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dc.contributor.authorNamugwanya, Mary Patience
dc.date.accessioned2023-08-14T10:35:05Z
dc.date.available2023-08-14T10:35:05Z
dc.date.issued2023
dc.identifier.citationNamugwanya, Mary Patience. (2023). Satellite store and forward system for landslide monitoring and prediction. (Unpublished undergraduate dissertation) Makerere University; Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12281/16206
dc.descriptionA research report submitted to the College of Engineering Design and Art in partial fulfillment of the requirement for the award of the degree Bachelor of Telecommunications Engineering of Makerere University.en_US
dc.description.abstractIn Uganda’s eastern and western hilly regions, landslides constitute a frequent and dangerous geologic hazard thus have resulted in a significant number of fatalities and significant economic losses. Investigations into landslides in the Mount Elgon region have minimal attempt made towards using modern technology to monitor, watch, and warn about landslide events. A good landslide hazards prevention program is required to address the awareness of several fundamental aspects of landslides. This project presents a satellite store and forward system for landslide monitor- ing and prediction . The system includes a network of wireless sensor nodes that are placed at potential landslide regions in order to capture data on ground saturation (soil moisture) and geomechanical properties (vibration). These are most significant quantifiable landslide parameters in Bududa. The Long Range transceiver linked to the sensor node uses Chirp spread spectrum to send sensor data to a LoRa board ,with a Long Range Wide Area Network gateway, that is onboard the satellite (Cube- Sat) across the unlicensed band of 868 MHz. The CubeSat LoRaWAN gateway is connected to The Things Network, a protocol and infrastructure that provides a link to cloud applications hence the name Store and Forward. The Things Network au- tomatically sends the collected sensor data to ThingSpeak .The data gathered is vi- sualized, analysed and examined from ThingSpeak. In order to display the data on a simple Hyper Text Mark-up Language web page and deliver notifications when the risk of a landslide rises, ThingSpeak iframes were used. This method offers cost-effective and efficient means to monitor landslides in real-time, acting as an early warning system that might potentially save lives and avert property damage. The architecture of the suggested system, the communication protocols, and the data processing algorithms are all covered in this study.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectSatelliteen_US
dc.subjectLandslideen_US
dc.titleSatellite store and forward system for landslide monitoring and prediction.en_US
dc.typeThesisen_US


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