Industry
Smart Mobility
Duration
2 months
Team Size
4 people
Project Overview
A group responsible for managing vehicular traffic in Singapore approached Katomaran Technologies with a clear goal: to modernize their operations. Their existing system was outdated, cumbersome, and struggling to keep up with the demands of a fast-paced urban environment. They needed an AI-powered Automatic Number Plate Recognition (ANPR) solution capable of reading license plates accurately in any weather—blazing sun, heavy rain, or dark nights. The new system also had to work smoothly with their current citywide CCTV network without requiring a major infrastructure overhaul, all while keeping privacy front and center.
Challenges
Making traffic management effortless wasn't as simple as it sounds
- 1Weather Variability: The system needed to accurately read license plates in diverse weather conditions, including intense sunlight, heavy rain, and low-light night environments.
- 2CCTV Integration: The solution had to integrate seamlessly with Singapore's existing citywide CCTV network without requiring costly or disruptive infrastructure changes.
- 3Privacy and Data Security: Ensuring the protection of sensitive data, particularly license plate information tied to individuals, was critical to comply with privacy regulations.
Our Solution
We tackled these challenges with smart, practical solutions
- 1AI-Powered ANPR for All Conditions: Developed a robust AI-based Automatic Number Plate Recognition (ANPR) system trained on a vast dataset of images from various weather scenarios to ensure high accuracy in any condition.
- 2Seamless CCTV Integration: Designed an integration layer using RESTful APIs to connect the ANPR system with the existing CCTV network, enabling real-time data processing without hardware upgrades.
- 3Privacy-Focused Security Measures: Implemented end-to-end encryption, data anonymization, and strict access controls to safeguard sensitive information and ensure compliance with Singapore's privacy laws.
Key Modules
The system keeps everything running smoothly
- 1ANPR Engine: The core component responsible for detecting and reading license plates from CCTV footage with high precision.
- 2Weather Adaptation Module: Adjusts image processing techniques in real-time to account for varying weather conditions, ensuring consistent performance.
- 3Integration Layer: Facilitates smooth communication between the ANPR system and the city's existing CCTV infrastructure via APIs.
- 4Privacy Compliance Module: Enforces security protocols, including encryption and access management, to protect data and meet regulatory standards.
- 5Dashboard and Reporting Tool: Provides a user-friendly interface for traffic management teams to monitor operations, generate reports, and gain insights.
Services Offered
Services that we offered to make the client vision ourreality
Web Application Development
Crafting secure, scalable platforms that power your online presence.
AI & ML
Harness the power of data with custom models and intelligent automation to drive smarter, faster decisions.
DevOps & Cloud Engineering
Streamlining deployment pipelines and infrastructure for reliable, rapid delivery.
Tech Stack
The technologies and frameworks we leveraged to build a robust, scalable, and high-performance solution.
TensorFlow
Deep Learning Framework
OpenCV
Computer Vision Library
React.js
Frontend Framework
Python
Programming Language
PostgreSQL
Database System
AWS
Cloud Platform
Impact & Results
The system has transformed traffic management
- 1Enhanced Recognition AccuracyThe system achieved a 95% accuracy rate in license plate detection across all weather conditions, a significant improvement from the previous system's 70% accuracy in suboptimal conditions.
- 2Faster Incident ResponseResponse times for traffic incidents improved by 30%, allowing for quicker resolution of issues and smoother traffic flow.
- 3Cost EfficiencyBy integrating with the existing CCTV network, the project avoided an estimated $2 million in infrastructure upgrade costs.
- 4Privacy and ComplianceThe system passed all privacy audits with zero compliance issues, ensuring trust and security for both authorities and the public.
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