"ParkView": AI Innovation by Engineering Students, Winning the Popular Vote Award at the BDI Stage
Smart parking recommendation system using CCTV cameras, held under the theme “Building a Smarter Bangkok, Scaling to a Smarter Thailand.”
Congratulations to Team ParkView — members Ms. Julia Yrjoelae, Ms. Yonwaree Kanjasan, and Mr. Punnawit Suraruk, students in Artificial Intelligence Engineering and Data Science, School of Engineering — creators of “ParkView,” a smart parking recommendation system using CCTV cameras, for winning the Popular Vote Award among 213 teams narrowed down to 21 finalists at the BDI Hackathon 2026: OPEN AT BANGKOK, held under the theme “Building a Smarter Bangkok, Scaling to a Smarter Thailand.” The competition was organized by the Big Data Institute (Public Organization) under the Ministry of Digital Economy and Society.
From an Idea to the Competition Stage
“We saw the problem of roadside and illegal parking, which is one of the factors contributing to traffic congestion. So we applied AI technology and data to develop an approach for managing parking spaces that helps drivers and improves the efficiency of parking space management. We took an idea we had previously worked on as a classroom project and developed it further into ‘Park View’ — a smart parking recommendation system built on existing CCTV cameras, using Edge AI to display real-time occupancy data. We also integrated data from multiple sources, including the Google API, TOMTOM, and Traffy Fondue, to analyze occupancy levels and recommend suitable parking spots to users through a single all-in-one app — covering everything from search, navigation, and booking to automatic payment.”
ParkView: A Real-Time Smart Application
“ParkView was designed as an application for searching and planning journeys, capable of displaying parking area information, location, distance, and related data to help drivers decide on the most suitable parking spot for their destination. The system also applies data from CCTV cameras and AI technology for vehicle detection, while connecting data from various sources to support traffic analysis and route planning. The key goal is to reduce the time drivers spend circling to find parking, which helps cut down both wasted time and pollution from traffic.”
Overcoming the Competition to Win the Popular Vote
“The competition journey began with 213 teams narrowed down to 30, before entering a workshop process to strengthen knowledge in technology, databases, and AI from experts and project partners. The teams were then narrowed down further to 21, continuously developing their work until Demo Day. In the final round, the team presented their work on stage and showcased their prototype for the judges and attendees to view and discuss — impressing the audience and earning enough votes to win the Popular Vote Award. This achievement reflects strong interest in and positive reception of using technology to solve travel and parking challenges.”
Success That Extends Toward Real-World Application
“Behind the team’s success was dedicated hard work and guidance from Dr.Romuald Jolivot, their academic advisor, who provided consultation from the idea development stage, through technical problem-solving and AI implementation, to refining their slides and presentation. The team also visited real locations to study the feasibility of installing cameras and to speak with relevant stakeholders. They also gained experience working with mentors, experts, and the business sector — learning about technology, product development, marketing, and business models, while building a network to further develop their work in the future.”
The success of Team ParkView reflects the potential of students to apply their knowledge of technology and data to create innovations that address real-world problems — marking another important step in learning through real experience and developing work that benefits society.
