research-article

An Effective Drought Early Warning System for Sub-Saharan Africa: Integrating Modern and Indigenous Approaches

Author:

Muthoni MasindeAuthors Info & Claims

SAICSIT '14: Proceedings of the Southern African Institute for Computer Scientist and Information Technologists Annual Conference 2014 on SAICSIT 2014 Empowered by Technology

Pages 60 - 69

https://doi.org/10.1145/2664591.2664629

Published: 29 September 2014 Publication History

Abstract

Droughts remain the number one disaster in Africa; of all the people affected by all types disasters, drought is responsible for over 88% of them. An effective drought early warning system can support appropriate mitigation and preparedness strategies and hence minimize these effects. Existing systems tend to ignore the 'at risk' community and are faced with a number of implementation challenges; their utilisation is very low. This paper describes an effective drought early warning system that integrates indigenous and scientific drought forecasting approaches. The system is anchored on a novel integration framework called ITIKI (acronym for Information Technology and Indigenous Knowledge with Intelligence). Indigenous knowledge ensures that the system is relevant, acceptable and resilient. ITIKI further employs three ICTs (Mobile phones, wireless sensor networks and artificial intelligence) to enhance the system's effectiveness, affordability, sustainability and intelligence. This paper describes the design, development and evaluation of the system.

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An Effective Drought Early Warning System for Sub-Saharan Africa: Integrating Modern and Indigenous Approaches

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SAICSIT '14: Proceedings of the Southern African Institute for Computer Scientist and Information Technologists Annual Conference 2014 on SAICSIT 2014 Empowered by Technology

September 2014

359 pages

ISBN:9781450332460

DOI:10.1145/2664591

Copyright © 2014 ACM.

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Published: 29 September 2014

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SAICSIT '14

SAICSIT '14: Southern African Institute for Computer Scientist and Information Technologists Annual Conference 2014

September 29 - October 1, 2014

Centurion, South Africa

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Hameed MMohd Razali SWan Mohtar WYaseen Z(2023)Improving multi-month hydrological drought forecasting in a tropical region using hybridized extreme learning machine model with Beluga Whale Optimization algorithmStochastic Environmental Research and Risk Assessment10.1007/s00477-023-02548-437:12(4963-4989)Online publication date: 9-Sep-2023
https://doi.org/10.1007/s00477-023-02548-4
Lelamo LShenkut BAbdilahi A(2022)Drought characteristics and pastoralists’ response strategies in Korahey zone, Somali regional state, Eastern EthiopiaScientific African10.1016/j.sciaf.2022.e0125416(e01254)Online publication date: Jul-2022
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