| dc.description.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. | en_US |
