designed to educate rural African communities on clean water access, sanitation, and hygiene (WASH) principles. WASHtsApp leverages a Retrieval-Augmented Generation (RAG) approach to address the limitations of previous approaches with limited reach or missing contextualization. The paper details the development process, employing Design Science Research Methodology. The evaluation consisted of two phases: content validation by four WASH experts and community validation by potential users. Content validation confirmed WASHtsApp's ability to provide accurate and relevant WASH-related information. Community validation indicated high user acceptance and perceived usefulness of the chatbot. The paper concludes by discussing the potential for further development, including incorporating local languages and user data analysis for targeted interventions. It also proposes future research cycles focused on wider deployment and leveraging user data for educational purposes.