Foundations of distributed artificial intelligence
Foundations of distributed artificial intelligence
Proceedings of the Sixth International Conference on Information and Communications Technologies and Development: Notes - Volume 2
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Despite global advancements in technology and inter-trade volumes, Sub-Saharan Africa is the only Region where cases of hunger have increased since 1990. Rampant and frequent droughts are one of the major causes of this. Monumental and mostly donor-funded projects have been mounted to counter this but with little success. One of the latest strategies being experimented is a community-based early warning system that seeks to integrate indigenous knowledge with western climate science. This initiative is informed by the realization that, though crucial, weather forecast information provided by the national meteorological departments has little utilization amongst small-scale farmers. Though having generated promising results, the integration project still faces the challenges of scaling up across communities as well as the lack of micro-level weather data. In this paper, we describe how the adoption of mobile phones and wireless sensor networks technology is being used to address these two challenges. Use of denser wireless sensor networks to collect local weather data and mobile phones to disseminate forecasts brings information closer to the farmers that need it most. To ensure that the non-mystical aspects of indigenous knowledge are portable across communities, language technologies (part of artificial intelligence) are used in the design of our system.