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A Framework for Integrating Indigenous Knowledge With Wireless Sensors in Predicting Droughts in Africa

Masinde, Muthoni and Antoine Bagula (2011) A Framework for Integrating Indigenous Knowledge With Wireless Sensors in Predicting Droughts in Africa. In Proceedings Indigenous Knowledge Technology Conference 2011, Polytechnic of Namibia, Windhoek, Namibia.

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Unlike in other parts of the world, droughts are the leading natural disasters in Africa; they account for over 90% of effects perpetuated by natural disasters. The problem is compounded by the fact that droughts form a complex web of effects for which the onset, termination and quantification/qualification perplexes researchers to date. Agriculture sector still forms the backbone of most economies in Africa with 70% of output being derived from rain-fed small-scale farming. This sector happens to be the first casualty of droughts and hence the rampant food insecurity problem in most African countries. Accurate, timely and relevant drought predication information enables a community to anticipate and prepare for droughts and hence minimize the negative impacts. Though it may be argued that the science of predicting droughts has come of age especially in the West, the results of such predictions are still alien to African farmers most of whom live in the rural areas where they are still struggling with illiteracy and poor communication infrastructures. However, these farmers are host to indigenous knowledge on not only how to predict droughts but also unique coping strategies. On the other hand, effects of global phenomena such as population growth, climate change, global warming and ICTs revolution cannot be ignored and relying only on indigenous knowledge would endanger any community. Adoption of Wireless Sensor Networks and mobile phones to provide the bridge between scientific and indigenous knowledge weather forecasting methods is one way of ensuring that the content of forecasts and the dissemination formats meet the locals’ needs. A framework for achieving this integration is presented in this paper. A system prototype that implements this framework is also presented.

EPrint Type:Conference Paper
Keywords:Indigenous Knowledge, Droughts Prediction, Belief-Desire-
Intention Agents, Wireless Sensor Networks, Mobile Phones
Subjects:I Computing Methodologies: I.5 PATTERN RECOGNITION
ID Code:721
Deposited By:Bagula, Antoine
Deposited On:18 November 2011