Design for Human-Baboon Conflict Management: Animal Location Using a Sensor Network Ecosystem

Siguín, Marta ; Marco, Álvaro ; Trasviña, Carlos ; Casas, Roberto ; O’Riain, Justin ; Blanco, Teresa

En : Advances on Design Engineering V. Proceedings of the 34th INGEGRAF International Conference, INGEGRAF2025, June 25–27, 2025, Seville, Spain. Volume II: Pioneering Graphical Engineering, Design Methods, AI Applications and Educational Innovation
2026
Springer Cham
ISBN: 978-3-032-08107-0
Pp: 421-431

Abstract: Human–wildlife conflict is an escalating global issue, especially in urban-edge environments where wildlife seeks anthropogenic resources. In South Africa’s Cape Peninsula, chacma baboons (Papio ursinus) regularly enter urban areas, leading to safety risks, property damage, and threats to the animals themselves. This study presents a novel localisation system developed through an Animal-Centred Design approach, aimed at supporting the management of these conflicts in an ethical, low-impact manner. The system combines LoRa and Bluetooth Low Energy (BLE) technologies to enable proximity-based detection and alert generation, avoiding the need for GPS and reducing energy consumption and device weight. The infrastructure is designed to integrate seamlessly into the urban environment by installing fixed receivers on residential and other building rooftops, allowing for discreet deployment while promoting community involvement. Technical validation under field conditions confirmed reliable communication over several kilometres and effective system operation. The system is intended to support the work of rangers and conservation teams by providing timely information for early intervention, without requiring continuous on-site surveillance. These results demonstrate the value of interdisciplinary, welfare-conscious design in developing scalable technologies for wildlife monitoring, with potential applicability to other species and conflict scenarios.

Nota: Postprint This work was supported by Aragon Regional Government through BOA20211216010 and BOA20240517024 (ref. MVT_01_24). It was also partially funded by the Aragon Regional Government through the Program for Research Groups under Grant T27_23R (Howlab Research Group) and PROY_T38_24; and by the Centro Universitario de la Defensa under the project CUD-2025_08.

DOI: 10.1007/978-3-032-08108-7_32