DR. MUTHONI MASINDE
PhD. Computer Science, MSc. Computer Science (Distinction), BSc. Computer Science (Upper Second Division)
Chiromo Campus, School of Computing and Informatics Building, muthoni@uonbi.ac.ke
Chiromo Campus, School of Computing and Informatics Building, muthoni@uonbi.ac.ke
Mbeere is in Eastern Kenya and it has an average of 550 mm annual rainfall and therefore classified under Arid and Semi-Arid Lands. It has fragile ecosystems, unfavorable climate, poor infrastructure and historical marginalization; the perennial natural disasters here are droughts. Of importance to this paper is the fact that despite its vast area of 2,093 km2, there is no single weather station serving the area. The main source of livelihood is rain-fed marginal farming and livestock keeping by small-scale and peasant farmers who rely mostly on the indigenous knowledge of seasons in making cropping decisions. ITIKI; acronym for Information Technology and Indigenous Knowledge with Intelligence is a bridge that integrates indigenous drought forecasting approach into the scientific drought forecasting approach. ITIKI, a framework initiated by the authors of this paper was adopted and adapted from the word itiki which is the name used among the Mbeere people to refer to an indigenous bridge used for decades to go across rivers. ITIKI makes use of mobile phones, wireless sensor networks and artificial intelligence to downscale weather/drought forecasts to individual farmers. ITIKI implementation project in Mbeere commenced in August 2012; this paper describes the implementation roadmap for this project.