ITIKI: bridge between African indigenous knowledge and modern science of drought prediction,

dc.contributor.authorMasinde, Muthoni
dc.contributor.authorBagula, Antoine
dc.contributor.otherTaylor & Francis (Routledge): Knowledge Management for Development Journal
dc.date.accessioned2016-02-10T12:34:54Z
dc.date.available2016-02-10T12:34:54Z
dc.date.issued2011
dc.date.issued2011
dc.descriptionPublished Articleen_US
dc.description.abstractDroughts are the most common type of natural disaster in Africa and the problem is compounded by their complexity. The agriculture sector still forms the backbone of most economies in Africa, with 70% of output being derived from rain-fed smallscale farming; this sector is the first casualty of droughts. Accurate, timely and relevant drought predication information enables a community to anticipate and prepare for droughts and hence minimize the negative impacts. Current weather forecasts are still alien to African farmers, most of whom live in rural areas and struggle with illiteracy and poor communications infrastructure. However, these farmers hold indigenous knowledge not only on how to predict droughts, but also on unique coping strategies. Adoption of wireless sensor networks and mobile phones to provide a bridge between scientific and indigenous knowledge of weather forecasting methods is one way of ensuring that the content of forecasts and the dissemination formats meet local needs. A framework for achieving this integration is presented in this paper. A system prototype to implement this framework is also presented.en_US
dc.format.mimetypeApplication/PDF
dc.identifier.issn1947-4199
dc.identifier.issn1871-6342
dc.identifier.urihttp://hdl.handle.net/11462/725
dc.language.isoen_USen_US
dc.publisherTaylor & Francis (Routledge): Knowledge Management for Development Journal
dc.relation.ispartofseriesKnowledge Management for Development Journal,;Vol. 7, Iss. 3
dc.rights.holderKnowledge Management for Development Journal
dc.titleITIKI: bridge between African indigenous knowledge and modern science of drought prediction,en_US
dc.typeArticleen_US

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