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dc.contributor.authorAkankwatsa, Dickens
dc.contributor.authorMusinguzi, Douglas
dc.contributor.authorSsebuganda, Denis
dc.contributor.authorAlyao Jabulon, Emmanuel
dc.date.accessioned2024-01-08T09:51:47Z
dc.date.available2024-01-08T09:51:47Z
dc.date.issued2023-07-20
dc.identifier.citationAkankwatsa, D. et al. (2023). Flood Monitoring and Alert System (Unpublished undergraduate dissertation). Kampala: Makerere Universityen_US
dc.identifier.urihttp://hdl.handle.net/20.500.12281/18104
dc.descriptionA 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 of Makerere University.en_US
dc.description.abstractFloods pose significant risks to communities, infrastructure, and human lives, making effective flood monitoring and timely alert systems crucial for disaster management. This report presents a comprehensive overview of a Flood Monitoring and Alert System (FMAS) designed to mitigate flood-related risks. The FMAS integrates real-time data collection, advanced analytics, and user-friendly interfaces to enable accurate flood monitoring, early warning generation, and efficient dissemination of alerts. The FMAS is the first version that is built to run in a simulated test environment to continuously monitor the primary flood parameter of water level. The water level sensor is used and deployed in a container that simulates a water body. It is based on the Internet of Things (IoT) devices, to collect data with high precision and reliability. The collected data is transmitted to a centralized database in real-time, enabling the system to generate timely and accurate flood forecasts. The FMAS features a user-friendly mobile application-based support data analysis and flood prediction, the FMAS employs advanced analytics techniques, including machine learning algorithms and statistical modeling. These algorithms leverage historical data, weather forecasts, and hydrological models to predict flood patterns and assess their potential impact. By continuously updating and refining its models, the FMAS improves the accuracy of its flood forecasts over time. Interface accessible to both authorities responsible for flood management and the general public. Through this interface, users can visualize real-time flood data, access flood forecasts, and receive alerts and warnings based on predefined thresholds(described in section 2.6) . The system ensures the seamless integration of different communication channels, including SMS, and mobile applications, to disseminate timely and localized flood alerts to affected communities. The effectiveness of the FMAS has been demonstrated through extensive testing and evaluation However no field trials have been conducted for this version. Moreover, the FMAS's modular design allows for scalability and customization to meet the specific needs and requirements of different regions and infrastructure setups. In conclusion, the Flood Monitoring and Alert System (FMAS) described in this report represents a significant advancement in flood management and disaster preparedness. By combining real-time data collection, advanced analytics, and efficient alert dissemination, the FMAS enables proactive decision-making, timely response, and enhanced community resilience in the face of flood-related risks. The FMAS serves as a valuable tool for authorities, emergency responders, and individuals, fostering a safer and more secure environment in flood-prone areasen_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectFMAS (Flood Monitoring and Alert System)en_US
dc.subjectFlood Monitoring and Alert IoT systemen_US
dc.subjectApplication Programmingen_US
dc.titleFlood Monitoring and Alert Systemen_US
dc.typeThesisen_US


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