When Singapore raised the DORSCON status alert to orange and daily temperature screening was implemented on campus, the University Campus Infrastructure’s Digital Transformation Unit (UCI DTU), Organisational Excellence Transformation Unit (OETU) and GovTech started exploring ways to improve the current process of temperature screening to meet high human traffic demand.
GovTech proposed an AI-driven solution – VigilantGantry, an automated temperature screening system that alerts and bars movement when high temperature is detected, thus allowing prompt staff intervention and reduction in manpower. VigilantGantry also features an alarm to alert staff and facial recognition for contact tracing. Those with surgical masks need not remove their masks for the temperature scanner, resulting in less queuing and saving time.
The prototype, which was on trial at the NUS Central Library from 26 February to 11 March, showcased a solution that can be easily integrated with existing hardware to benefit the community. Ng Yong Kiat, Senior Manager from GovTech expressed his appreciation for the support from NUS and commended the project team for their dedication in ensuring that all necessary resources were in place for the trial set-up and deployment. Steven Chow, Principal Librarian who helped facilitate the trial, noted its effective screening which helped to keep the library users safe. “Our community’s well-being is of utmost importance to us,” Steven said.
The UCI DTU team helped to test VigilantGantry before it was made available for wider national use. “Across the University, NUS regularly collaborates with government agencies and corporations as a testbed for novel solutions before innovative ideas are widely applied,” explained Junius Soh, Senior Associate Director at UCI DTU.
Qianni Soh and Lim Wee Keong, Managers at OETU observed that the innovative temperature screening gantry provided a seamless experience, with many library users sharing that they were unaware of their temperatures being screened. The user feedback and data collected during the trial will enable GovTech to effectively scale up the gantry solution for future usage.
NUS and GovTech collaborators (from left): Rachel Shong (GovTech), Lim Wee Keong (OETU), Junius Soh (UCI DTU), Yam Guan Shyh (OSHE), Yuan Ye (NUS Libraries), Ng Yong Kiat (GovTech), Bill Cai (GovTech), Andy Quek (NUS Libraries), Corey Chong (GovTech), Delon Leonard, (GovTech), Koh Yan Leng (UCI) and Soh Qianni (OETU)