Science and Technology Development
Google maps with CartoDB
Farmers in Thailand find it difficult to access crucial agricultural information that enables them to plan their seasonal work and increase their productivity. This vital information is stored in various knowledge centres across the country. The aim of the National Electronics and Computer Technology Centre (NECTEC) was to centralize this information and provide a solution that helped to decrease the negative outcomes of the current system, such as oversupply. NECTEC has collaborated with various government agencies to gather the right kind of information to start the project, with the goal of improving farmers’ incomes and overall quality of life.
- To improve the planning for economic crops, land suitability and connecting to local purchasing
- Use CARTO to solve the problem of fusion table and storing big shapefiles
The solution focuses on farmers and how to grow the ‘right’ crops in their areas while taking into account soil type, weather and overall demand for the area. The project comprises of three main elements: an agricultural-products-for-replacement model, an e-learning and agriculture database and a weather-monitoring station.
In the first year, the NECTEC team together with GoPomelo developed the system for agriculture data integration and data optimisation. Using the solution from CARTO, GoPomelo’s technical team helped NECTEC to create the frame to solve the problem of fusion table and storing big shapefiles.
- A web and mobile based maps application, using Carto APIs to visualise agricultural data across Thailand
- Thai Farmers are now able to be more informed when making decisions for land suitability when growing crops
- Farmers can use agriculture information to better plan the distribution of their products in the local area
The web and mobile based application uses Carto APIs to visualize agriculture data across Thailand. Farmers are now able to access this information and make a decision based on the data. This solution will enable farmers to facilitate the prediction of demand for crops and distribution in the local area, leading to greater productivity in the community. The project will later be expanded nationwide.