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Esagip: advanced water current and weather monitoring with rescue response using lorawan and unmanned aerial vehicle for real-time monitoring/ Nebiel Arceo, Andrei Marlou C. Enova, Mhykel Aaron B. Lupac, Bingbong P. Malong, and Rinoa F. Pedragosa.--

By: Contributor(s): Material type: TextTextPublication details: Manila: Technological University of the Philippines, 2025.Description: xviii, 242pages: 29cmContent type:
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  • BTH TK 870 A73 2025
Dissertation note: College Of Engineering.-- Bachelor of science in electronics engineering: Technological University of the Philippines, 2025. Summary: The 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.
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Item type Current library Shelving location Call number Copy number Status Date due Barcode
Bachelor's Thesis COE Bachelor's Thesis COE TUP Manila Library Thesis Section-2nd floor BTH TK 870 A73 2025 (Browse shelf(Opens below)) c.1 Not for loan BTH0006446

Bachelor's thesis

College Of Engineering.-- Bachelor of science in electronics engineering: Technological University of the Philippines,
2025.

Includes bibliographic references and index.

The 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.

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