000			03163nam a22003257a 4500
003			OSt
005			20250714144809.0
008			250714b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH TK 870 _bA73 2025
100			_aArceo, Nebiel _eauthor
245			_aEsagip: _badvanced water current and weather monitoring with rescue response using lorawan and unmanned aerial vehicle for real-time monitoring/ _cNebiel Arceo, Andrei Marlou C. Enova, Mhykel Aaron B. Lupac, Bingbong P. Malong, and Rinoa F. Pedragosa.--
260			_aManila: _bTechnological University of the Philippines, _c2025.
300			_axviii, 242pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege Of Engineering.-- _bBachelor of science in electronics engineering: _cTechnological University of the Philippines, _d2025.
504			_aIncludes bibliographic references and index.
520			_aThe Philippines’ vulnerability to climate-related disasters demands innovative solutions for effective monitoring, preparedness, and response. The eSAGIP system integrates emerging technologies such as IoT-enabled sensors, machine learning models, drones, and LoRaWAN communication to provide a comprehensive disaster management platform. It gathers real-time environmental data—weather conditions, air quality, water levels, and current speed—and transmits this information for centralized analysis. Machine learning models, including TCN-LSTM and Gradient Boosting, are used for forecasting and rescue operation prioritization. A cross-platform mobile and web application delivers real-time alerts, evacuation guidance, and rescue coordination, while UAVs assist in flood assessment and navigation. The system was deployed in Bacoor City, where it proved to be both functional and reliable. Sensor calibration confirmed high accuracy in data collection, and the TCN- LSTM model demonstrated strong forecasting performance—particularly in predicting pressure, temperature, and humidity. Although rainfall prediction showed limitations with extreme values, it effectively captured overall trends. User Acceptance Testing (UAT) reflected strong support from disaster response teams, technical experts, and residents, with 82% to 87% satisfaction ratings in functionality, usability, and safety. Users appreciated its intuitive interface and timely alerts. Some challenges, such as occasional connectivity issues and limited sensor coverage, were noted, but did not outweigh the system’s benefits. Overall, eSAGIP significantly enhanced Bacoor City’s disaster preparedness and response efforts. With further refinement and expansion, it holds great potential for replication in other flood-prone communities.
650			_aLoRaWAN network
650			_aUAV assistance
650			_aFlood assessment
700			_aEnova, Andrei Marlou C. _eauthor
700			_aLupac, Mhykel Aaron B. _eauthor
700			_aMalong, Bingbong P. _eauthor
700			_aPedragosa, Rinoa F. _eauthor
942			_2lcc _cBTH COE _n0
999			_c30338 _d30338