A public transport detection system for the visually impaired using the internet of everything/ Jherwin G. Bautista, Nhiel Criane O. Bautista, Eomer Paul T. Sta. Maria, Wilfredo B. Tunay Jr., Elijah Joshua B. Venus.--

Bachelor's thesis

College of Industrial Technology.-- Bachelor of engineering technology major in computer engineering technology: Technological University of the Philippines, 2025.

Includes bibliographic references and index.

Transportation 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.