In the 1970’s, Los Angeles launched its first big-data project, “The State of the City: A Cluster Analysis of Los Angeles”. The study focused on a wide variety of city issues, from unemployment levels to the number of traffic accidents.
Fast forward to 1994. That year, Amsterdam arguably took the title of first Smart City with its De Digital Stat initiative, which sought to promote internet usage. Over the next two decades, the Smart City movement slowly coalesced thanks to major investments from Cisco and IBM. Legislative initiatives like the American Recovery and Reinvestment Act (2008) and the EU Electricity Directive (2009) further accelerated the emergence of today’s Smart City.
When Barcelona deployed its Smart City initiative in 2012, the city’s plan for data-driven urban systems specifically included parking, public transit, and street lighting. The concept of Smart Cities has evolved since then. The modern Smart City has several key characteristics:
Note that a city’s traffic directly relates to many of these elements. For example, reduced traffic congestion supports environmental sustainability and improved safety. An effective public transit system can make a city a more attractive place to live, contributing to the city’s economic competitiveness.
Data is truly the foundation of any successful Smart City initiative. Rich, accurate data is necessary for city planners to make well informed decisions. And today, data is hardly in short supply. The Internet of Things (IoT) connects a host of sensors, cameras, and other devices–even including vehicles.
To complement this data, about 84% of people also carry a constant data source right in their pockets. Smartphones generate a wealth of data that can be collected, anonymised and analysed. Although the use of smartphone data is relatively new, it offers plenty of opportunities for innovative city planners.
Accurate Data is the foundation of any successful Smart City initiative
When it comes to traffic management, getting accurate, timely data has long been a challenge. In decades past, people would manually count cars at intersections, yielding only a brief snapshot of traffic that could hardly be generalized to other traffic scenarios. Road tubes offered an improvement here, allowing for 24-hour counting, but providing little insight on other important factors like vehicle classification, its direction or traffic violations.
Surveillance cameras are surely a far better option–they can monitor 24/7 and provide a host of data. But according to some estimates, about 98% of this video footage goes unwatched and humans miss 95% of the relevant incidents.
This is where artificial intelligence makes an incredible contribution to traffic management. For example, AI-powered software can analyze traffic camera data in real time, immediately sending alarms to transport management systems. It can also collect historical data, for better insights on traffic trends over time.
This kind of software offers many applications that directly support the goals of a Smart City:
It may seem that real-time traffic video analytics are complex and cumbersome, especially for cities that have limited resources. However, the transition can be easier than you think–and yield long-term advantages that more than pay for the initial investment. A few steps can help you choose the right software to maximize your benefits, without blowing your budget.
Most cities already have at least some traffic cameras, for instance at busy intersections or areas of high congestion. Look for software that will work with your existing traffic cameras, so that you don’t have to buy the software and purchase new equipment. Capitalize on your current traffic monitoring infrastructure wherever you can.
Before you embark on the journey of implementing a new system, take some time to assess what data you actually need, or would like to have. Think beyond what’s already available: If you could have any traffic data, what would it be? While not everything might be available, implementing real-time video analytics should substantially expand what’s accessible.
One potentially sneaky cost of real-time traffic video analytics is storage. All that video data can add up, and not all software providers are upfront about storage costs. Look for a provider that offers transparent pricing on storage–along with robust security, to ensure that your data is well protected.
While data storage is a hidden cost, there are some oft-overlooked opportunities for cost savings for the whole city. Data collected from traffic monitoring systems might provide information that other city departments can use, helping them to run more efficiently. Look for opportunities to share data beyond your department to realize further cost savings.
So the numbers are there, but what comes next? You and your team must be able to use all your traffic data! Choose a platform that has interactive tools and dashboards to support traffic modeling. These might include features like data filtering tools, reports and exporting capabilities.
At GoodVision, we’re proud to deliver a robust set of traffic monitoring tools that include real-time video analysis. Our Live Traffic is a complete software solution for traffic monitoring and real-time event detections. It is equipped with an AI engine compatible with your existing IP cameras. The system analyses camera streams automatically and provides traffic data to third party systems. Traffic data is also collected into GoodVision Video Insights analytical platform for your next traffic analyses. An interactive analytical application allows users to define events and scenarios, detecting speeding, congestion, traffic violations or illegal parking.
Ready to learn more? Contact us or check out our on-demand webinars to see our software in action globally.