This community innovation has been accepted at the 2025 DHIS2 Annual Conference
Digitizing dhis2 data using voice, images and AI
(PLEASE SEE FULL ABSTRACT PDF) This presentation will explore how we can make use of AI services to ingest image and voice data into pre-defined programs/data sets in DHIS2. By harnessing image-to-text and speech-to-text LLMs abilities, we can convert these two modalities into data payloads of DHIS2 programs and have a more automated way of capturing data. This approach could facilitate the speed of data digitalization, allowing data entry users to focus on the quality of these registrations, reviewing and correcting fields when needed. However, these approaches require evaluation and validation in real world contexts and should not be considered a silver bullet. In SolidLines, we have been working during the last 2 years on generative AI-based applications for chatbots in Kenya, South Africa, and India, and we want to bring this world closer to DHIS2. In our presentation, we will share a proof-of-concept to explore this multimodal data capture into DHIS2, and will share our key learnings about combining LLMs with DHIS2. This example will show how AI-assisted tools can streamline data ingestion, allowing users to focus on validating and ensuring data accuracy. We will also share lessons learned from implementation of other AI projects in low resource settings to help inform how DHIS2 and AI assistive tools can be more effectively tested and evaluated with field use cases for iterative improvement of the tools alongside governance and other issues.
Primary Author: Amalia Villa
Keywords:
IA, LLM, artificial intelligence, voice, image, digitalization
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