SIWA evaluation ends with increased farmer adoption, stronger trust in data-driven forecasts
The evaluation of the Smart Indigenous Weather Application (SIWA) has ended across selected districts, recording increased farmer adoption and growing trust in data-driven weather forecasting.
The exercise, conducted in Obuasi East, Asin Fosu and Atiwa West, assessed how farmers are using the application and reviewed the accuracy of forecasts generated through the platform. It also provided an opportunity to share results with users to guide future decision-making.
Findings from the evaluation show that farmers are increasingly willing to complement indigenous knowledge with scientific weather forecasts to improve planning and reduce risks associated with changing climate conditions.
The Climate Change and Ecosystem Monitoring Lead at the DIPPER Lab, Dr. Enoch Bessah, said the engagement is helping to improve how farmers respond to climate variability.
“Things that farmers relied on for predictions in the past are no longer consistent due to changes in the environment and ecological patterns. This is why it is important to integrate scientific forecasts to support their planning,” he said.
He added that continuous data collection through the application will strengthen its artificial intelligence model and improve forecast accuracy over time.
The Smart Indigenous Weather App (SIWA) was introduced to farmers in the municipality in 2025, with periodic engagements held to gather feedback and improve its performance.
During the latest evaluation, prediction charts were reviewed with farmers to assess accuracy and identify areas for improvement.
As part of the exercise, the Gender Lead, Dr. Elikplim Abui Tamakloe, engaged women farmers to assess the app’s usability and its impact on household decision-making.
According to her “the engagement showed increased participation of women in farm-related decisions, with many expressing confidence in using the application and willingness to recommend it to others”.
The ObaaSIWA initiative, which focuses on women’s inclusion in digital agriculture, is being implemented under the Gender and Responsible Artificial Intelligence Network (GRAIN) as part of efforts to develop the Gender Equality and Digital Inclusion (GEDI) framework and the SIWA mobile application.
The initiative is funded under the EmpowerHerAI programme and delivered through a collaboration between the DIPPER Lab and the GRAIN Network under the Artificial Intelligence for Development (AI4D) programme.
