DETERMINANTS FOR THE ADOPTION OF INTERNET OF THINGS (IOT) FOR FLOOD AND DROUGHT DISASTER MANAGEMENT IN KENYA.
Authors: Gilbert Barasa Mugeni ; Kelvin Kabeti Omieno ; Franklin Wabwoba ; Simon Maina Karume ; Leonard Mabele ; Daniel Otanga
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Major disasters continue to affect millions of people worldwide every year. These disasters range from earthquakes, floods, hurricanes, cyclones, hunger, terrorist activities to collapse of buildings, among others. Floods and droughts are by far the most common natural disasters worldwide and account for the most deaths. The deadliest disaster of the 20th century was the China floods of 1931, which resulted in more than a million deaths. One common characteristic of these disasters is the poor predictability and inability to stop the occurrence of the same. This research proposes a real time IoT big data analytics system that collects a huge amount of flood and drought related information generated prior to, during, and after the disaster, and employs big data analytics and visualization techniques among others to support situational awareness and decision making by providing timely, accurate and relevant information to relevant groups of stakeholders. It is to be noted that with slight changes in the transducers and design approach, this technique employed in the study can easily be extended for use with any other disaster management. In fulfilling the first objective of the research, we carried out a survey in Kenya among experts, opinion leaders, policy makers and selected members of public on the factors influencing the increased adoption of IoT technology for flood and drought disaster management in Kenya. The results of the research indicate that Perceived knowledge (PK), Perceived Ease of Use (PE), and Relative advantage (RA) respectively are very significant in influencing the adoption of IoT technology in flood and drought disaster management in Kenya, while self efficacy (SE), and Referent’s Influence (RI) constructs were moderately significant. However, perceived declining cost (PD), Facilitating conditions (FC ), and utilitarian outcome (UO) were found to be least significant in explaining the behavioural intention to adopt IoT for flood and drought management in Kenya. Among the Key recommendations,