Livestock identification and tracking system for controlling livestock theft: case study of South Africa.

Abstract

This thesis explores livestock theft problem within the South Africa context, focusing on cattle, sheep, and goats, and evaluates the potential of Information and Communications Technologies (ICTs) to address this critical problem. Conventional identification and tracking methods are currently ineffective, prompting the need for ICT based solutions. Despite calls for ICT intervention, no comprehensive conceptual model exists for South Africa. This study aims to fill this gap by proposing an ICT-based national livestock identification and tracking system to control livestock theft in South Africa. Utilizing Actor-Network Theory and a qualitative approach, the research includes interviews and questionnaires with stakeholders such as farmers, police, and stock theft forums. The study also integrates secondary data and literature, supported by a Scoping Review, snowball strategy, PRISMA method, and CASP framework. Data analysis employed thematic and content analysis techniques. Findings reveal that livestock theft networks are well-organized, highlighting the need of a unified national ICT based solution to combat livestock theft. The study identifies several potential ICT tools such as mobile phones, biometric technology, radio and TV broadcasting, camera traps, cloud computing, and drones as viable solutions. The proposed conceptual model of a national livestock identification and tracking system features two modules: retinal pattern-based biometric identification and three tracking methods. A Design Science Research Methodology (DSRM) framework was used to present the conceptual model for the proposed system. Recommendations emphasize the need for collaboration among stakeholders, including the Department of Agriculture, South African Police Service, and State Information Technology Agency. Limitations include a focus on the top ten livestock theft-hotspots and reliance on secondary data, with suggestions for future research to involve direct data collection from additional informants and explore how perpetrators use ICTs. The study contributes empirical insights and presents a practical model for controlling livestock theft through ICTs, along with a business case for its implementation. Future research should address the political implications and technical details of the ICT solution, as the current study does not cover the implementation process.