Land valuation system

dc.contributor.author Ssemwogerere, Trevor
dc.contributor.author Ssali, Benjamin
dc.contributor.author Kazibwe, Julius
dc.contributor.author Namuli, Sylvia
dc.date.accessioned 2025-10-31T10:13:28Z
dc.date.available 2025-10-31T10:13:28Z
dc.date.issued 2025
dc.description A project report submitted to the School of Computing and Informatics Technology for the study leading to a project in partial fulfillment of the requirements for the award of the Degree of Bachelor of Science in Software Engineering of Makerere University. en_US
dc.description.abstract The Land Valuation System is a web-based platform developed to address the persistent challenges of land valuation, such as inconsistent pricing, unreliable data sources, and the lack of standardized methodologies. This system leverages machine learning algorithms and real-time data integration to provide accurate, data-driven predictions of land values across various regions. By incorporating a wide range of factors—including historical land sales data, infrastructure development, environmental metrics, and demographic trends—the system offers users intelligent valuation insights, trend analyses, and customizable reporting tools. Designed with scalability and usability in mind, the platform features a user-friendly interface, metadata-based search functionality, interactive dashboards, and integration with external data sources like government and real estate databases. The system’s architecture is built on a robust tech stack consisting of a Flask backend, a Next.js frontend, PostgreSQL for data management, and GIS tools such as the Google Maps API. This design ensures high performance, seamless data processing, and adaptability to diverse user needs. Targeting stakeholders such as real estate investors, urban planners, financial institutions, and land developers, the Land Valuation System aims to standardize the valuation process, promote market transparency, and enhance decision-making in land-related investments and policy formulation. en_US
dc.identifier.citation Ssemwogerere, T., Ssali, B., Kazibwe, J. & Namuli, S. (2025). Land valuation system (Unpublished undergraduate dissertation). Makerere University, Kampala, Uganda. en_US
dc.identifier.uri http://hdl.handle.net/20.500.12281/20886
dc.language.iso en en_US
dc.publisher Makerere University en_US
dc.subject Machine Learning en_US
dc.subject Land en_US
dc.subject Software Development en_US
dc.title Land valuation system en_US
dc.type Thesis en_US
Files