15 February 2021

Law Enforcement / Smart City Traffic Management – Asia

Advanced ALPR Software enabling

ALPR Accuracy 0%
Multi-operator 0+ seats
Operational 0Hrs 365 days / year

The Sinamalé Bridge links the islands of Malé, Hulhulé and Hulhumalé (through Hulhulé’) in the Maldives. The 1.39 km long bridge has two vehicle lanes and separate lanes for motorcycles and pedestrians.
Opened on 30 August 2018, it is the first inter-island bridge in the Maldives.

The Challenge

The Maldives Police Service reported accidents have taken place almost daily on the Sinamale’ Bridge since its inauguration in 2018 and 40 percent of the accidents that took place on Sinamale’ Bridge were due to speeding.

Vaxtor was invited by the Maldives government agency to design a smart traffic monitoring system for both the Sinamalé Bridge and also the rest of the highways on the main islands for detecting vehicle speed violations and also for detecting traffic “red light” violations (vehicles that drive through red lights after an initial grace period).

The main operational challenges of the projects were:

  1. How to fully leverage the existing and new surveillance cameras to not only function as normal surveillance cameras but also to utilise them as speed violation sensors for over-speeding vehicles?
  2. In addition to detecting speeding vehicles, how to identify the vehicle’s license plates and automatically send all violation details to the police database for further investigation?
  3. How to leverage both the existing and new surveillance cameras to function as vehicle “red-light violation” detection cameras and how to identify these license plate details to trigger further police sanctions?
  4. How to further enhance the “Safe City” monitoring with the minimum investment?
  5. How to ensure the “smart traffic solution” is an “OPEN” system, able to be integrated with other government agencies’ systems and guarantee that the system is continuously upgraded?

The Solution

Based on the customer’s requirements, Vaxtor designed a “Smart Traffic” System based on both existing and new AXIS cameras converting normal cameras into multi-function smart IoT devices that perform:
General surveillance, license plate recognition, vehicle speed capture, vehicle over-speed alarm generation, over-speed vehicle data reporting, traffic light status monitoring, red-light running detection, red-light violation license plate capture and also red-light violation data reporting.

Vaxtor’s proposal avoided the use of additional radar detectors and leveraged existing assets to achieve the automatic detection of speeding vehicles. The solution utilized existing camera power supply points and lamp posts minimising infrastructure costs.

The solution avoided the expensive closure of airport roads to install ground-loops by utilizing cameras to optically detect changes in the status of the traffic lights, thus avoiding any physical connection with any critical traffic infrastructure and avoid any operational risk.  

Vaxtor’s solution utilized all the existing and planned cameras as ALPR IoT sensors to continuously capture all vehicles’ license plates as big data for future traffic and city development planning. In addition the system automatically identifies any “black-listed vehicles” such as those with past speeding records, potential terrorists, reported stolen vehicles, vehicles with expired road tax or any vehicles of interest needing to be tracked by government agencies. The system also detects vehicles driving the wrong way, vehicles parked on the hard shoulder and vehicles that have broken on the main highway.

Vaxtor’s solution can also provide useful data such as vehicle counting on specific sections of highway to warn of potential traffic jams.

One of the most popular Vaxtor functions used by customer is the versatile search function to instantly extract traffic information for quick decision making and the data can be automatically passed to police agencies’ existing systems for a fully integrated information system.

The Result

Phase 1 of this project is now being deployed and the license plate accuracy rate performance is in the 95-98% range. The customer is already planning to expand this solution to other neighbouring islands.