Thesis Title: Terrestrial Biodiversity Data Processing Architectural Model Based on IoT Technology for Sustainable Livelihoods

Student’s Name: Onunga Jeremiah Osida

Supervisors Names

1. Dr. Anselemo Peters Ikoha
2. Dr. Peter Edome Akwee

Abstract

There are increasing challenges of terrestrial biodiversity variability change, creating problems like loss of livestock in Turkana County in Kenya. In the current digital age, IoTs are core to facilitate access to real time data and enhance efficiency across various services. The study investigated the various ways in which IoTs are deployed in communicating appropriate localized terrestrial biodiversity data to help rural pastoralists make appropriate decisions to improve their livestock productivity and their livelihoods. The study developed an architectural model for processing and sharing terrestrial biodiversity data, based on Internet of Things technology. The study redesigned model to mainstream IoT based terrestrial biodiversity data for increased long-term livelihood sustainability.  The study achieved this by evaluating the extent to which rural communities have access to IoT technologies; examining how rural communities utilize IoT-based terrestrial biodiversity data to enhance and sustain their livelihoods; assessing the effects of employing IoT-based terrestrial biodiversity data on the adoption of livelihood strategies and developing an architectural model based on IoT technology for processing and sharing terrestrial biodiversity data. The study used innovation diffusion and technology adoption theories to connect user adoption and practice, while also connecting it to biodiversity data for sustainable livelihoods. The study used mixed method, both quantitative and qualitative data. The study targeted a population of 164,519 households, from which a sample size of 384 households was surveyed. Data was collected using questionnaires, focus group discussions and key informant interviews. Data was analyzed and presented in tables. The study used inferential statistics to establish the statistical significant relationship between the variables. Path analysis was used to establish direct contribution of the requirement variables for the development of the model. The findings indicated that smartphones and radios are the most cost-effective and useful IoT devices for rural pastoralists to get timely biodiversity data and pastoral advice. The research findings was that rural pastoralists to utilize IoT based terrestrial biodiversity data. There was evidence that the rural communities’ livelihood methods have been improved, which strengthened their assets for a sustainable livelihood and improved their livelihoods. A request-response model was developed in this study for processing, sharing, and transmitting terrestrial biodiversity data. This research’s contribution to knowledge was an improved model, whose framework showed the relationship between data on terrestrial biodiversity and livelihood strategies through thematic analysis of diverse responses.