Integrating Geospatial Technologies, Artificial Intelligence, and Citizen Science for Ethnobotanical medicinal plants: Towards improved Digital Public Health

ABSTRACT: Rural and indigenous communities still rely heavily on medicinal plants and ethnobotanical knowledge to support primary health care and provide cultural-based treatments. However, a significant amount of this knowledge remains scattered, underutilized, and undigitized in modern public health systems. In order to improve Digital Public Health systems, this conceptual review explores the integration of citizen science, Artificial Intelligence (AI) and Machine Learning (ML), and geospatial technology. AI and ML improve species identification, prediction, and knowledge synthesis; citizen science encourages community involvement and data collecting; and geospatial tools facilitate the mapping of medicinal plant resources and accessibility. In order to support conservation, health equity, and sustainable resource management, the article suggests an integrated system that connects citizen-generated ethnobotanical data with geographic and AI/ML analytics. This two-way system links policy-relevant digital outputs with community knowledge. The necessity for open, participative, and culturally sensitive digital platforms that support both biodiversity conservation and public health outcomes is highlighted by enduring challenges, including data interoperability, ethical governance, and inclusiveness.