Foundation Projects
Empowering remote agricultural communities in Lao PDR through long-range wide area networks
Makerbox Lao
The project aimed to leverage the possibilities offered by low-power, long-range IoT solutions, in particular Long Range (LoRa) wireless, for relaying agriculturally-relevant sensor data from remote areas to modellers, and bring synthesized forecasting data to farmers in a simple-to-understand format, thereby bridging the technological and communication divide between urban centers and remote agricultural communities in the Lao PDR. Our design would have the capability of utilizing solar power, which is especially important in areas where electrical service is lacking or unstable. Being low-power was also a requirement, and LoRa was ideally suited for this due to its low power consumption, with some chips lasting years on a single battery charge.
In the first phase of the project, we assembled a prototype based on commercially available solutions that collates and forwards data, such as weather (air pressure, temperature, precipitation, humidity, wind speed, wind direction) and hydrological (water table and river levels) to us for analysis. The first prototype was installed in a countryside location that is representative in terms of geography and network coverage of the local conditions.
![](https://apnic.foundation/wp-content/uploads/2024/08/IMG_4259-1-768x1024.jpg)
In a second phase, we focused on cost reduction for the system, following review of the first phase and results from a small survey we conducted to learn about farmers' interest in agricultural data. We focused our new design on generic, cheap and easily accessible parts to ensure cost efficiencies and possibility of maintenance by local participants. We put an emphasis on locality, so that the system would both be assembled locally and adapted to local conditions and user needs. Finally, to ensure sustainability and awareness, we organized a hackathon where over twenty students from varied backgrounds worked on components of the revised system, gaining the required knowledge to further develop and implement a full-scale system.