Oh Tiong Keng is currently manager-in-charge of Autonomous Technology Innovation Centre at Nanyang Polytechnic (NYP), focusing on autonomous-related projects with SMEs in the area of logistics, healthcare, facilities management, security and surveillance, hospitality, etc. He leads and develops AI & autonomous system solutions in the area of manufacturing, transportation, healthcare, security, etc.
Prior to this, he was manager-in-charge of the Imaging Technology Centre and Machine Vision Centre at NYP, focusing on imaging-based applied R&D projects with industry in the area of machine vision, video analytics and real-time automated inspection, test and measurement systems, etc. He has led project teams to garner 9 externally and internally granted R&D projects worth more than S$1.7M. He has also developed, implemented and managed over 120 industry collaborative projects with SMEs and MNCs such as Seagate, Delphi Automotive, Rolls-Royce, Hoya Medical.
Throughout his career, Tiong Keng has led many award-winning project teams such as the development of a patented depth-programmable self-floatation device, and an automatic 2-dimensional semiconductors package inspection system.
As part of an industry project with a Singapore SME to develop a Foreign Object Debris Intelligent Detection and Alarm System (FIDAS), Tiong Keng was responsible for developing the intelligent camera system that detects foreign object deposit (FOD) in real-time and integrating with other modules like LADAR (Laser and Radar) and GPS to pinpoint its exact locations. The camera system automatically takes pictures of all detected FOD and records information on the nature, time and location of the detected FOD. The information is stored in the FIDAS database for analysis, enabling the operator to identify areas more prone to FOD.
Collaborated with a Singapore SME that developed a train fault detection system using AI (artificial intelligence), imaging and sensors to detect the current collector device (CCD) fault on moving trains. Whenever there was an incoming train, high-resolution cameras are triggered to take up to a thousand photos and an AI engine would screen them for any improper contact. Tiong Keng was responsible for leading the development of the deep learning-based AI engine that is able to localise the components of CCD and classify any defected components that cause the improper contact of CCD with trains.
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