Countculture Sensors Aid City of Sydney Pedestrian Data Collection
Sydney CBD
Oxford Street
Sydney has undergone substantial transformations over the past 15 years, making strides in pedestrianisation, cycle lanes, and public transport. But, planners and businesses are sometimes limited by the lack of real-time data to support decisions.
Oxford Street was chosen for a trial deployment of Countculture sensors, leveraging existing relationships with the local business community and timed to coincide with the delivery of a separated cycleway.
Our sensor has capability to accurately count and classify different mode users on the footpaths and report near-misses between micro-mobility devices and pedestrians.
Oxford Street was chosen for a trial deployment of Countculture sensors, leveraging existing relationships with the local business community and timed to coincide with the delivery of a separated cycleway.
The trial tested a new partnership model, installing sensors under awnings using businesses' own power supplies. This approach was simpler and more cost-effective compared to mounting cameras on street light assets, which required additional power circuits to provide day time power and complex approvals.
While the key aim of the trial was to understand pedestrian flow on Oxford St throughout the day, another aspect of the trial was the use of Countculture’s advanced AI analytics, which can identify small vehicles such as share bikes and cargo bikes riding on footpaths.
Historically, there hasn’t been any way to access data around this issue, and understanding how it evolves is crucial, especially since share bikes have increased tenfold, from less than 400 in 2022 to over 4,000 today.
The Countculture anonymous sensor data allows the team to ask important questions about the riders and their behaviours. Sensor data will be able to reveal whether the number of people riding on the footpath tracks with the increased availability of share-bikes, for example.
Understanding these patterns can help address the issues more effectively, such as whether installing a cycleway would solve the problem or if people would still ride on the footpaths out of habit.
Additionally, the data provides insights into the night-time economy. Understanding these patterns is vital for urban planning to ensure the city remains vibrant and accessible.
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