000			03473nam a22003257a 4500
003			OSt
005			20250711150825.0
008			250711b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH QA 76.9 _bB38 2025
100			_aBautista, Jherwin G. _eauthor
245			_aA public transport detection system for the visually impaired using the internet of everything/ _cJherwin G. Bautista, Nhiel Criane O. Bautista, Eomer Paul T. Sta. Maria, Wilfredo B. Tunay Jr., Elijah Joshua B. Venus.--
260			_aManila: _bTechnological University of the Philippines, _c2025.
300			_axii, 109pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Industrial Technology.-- _bBachelor of engineering technology major in computer engineering technology: _cTechnological University of the Philippines, _d2025.
504			_aIncludes bibliographic references and index.
520			_aTransportation is an important part of daily life; it provides individuals to maintain independence and participate in society. But for the visually impaired, navigating through public transportation remains a significant challenge due to inadequate infrastructure, insufficient access to assistive technologies, lack of standardized protocols, poorly trained transit staff, and limited tactile or auditory guidance in public transit environments. There are numerous methods used to assist the visually impaired, like designated PWD seating or limited tactile paving, including the latest technological innovations, such as, use of electromagnetic technologies, Global Positioning System modules, Radio Frequency communications systems, and Artificial Intelligence-driven computer vision models and detection sensors. However, these technologies still face challenges, with limited detection ranges, bulky and heavy components, insufficient battery life, lack of real-time feedback, inability to adapt in diverse environments, and another is the high costs of development and maintenance. This project study aims to design, develop, test, and evaluate an assistive cane using the Internet of Everything and AI-based computer vision system, offering real- time audio feedback for navigation and vehicle classification. The project was developed and implemented based on Agile Scrum methodology. Test results show that the system is functional based on its design specifications, and significantly consistent in terms of its accuracy (F (3,76)=0.650634, p=0.584986) and timeliness (F (2,57)=0.161784, p=0.851014; F (2,57)=0.814923, p=0.447764). performance . The project was evaluated by 10 visually impaired, and 10 experts as respondents and rated it as overall "Very Good" based on ISO 25010:2023 evaluation criteria of functional correctness, functional appropriateness, usability, compatibility, effectiveness, and safety. The project study is contributory to the United Nations’ Sustainable Development Goals (UN-SDG) No. 3 and 10 – Good Health and Well-Being and Reduced Inequalities, respectively.
650			_aAssistive cane
650			_aInternet of everything
650			_aVisually impaired
700			_aBautista, Nhiel Criane O. _eauthor
700			_aSta. Maria, Eomer Paul T. _eauthor
700			_aTunay Jr., Wilfredo B. _eauthor
700			_aVenus, Elijah Joshua B. _eauthor
942			_2lcc _cBTH CIT _n0
999			_c30300 _d30300