As more urban areas adopt a “smart city” model, an effective implementation strategy comes down to the right mix of technology, funding and mindset, writes Zareh Megerdoonian, Hanwha Vision America.
City life is a fast-paced mix of commerce, tourism, entertainment, congestion, crime, rapid growth and changing demographics. To keep pace, the traditional security and surveillance technology that’s used to protect people and property must evolve to support Intelligent Transportation Systems (ITS).
Traditional city surveillance monitoring can now enhance traffic management and, as cities grow, they can pivot to a “smart” infrastructure mindset.
The ongoing acceptance of AI and advanced data analytics has allowed surveillance camera technology to shift from being a tactical tool to a strategic business solution.
Combining traditional surveillance technology with AI-based processing, data-driven insights can streamline transportation systems, enhance traffic management, improve situational awareness, optimise resource allocation and streamline emergency response procedures.
Smart cities leverage connected devices and sensors to collect data and improve efficiency across areas like traffic, energy and public safety.
ITS technology helps smart city managers perform critical data analysis to allocate and manage public safety resources, manage transportation systems and create safer environments for passengers and transit employees.
It also helps to protect every mode of transportation, from mass transit systems and terminals to airports and borders.
A growing market
ITS involves leveraging the camera as a sensor, where the video captured is secondary to the rich metadata extracted. That data serves as the foundation to building predictive models and solutions, ultimately enhancing urban living and even promoting sustainability.
To continue the smart city growth trend, cities must have a mindset that’s open to change.
That includes investing in robust fibre optic networks, which ideally serve as the foundation of ITS by enabling high bandwidth connectivity and low-latency communication.
Expanding use cases and applications
The potential applications and use cases for smart cities and ITS environments are diverse. They include traffic safety, congestion reduction and the integration of connected and autonomous vehicles (CAVs). However, they also extend to other applications, including:
- Air quality – where ITS can collect real-time data on air pollution and particulate matter to help cities take actions to reduce pollution or regulate traffic flows based on pollution levels and promote cleaner vehicles
- Public transportation efficiency – using real-time data to schedule routes efficiently
- Demand-responsive transportation – in areas with low demand, smaller vehicles or flexible transportation alternatives are allocated
- Smart parking solutions – using sensors and apps to help drivers find parking options, reducing driving time spent searching for parking and ultimately reducing traffic
The list also potentially includes logistics management, health and emergency response, data-driven city design, community engagement, accessibility, autonomous delivery and crowd management.
Intelligent transportation technology
The phrase “doing more with less” is a perfect way to describe how security and surveillance devices are doing more than just “monitor and protect.”
City agencies are looking for ways to maximise their security spending by getting the most out of an initial technology investment.
Surveillance solutions are increasingly incorporating on-board analytics to provide low latency real-time alerts and deliver data that can drive intelligent business decisions.
Multi-sensor camera technology is a perfect example. With one device through one data connection, it’s possible to monitor and record several key areas with unique fields of view for each, such as outdoors in public areas or intersections, roads and shared pathways.
Adding the power of analytics to those cameras makes it possible to collect analytics-based data while providing safety and security alerts.
With built-in analytics, cameras are capable of driving truly intelligent transportation and surveillance functions. For example, a popular use case is “incident detection” – identifying road congestion or stalled vehicles in real-time.
This type of detection done with smart cameras can send notifications to the traffic management centre (TMC) and simultaneously send notifications to drivers by activating flashing lights and signs.
City stakeholders may want to detect and track pedestrian street-crossing patterns, jaywalking or detect a near miss and collision. Work zone management is a concern for safety, along with commercial vehicle parking or double parking.
Planners may need to know how many people cross the street outside city hall or near a light rail facility.
Since the cameras are already pointing in the direction of that train station, they can capture that data but can also gather footage useful to the police department if needed.
Enabling this cross-agency function are multi-sensor cameras, now powered by a Graphics Processing Unit (GPU).
The addition of an in-camera GPU can provide the horsepower necessary to adopt best of class ITS video analytics without adding external servers or edge processors.
The power of the GPU allows complex traffic safety analytics on the first stream while sending the second H.265 video stream to real-time crime centres (RTCC).
Being able to process traffic analytics on one stream, while providing a HD video stream to the VMS is truly the silver bullet for a dual-function multi-agency smart camera.
Using this dual-approach model is also efficient. The metadata stream is roughly 5% of the size of a video stream, while being anonymous and GDPR compliant for privacy.
A smart city is perfectly fine with anonymous data, whereas a police department would typically require specific attributes of a person and their demographic profile which can be derived from high-quality HD video.
The final tech piece comes down to network connectivity and data access. To avoid latency, fibre connectivity or at least 5G is optimal. One agency may have less developed fibre network and more point-to-point wireless connectivity compared to another area with strong fibre infrastructure and network uptime.
A collaborative mindset
Implementing ITS and smart city technologies requires alignment between different agencies and departments, as well as overcoming challenges like legacy infrastructure, budget constraints and cultural resistance to change.
AI is now at a tipping point where its accuracy enables it to replace existing sensors.
That said, if a traffic agency can’t use the utility pole to hang or power a camera, then these solutions are impossible to realise. A collaborative mindset is key across departments to maximise tax dollars and ROI.
Overall, the goal of smart cities and ITS is to create a more connected, efficient and sustainable urban environment. These technologies help cities manage resources more effectively, improve quality of life and support economic growth.
The long-term outlook for intelligent transportation systems and the development of smart cities will continue to hinge on a holistic approach combining surveillance technology, easy access to funding and a forward-thinking mindset.
When properly conducted, the results can represent a pivotal stage in urban management and infrastructure, leading to a safer, more secure and more efficient world.
Zareh Megerdoonian
Zareh Megerdoonian is Business Development Manager, ITS & Smart Cities, North America at Hanwha Vision America.