Last month Adroit installed its first three IoT video sensors as part of a cycle traffic monitoring project. The project for a local city council saw the installation of Bosch camera equipment specifically designed to detect vehicles to assist in traffic management and cycle lane assessment. These cameras will feed data back via the Adroit platform to provide accurate, real-time data initially on cycle lane use, and further down the track will have the option to provide a complete range of pedestrian, cycle and vehicle information.
So, why are they putting this tech in?
Cycle Lanes are often a hot topic for Councils, therefore there is a real need to collect data on their use and to make assessments about their effectiveness and ROI.
The Adroit solution is designed to provide data that will give the Council an understanding of not only how many individuals utilise the cycle lanes, but also the direction travelled, and times of day and days of the week they’re most used.
Technology that can report on traffic of all kinds in real-time is a really good way to help Councils understand where they’ve spent money on infrastructure, and that it is actually having a positive influence on the community they serve.
If the council knows this data, then what can they do with it?
Currently, most cycle data is collected by people with clipboards standing at key intersections for a period of time. As these individuals are unable to stay in place for all 24 hours, seven days a week, (or it is very costly to keep them there), the data is always only an extrapolation of observations made for a few hours on a few days.
As a result, key insights and opportunities could be missed – such as: are there a large number of cyclists going through an area before dawn and is the lighting adequate? Or how many cyclists are students or children and the safety implications of the roading layout? These are things planners wouldn’t know unless they’d experienced it themselves, or if they’d stationed someone there at that time.
And while basic counting is the first objective, Councils ideally need to identify more complex outcomes, such as how many bikes turn left or right at an intersection, meaning that the lane could be placed better, or traffic lights could be modified to facilitate that.
Once a Council has access to real-time data, they’re able to start to tweak the roading system for the benefit of all. And they’ll have excellent historical data to utilise in planning for the future.
How it Works
Adroit’s city platform is based around Bosch camera technology, connecting to the Adroit platform via the Cat-M1 IoT network.
What we’ve done is to make the camera into an IoT sensor that effectively transfers only the counted data. We don’t transfer a video stream, just the data – 10 bikes went left, 10 bikes went right, 10 bikes went straight.
To do this, Adroit created its own integration device that pulls the metadata from the camera, normalises it and uploads it into our Adroit platform, where we’re able to display all of that information via a dashboard onto Android or iOS devices. Then we plug that through as an API to the Council to give them access to that data for analysis through their own planning platforms.
Adroit chose to utilise Bosch cameras for the solution. Bosch has a whole range of cost-effective cameras that do all types of things, with inbuilt analytics software on the camera. They’ve got the ability to identify the difference between pedestrians, cycles, cars, trucks, so forth.
So, data collection can be focused solely on cyclists or expanded to all traffic – measuring the ratio of cyclists vs vehicles on the road, the impact of congestion, weather conditions and other public transport options. All are possible via the Adroit solution.
Camera detects a car, bike and pedestrians
Adroit Platform monitoring dashboard
The solution we’ve developed here is getting interest from multiple areas. And not just for road use.
People want to know the number of cars in car parks for example. Think about a ski field car park for example – if you drive all the way up the mountain and find out it’s full, you’ve got to drive all the way back down. Whereas if you had a camera counting the number of cars, it would be easy to automate a barrier that stops additional cars from coming through almost immediately.
Or you’ve got lecture halls with 300 person capacity (for example), but no one can see from a management perspective what occupancy they’re achieving, so there’s no impetus to change the facility, layout, promotion or customer interaction. With a video analytics-based attendance counting solution you can easily and cost-effectively gather data on attendance numbers and duration.
These scenarios are well within current video analytics capabilities, but there are many more options. Such as with the use of Artificial Intelligence, data from the cameras can be used to measure all kinds of scenarios, then alerts can be added for certain limits or schedules, or other actions triggered.
We originally started talking with a local council in October, and within six weeks we had approval. We developed the integration and installed the initial site in February and it’s all functioning well. In the next week, we’re going to be doing a validation process of having people on the streets counting cyclists versus the camera to validate the accuracy.
And then this will be hopefully something that will potentially be adopted by other councils.
Adroit’s philosophy is working with all the best suppliers for specialist applications – leveraging technology developed by global companies spending significant amounts on research and development.
Our mantra is to find best-of-breed tech products for a particular use case and bring them together in a fit-for-purpose way to market. That’s why we’re able to provide innovative, cost-effective and low-risk solutions delivered quickly and easily for businesses across New Zealand.
To learn more about Adroit’s IoT camera analytics-based solutions –