In 2018, AWS initiated its Hackday program, providing teams across the ASEAN region with the chance and resources to create innovative projects and vie for exciting prizes, including a trip to Las Vegas for the annual re:Invent conference. Over 1,000 developers from countries such as Singapore, Vietnam, Malaysia, Indonesia, the Philippines, and Thailand collaborated in teams to develop new technologies during a single-day hackathon. The winners from each region then competed in Jakarta, where the Thai team ultimately secured the grand prize and the coveted trip to Las Vegas.
Building on last year’s triumph, AWS launched the second edition of the hackathon, this time with an emphasis on addressing pressing challenges within each community across four sectors: HealthTech, AgriTech, FinTech, and Smart City. This year’s competition was made accessible online, allowing participants from all over ASEAN to join.
The response was overwhelming, with more than 1,500 participants eager to compete. Similar to the previous year, leading teams were selected to advance to the final round, taking place at the AWS Singapore Summit in April. Each team was tasked with creating a “Computer Vision for Good” project within a 9-hour timeframe. Utilizing AWS, Intel’s Movidius Neural Compute Stick, and OpenVino ToolKit, teams diligently worked under pressure to present their solutions to a panel of experts.
Learn more about each team below, starting with the champion from Malaysia, Team Galaxy.
Team Galaxy – Malaysia
This team of colleagues from a Malaysian broadcasting company came together to form Team Galaxy. Azhar, Ravi, and Mira, all Solution Architects at Astro, claimed victory in their regional competition with ParkSmartly, an application designed to provide real-time parking information through IoT-connected devices. Their winning hack utilized computer vision to identify specific objects and send automatic alerts. Initially aimed at detecting firearms, their solution was intended to enhance security and provide efficiency for security teams. The challenge of monitoring video feeds for weapons made a computer solution invaluable.
Team Morning Glory – Thailand
Returning for a second consecutive year, Team Morning Glory, the previous champions, focused on fitness this time. They developed an application that captures video of workouts and notifies users when their form is incorrect. Although they didn’t achieve back-to-back victories, team members Anon, Poon, and Kanya performed admirably, finishing in second place.
Team Happy Faces – Vietnam
Representing Vietnam, this quartet aims to reduce workplace stress by encouraging employees to begin their day with a smile. Nhi, Long, Minh, and Hoa designed a check-in system that prompts employees to smile as they enter the office, using computer vision to analyze facial expressions and emotions.
Team SafeVision – Philippines
Identifying autism in young children can be challenging. Team SafeVision, composed of Leo, Sam, Eric, and Tessa from Nokia, created a hack aimed at helping parents recognize early signs of autism. Their technology leverages computer vision to detect behaviors such as rapid movements and facial expressions, simplifying the process for parents.
Team Guardian – Indonesia
Having met during their university studies, Team Guardian later collaborated at GDP Labs, a subsidiary of GDP Ventures focused on high-impact projects. Experienced team members Fajar, Sari, and Rian aimed to develop a computerized eye to protect visually impaired individuals, often vulnerable to crime. Their technology, named SEEIT, aids users in avoiding obstacles, detecting crimes, and capturing images of suspects.
Team CareConnect – Singapore
Though Team CareConnect had known each other through church, this competition marked their first tech project collaboration. Jaden, Timothy, and Emily won their regional contest by creating a tool for doctors to transcribe and annotate notes during endoscopies. In their quest to innovate in the healthcare field again, Team CareConnect sought to employ machine learning to analyze fetal scans for early detection of abnormalities.
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