While AI-powered systems hold immense potential, they also raise significant concerns that cannot be overlooked. Below are the key challenges associated with AI-driven traffic counting cameras:

1. Individual Privacy Concerns of traffic counting cameras

AI traffic counting cameras rely on continuous data collection to monitor and analyse traffic patterns. This raises critical questions about how much personal information is being captured, how it is stored, and who has access to it. Balancing the need for innovation with the right to privacy remains a delicate issue.

2. Ethics of Data Retention

The long-term storage of collected data poses another layer of complexity. Policies around data retention often vary, leading to uncertainties about how long the data is kept and whether it could be used for unintended purposes.

3. High Lifecycle Costs and Operational Limitations

While these systems promise efficiency, the costs associated with their implementation, maintenance, and eventual upgrades can be significant. Additionally, their need for continuous power supply and large storage drives to accommodate 24/7 video recording presents logistical challenges. These constraints can limit the cameras' ability to operate year-round, resulting in incomplete data that fails to capture seasonal trends. Such gaps undermine their utility in providing an accurate and comprehensive picture of traffic patterns throughout the year.

Broken traffic counting camera

4. Inaccuracies and Data Gaps

Despite their sophistication, AI systems are not immune to errors. Misidentification, blind spots, or gaps in data collection can lead to flawed insights that impact large-scale urban planning and decision-making processes. They are especially susceptible to errors caused by environmental factors. Adverse weather conditions such as storms, snow, rain, and low-light scenarios during nighttime can hinder the cameras’ ability to detect and classify vehicles accurately.

Is there an alternative solution?

After more than 3 decades in the vehicle monitoring industry, and over 8 years conducting research and development, MetroCount has developed a ground-breaking, real-time data collection device that eliminates any concerns posed by traffic counting cameras while providing reliability, extreme accuracy, low lifecycle costs and ease of use.

Traffic counter magnetometer

Patented magnetometer traffic counting technology: RoadPod VM

The RoadPod VM consists of discreet sensors housed in solar powered cat’s eye studs. These are quickly and securely installed on a traffic lane in under 60 seconds each. The magnetometer technology inside collects anonymous yet precise information on every single vehicle passing by. This includes length, speed and traffic gap, providing vehicle volumes, classification and speed accuracy consistently higher than 98%.

The entire system is off-grid, allowing it to be installed almost anywhere and eliminating data gaps resulting in mains power outages. A solar panel, back-up battery and daily site diagnostics ensure a continuous stream of high-quality, reliable traffic information year-round at an extremely low cost compared to other traffic monitoring devices.

 

The system securely transmits data in real-time to a data analytics and storage software, where network-wide traffic flows can be easily understood on an interactive map. The software allows for data management, historical data storage and easy sharing with stakeholders.

Real-world uses

The RoadPod VM is already being used around the globe for a variety of purposes. The London Council of Ealing installed the system to gather 24/7, 365 day-a-year data that drives decisions on road maintenance, traffic calming and infrastructure design.

Sunshine Coast Council in Australia used the system connected to a digital variable message display to reduce rear-end collisions at a high-risk location.

Traffic sensor connected to digital variable sign

Timaru District Council in New Zealand use the RoadPod VM to monitor heavy vehicle movements at multiple locations and use data to apply for government funding.

Donna Seymour, Business Manager at Roading Logistics, says the RoadPod VM has significantly improved data collection on high-volume roads in a variety of ways.

“Switching to the RoadPod VM system saves us money, gives us more data all while reducing the risk to our staff - with limited time installing/maintaining sensors on the carriageway. It also improves the road environment by not using rubber tubes and nails or screws into the road surface.”

"The 24/7 real-time data has proved extremely accurate,” she explains. “We compared the data collected with both video monitoring and a MetroCount tube counter, on the same site for the same period."

"Our clients are so impressed with the data and being able to view/share the information so easily and clearly in the ATLYST software.”

"The other added benefit of the RoadPod VM is the cost. Once the system is installed and the data is flowing, that is pretty much where your costs end. So, for long term sites, you don’t need to visit the site, maintain the site, and if there ever was a problem, ATLYST will alert you to it!”

Traffic Counter
traffic counting camera

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