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Computational Ecology and Software, 2025, 15(1): 1-14
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Article

Design of the data-driven software application for identification, population monitoring, and risk assessment for lions in Serengeti Tanzania

Ambokile Okey1, Devotha Nyambo1, Shubi Kaijage1, Emmanuel Masenga2, Matana Levi2
1School of Computational and Communication Sciences and Engineering (CoCSE), Nelson Mandela African Institution of Science and Technology (NM-AIST), Tanzania
2Serengeti Wildlife Research Centre (SWRC), Tanzania Wildlife Research Insitute (TAWIRI), Tanzania

Received 15 September 2024;Accepted 20 October 2024;Published online 29 October 2024;Published 1 March 2025
IAEES

Abstract
This study presents a design of a Data-Driven software application for identification, population monitoring, and risk assessment for lions in Serengeti Tanzania. Lions' populations have been declining due to poaching, overhunting, and other ecosystem factors resulting in unmet demands for tourism and ecological balance. Data-driven techniques can lower the negative consequences by providing mechanisms for lions' management, risk assessment, and monitoring in selected wildlife reserves. Lion's whisker spots, poaching rates, prey availability, human-conflict incidences, and pride size are key elements for achieving management, identification, monitoring, and risk assessment for lions. The software application design aimed at providing conceptual and logical requirements for the development of the application that will enhance lions' monitoring and management efforts to protect their existence and contribution to the ecosystem. The study was conducted in the Serengeti ecosystem, including ecologists from the Tanzania Wildlife Research Institute Serengeti Wildlife Research Center, and information systems analysts. Through a mixed research methods approach, qualitative methods and incremental prototyping software development life cycle model were used to develop the specific requirements. Unified Modeling Language (UML) was used to model the requirements and led to the realization of design diagrams: application framework, database design, and artificial intelligence model workflows. The application should equip ecologists with tools to add and identify specific lions, monitor sightings, estimate population trends, assess risks for individual lions, and produce reports on monitoring and sightings. This design serves as a foundation for developing the data-driven software application for identification, population monitoring, and risk assessment for lions in Serengeti National Park Tanzania which will enhance monitoring and management activities of lions' population non-invasively.

Keywords database design;functional requirements;non-functional requirements;lion's identification;wildlife monitoring;conceptual design;unified modeling language;artificial intelligence;whisker spots.


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