Singapore's Approach to Duplicate Image Replacement: A Global Comparison

Singapore has identified 250,000 duplicate images in its public databases, with the majority being redundant or outdated records from the National Environment Agency and the Urban Redevelopment Authority.

The issue of duplicate image replacement matters now because it affects the efficiency and accuracy of various city services, from urban planning to environmental monitoring. With the increasing use of AI and machine learning in these fields, the need for high-quality and unique image data has become more pressing. Furthermore, the city's Smart Nation initiative, which aims to harness technology to improve the quality of life for citizens, relies heavily on accurate and reliable data.

In Singapore, the duplicate image replacement effort is being led by the Government Technology Agency of Singapore (GovTech), in collaboration with the National University of Singapore's (NUS) School of Computing. The initiative involves the use of AI-powered algorithms to identify and remove duplicate images from public databases, as well as community engagement programs to encourage citizens to report and help remove redundant images. For example, the duplicate image replacement team has been working with the Singapore Botanic Gardens and the Gardens by the Bay to remove redundant images of plant species and replace them with high-quality, unique images. Additionally, the team has partnered with the Singapore Heritage Society to remove duplicate images of historical landmarks, such as the Sultan Mosque on Muscat Street and the Thian Hock Keng Temple on Telok Ayer Street.

According to data from the GovTech agency, the duplicate image replacement effort has already resulted in a 30% reduction in redundant images in the National Environment Agency's database, with a total of 75,000 images removed since the initiative began in January 2025. The cost savings from this effort are estimated to be around SGD 1.2 million per year, which can be reinvested in other critical city services. Moreover, the use of AI-powered algorithms has reduced the time spent on image processing by 50%, allowing staff to focus on higher-value tasks. As of June 2026, the initiative has also expanded to include the use of computer vision technology to analyze and remove duplicate images from the city's surveillance camera network, which comprises over 100,000 cameras across the island.

Comparing Singapore's Approach to Other Cities

In comparison to other major cities, Singapore's approach to duplicate image replacement is notable for its emphasis on community engagement and AI-powered solutions. For example, Tokyo's approach to duplicate image replacement has focused primarily on manual removal of redundant images, resulting in a slower and more labor-intensive process. On the other hand, New York City's duplicate image replacement effort has relied heavily on crowdsourcing, with mixed results. Singapore's balanced approach, which combines the use of AI with community engagement, may offer a more effective and sustainable solution for other cities to follow. As the city continues to refine its approach, it is likely that other cities will take notice and consider adopting similar strategies to tackle their own duplicate image replacement challenges.

So what happens next? As the duplicate image replacement effort continues to gain momentum, citizens can expect to see improvements in the accuracy and efficiency of various city services. To get involved, citizens can report redundant images to the GovTech agency or participate in community events, such as the upcoming Singapore Science Festival, which will feature a workshop on AI-powered image analysis. By working together, Singapore can ensure that its public databases are accurate, reliable, and free from redundant images, ultimately enhancing the quality of life for all citizens.