Project Description

In the bustling metropolitan area of Melbourne, Australia, the City of Stonnington stands out for its vibrant inner south-eastern suburbs, known for their rich culture, architecture, and bustling streets. Among its highlights is Chapel Street, an iconic hub for fashion, food, art, and entertainment. However, with its popularity comes the challenge of managing diverse traffic and ensuring safety and efficiency for all road users. This case study delves into how the City of Stonnington, in partnership with Minnovation, leveraged cutting-edge technology to address these challenges, focusing on the deployment of AlphaX Vision cameras equipped with NVIDIA edge processing capabilities.


Chapel Street is not just a road; it’s a dynamic ecosystem of shops, cafes, and cultural spaces, frequented by millions annually. The area’s traffic volume fluctuates significantly, influenced by the time of day and season, presenting unique challenges. These include the shared use of roads by vehicles, cyclists, and pedestrians, the operation of public transport routes, and the need for speed and safety monitoring. Understanding the usage patterns and interactions of different road users is crucial for planning and management.

Technology and Implementation

The cornerstone of our solution was the integration of AlphaX Vision cameras with advanced NVIDIA edge processing technology. This innovative approach enabled the cameras to analyze and process data on-site, significantly reducing latency and preserving privacy by anonymizing data before it’s uploaded to the cloud.

Edge Processing Technology

Edge processing technology is a transformative approach that allows for real-time data analysis at the source rather than relying on cloud processing. This method offers several advantages, including reduced bandwidth requirements, lower latency, and enhanced privacy. By processing data on the edge, the system can immediately identify and categorize different types of road users, from pedestrians and cyclists to vehicles and mobility devices, without transmitting sensitive personal information.


A total of eight AlphaX Vision cameras were strategically installed along Chapel Street. These cameras, disguised and mounted on public parking signs to blend seamlessly into the urban environment, continuously captured and analyzed traffic patterns. The AlphaX Cloud platform played a pivotal role in aggregating, analyzing, and visualizing the data, offering a comprehensive view of traffic flows, road user interactions, and behaviors.

Insights and Analytics

The system provided a multifaceted understanding of road usage, delivering insights across three key areas: quantification of road users, interactions among different types of traffic, and behavioral patterns. This detailed analysis included:

  • Vehicle, cyclist, and pedestrian counts.
  • Speed monitoring for both vehicles and bicycles.
  • Identification of cyclists on footpaths, highlighting safety concerns.
  • Assessment of mobility device usage in specific zones.

Results and Accuracy

The accuracy of the AlphaX Vision system was meticulously validated against manual counts, showcasing impressive precision across various locations. For example, at one site, camera counts were compared to manual tallies, revealing an accuracy rate of over 96%. This high level of reliability underscores the system’s capability to provide dependable data for traffic planning and management.

Location 1 Location 4 Location 2 Location 8
Camera Count 32 (17/15) 36 (22/24) 38 (24/15) 290
Manaul Count 31 (16/15) 38 (22/26) 39 (23/15) 301
Accuracy 96.8% 94.6% 97.4% 96.2%

Benefits and Future Applications

The deployment of the AlphaX Vision system has yielded significant benefits for the City of Stonnington. It has eliminated the need for costly manual counts and on-road counters, offering savings and enhanced insights from continuous monitoring. The system’s ability to provide real-time data enables traffic planners to make informed decisions swiftly, optimizing traffic flows and improving safety.

Furthermore, the insights gained from the system are invaluable for identifying trouble spots and planning infrastructure improvements. The detailed data supports the creation of 3D models for future road and path redesigns, ensuring that urban planning is based on comprehensive and accurate information.


The partnership between the City of Stonnington and Minnovation has set a new standard for urban traffic management. By harnessing the power of edge processing technology and the sophisticated analytics of the AlphaX Vision system, the city has gained unparalleled insights into its traffic dynamics. This case study exemplifies how innovative technologies can be leveraged to enhance urban living, making our cities safer, more efficient, and more enjoyable for all road users. As we look to the future, the expansion of this network promises even greater advancements in urban traffic management and planning.


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