Katomaran Technologies developed ANPR, an advanced software solution for Singaporean authorities to capture and analyze vehicle license plates, addressing traffic congestion and air pollution issues. This case study demonstrates how ANPR enhances traffic management and air quality.


Environmental Factors

  • Katomaran Technologies utilizes high-resolution cameras and advanced image processing algorithms. It enhances LPR accuracy, addressing environmental factors like bright sunlight, rain, and low light conditions.

System Integration

  • It has seamless system integration and real-time data exchange.

Data Privacy

  • ANPR prioritizes data privacy by anonymizing license plate data after capture. It also focuses on traffic flow analysis and environmental impact studies.

Tech Stack


Adaptive Image Processing

  • ANPR employs advanced image processing algorithms to adjust to varying lighting conditions automatically. It ensures consistent accuracy in capturing license plates.

Data Anonymization

  • The software uses data anonymization to protect individual privacy. It enables efficient traffic pattern analysis and monitors environmental conditions after capturing license plate data.

API Integration

  • ANPR uses secure APIs to ensure seamless data exchange between its LPR system and Singapore's existing traffic management and air quality monitoring infrastructure.


  • ANPR is high-accuracy License Plate Recognition (LPR) software that captures vehicle plate numbers with exceptional accuracy, even under varying lighting conditions.
  • It processes captured data in real time, enabling immediate analysis and the generation of valuable insights.
  • ANPR seamlessly integrates with Singapore's existing traffic management and air quality monitoring systems.
  • It also provides a comprehensive understanding of traffic patterns and environmental impacts.


Katomaran Technologies' ANPR software is a valuable tool for Singapore to address traffic congestion and air pollution issues. It uses advanced LPR technology and data analysis to understand traffic patterns and their environmental impact. It enables the development of effective strategies for a cleaner, more sustainable Singapore.