000			02669nam a22002417a 4500
003			FT8873
005			20251210133511.0
008			251210b ||||| |||| 00| 0 eng d
041			_aengtag
050			_aT58.64 A73 2025
082			_a.
100	1		_aArcillas, Charlize L.; Sigua, Katrina Mae
245			_aMobiguard : An IoT-based monitoring system for persons with walking disability at home integrating computer vision, mobile application, and schedule reminder
264		1	_a. _b. _cc2025
300			_bCapstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
336			_2text _atext _btext
337			_2 unmediated _a unmediated _b unmediated
338			_2volume _avolume _bvolume
505			_aABSTRACT: Individuals with walking disabilities face significant risks, especially during emergencies like fires, due to their limited mobility. Caregivers, often balancing multiple responsibilities, struggle to provide constant supervision, increasing the safety risks for those under their care. Traditional monitoring methods offer limited real-time support, making it challenging to respond promptly during crises. To address these issues, this study developed MobiGuard, an IoT-based monitoring system designed to enhance the safety and well-being of persons with walking disabilities. The system aims to achieve three key objectives: (1) integrate a computer vision-based person tracking and fire detection model, (2) implement a mobile application for assistive communication between individuals and caregivers, and (3) enhance task management through real-time reminders with sound alarms. The MobiGuard system uses YOLOv8 for real-time object detection and tracking, paired with Arduino-controlled servo motors for dynamic camera adjustments. A mobile application, built with Android Studio and powered by Firebase, facilities caregiver-recipient communication and schedule management. The system also employs DFPlayer Mini and RTC DS3231 modules to deliver audio reminders at scheduled times. Results demonstrates the system’s effectiveness in accurately detecting persons (including came and wheelchair users) and fire, with a 92% accuracy rate for person detection and 70% for fire detection. Real-time notifications and audio reminders significantly improved caregiver response time and ensured timely task execution. Overall, MobiGuard provides a reliable solution for monitoring persons with walking disabilities, enhancing their safety and offering caregivers efficient tools for remote assistance and care management.
526			_aF
655			_aacademic writing
942			_2lcc _cMS
999			_c37317 _d37317