Normal view MARC view ISBD view

A Semi-Autonomous search and rescue mobot for victim localization in earthquake operations. 6

By: Lei Jan L. Ereno, Kamylle Feleen T. Mateo, Sophia Marie T. Miranda, Maria Kayla G. Pineda. 4 0 16, [, ] | [, ] |

Contributor(s): 5 6 [] |

Language: Unknown language code Summary language: Unknown language code Original language: Unknown language code Series: ; 4541346Edition: Description: Content type: text Media type: unmediated Carrier type: volumeISBN: ISSN: 2Other title: 6 []Uniform titles: | | Related works: 1 40 6 []Subject(s): -- 2 -- 0 -- -- | -- 2 -- 0 -- 6 -- | 2 0 -- | -- -- 20 -- | | -- -- -- -- 20 -- | -- -- -- 20 -- --Genre/Form: -- 2 -- Additional physical formats: DDC classification: | LOC classification: | | 2Other classification:

Contents:

Action note: In: Summary: ABSTRACT: The Philippines, situated in the Pacific Ring of Fire, is particularly vulnerable to disasters, especially earthquakes. During earthquake response operations, Search and Rescue (Sar) teams and victims face significant dangers due to aftershocks and hazardous environmental conditions. This study developed a SaR mobot with IR night vision, person detection, GPS and BLE-based victim localozation, and audio communication for earthquake response. Its mobility is facilitated by tracked wheels, a linear actuator, a dual motor driver, and two DC gear motors, and it can be remotely controlled utilizing 433 MHz KoRa. This study uses the TensorFlow Lite machine learning algorithm for person detection with an accuracy of 0.87, a precision of 0.92, and a recall of 0.92. Its frame rate has a mean of 4.17 FPS. The SaR mobot provides precise victim localization using BLE beacons for indoor relative positioning and GPS for outdoor positioning. Additionally, environmental conditions are accurately monitored using DHT22 and MQ-5 sensors. The operator can access gas, temperature, humidity readings, GPS coordinates, and real-time videp footage via a web server with a mean latency of 2.77 seconds. In conclusion, this study successfully met its objectives and demonstrated the optimal performance of the SaR mobot for earthquake response operations. Other editions:

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings ( 1 )
Title notes
Comments ( 0 )

Item type	Current location	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	PLM	PLM Filipiniana Section	Filipiniana-Thesis	TK5105 .E74 2024 (Browse shelf)	Available		FT7913

Total holds: 0

Browsing PLM Shelves , Shelving location: Filipiniana Section , Collection code: Filipiniana-Thesis Close shelf browser

Previous	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	Next
Previous	TK2891 B45 2025 Detection and classification of pneumonia in chest radiographs using hybrid CNN-Vision transformer model	TK4001 .M57 2024 Hybrid far infrared radiation and hot air rice grain dryer.	TK5102 .D48 2024 A Wireless data acquisition system for soil erosion measurement in sloping hillside.	TK5105 .E74 2024 A Semi-Autonomous search and rescue mobot for victim localization in earthquake operations.	TK5105 .G33 2024 Unmanned amphibious robot in aiding post-typhoon heavy flooding response using LoRa-based communication and YOLOv5 /	TK6565 .D48 2021 IoT-based life jacket tracker with dead-reckoning system for maritime search and rescue operations /	TK7800 H47 2024 Real-time driver drowsiness and distraction detection using convolutional neural network with multiple behavioral features	Next

Undergraduate Thesis : (Bachelor of Science in Electronics Engineering) - Pamantasan ng Lungsod ng Maynila, 2024. 56

ABSTRACT: The Philippines, situated in the Pacific Ring of Fire, is particularly vulnerable to disasters, especially earthquakes. During earthquake response operations, Search and Rescue (Sar) teams and victims face significant dangers due to aftershocks and hazardous environmental conditions. This study developed a SaR mobot with IR night vision, person detection, GPS and BLE-based victim localozation, and audio communication for earthquake response. Its mobility is facilitated by tracked wheels, a linear actuator, a dual motor driver, and two DC gear motors, and it can be remotely controlled utilizing 433 MHz KoRa. This study uses the TensorFlow Lite machine learning algorithm for person detection with an accuracy of 0.87, a precision of 0.92, and a recall of 0.92. Its frame rate has a mean of 4.17 FPS. The SaR mobot provides precise victim localization using BLE beacons for indoor relative positioning and GPS for outdoor positioning. Additionally, environmental conditions are accurately monitored using DHT22 and MQ-5 sensors. The operator can access gas, temperature, humidity readings, GPS coordinates, and real-time videp footage via a web server with a mean latency of 2.77 seconds. In conclusion, this study successfully met its objectives and demonstrated the optimal performance of the SaR mobot for earthquake response operations.

There are no comments for this item.

to post a comment.