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dc.contributor.advisor | Marco Segura, Juan Bautista![]() |
es_ES |
dc.contributor.advisor | Rivas Casado, Mónica![]() |
es_ES |
dc.contributor.advisor | Bajón Fernández, Yadira![]() |
es_ES |
dc.contributor.author | Sancho Martínez, Jorge![]() |
es_ES |
dc.date.accessioned | 2023-02-13T10:13:50Z | |
dc.date.available | 2023-02-13T10:13:50Z | |
dc.date.created | 2019-12-04 | |
dc.date.issued | 2023-02-13 | |
dc.identifier.uri | http://hdl.handle.net/10251/191794 | |
dc.description.abstract | [EN] The proposed project focuses on the use of drones with autonomous capabilities for the inspection of water treatment processes in wastewater treatment plants (WWTPs). Trickling filters and activated sludge have been selected as systems were to proof the concept of using autonomous drones for daily route inspections. Malfunction of such systems occurs on a regular basis. In remote and small plants, inspector officers cannot scan the systems daily, meaning that when they malfunction, the discharges will not be meeting the consents established by the regulators. To avoid this, the use of autonomous drones in combination of artificial intelligence (AI) could help to detect failures in the systems meaning that the inspector officer can get to know in advance if it is necessary to check the WWTP or not, which is one of the main expenses of the UK water companies, sending inspector officers frequently to these remote rural areas. The results of the combined used of autonomous drones and AI proved that the use of Unmanned Aerial Vehicles (UAVs) can be used for asset inspection in the water industry, specifically in wastewater treatment processes. The next steps of the water industry to develop the use of AI and UAVs would be in reservoirs nutrient detection, in wetlands the plant density measurement and plant identification and odour, volatile compounds and greenhouse emissions detection from WWTPs. | es_ES |
dc.description.sponsorship | I would like to thank Andrea Wilson Bursary which compounds Atkins, Scottish Water, Severn Trent and Cranfield University for funding this MSc Thesis and providing full access to the study sites. | es_ES |
dc.format.extent | 32 | es_ES |
dc.language | Inglés | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Trickling filters | es_ES |
dc.subject | Activated sludge | es_ES |
dc.subject | Unmanned aerial vehicles | es_ES |
dc.subject | UAVs | es_ES |
dc.subject | Asset inspection | es_ES |
dc.subject | Wastewater treatment plant (WWTP) | es_ES |
dc.subject.classification | INGENIERIA HIDRAULICA | es_ES |
dc.subject.other | Máster Universitario en Ingeniería de Caminos, Canales y Puertos-Màster Universitari en Enginyeria de Camins, Canals i Ports | es_ES |
dc.title | The combined application of artificial intelligence and autonomous drones to the water industry | es_ES |
dc.title.alternative | La aplicación combinada de la inteligencia artificial y los drones autónomos a la industria del agua | es_ES |
dc.type | Tesis de máster | es_ES |
dc.rights.accessRights | Cerrado | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos - Escola Tècnica Superior d'Enginyers de Camins, Canals i Ports | es_ES |
dc.description.bibliographicCitation | Sancho Martínez, J. (2019). The combined application of artificial intelligence and autonomous drones to the water industry. http://hdl.handle.net/10251/191794 | es_ES |
dc.description.accrualMethod | Archivo delegado | es_ES |