Cities and municipalities face a number of tough questions as they try to provide residents with a good place to work and live. How much congestion and pollution are caused by vehicles circling the block as drivers look for a parking spot? Which intersections have the most near-miss accidents? Where is jaywalking common — and why?
The ability to answer these questions is one hallmark of smart cities. Traditional technologies such as road tubes, inductive loops and infrared counters provide an incomplete picture of how vehicles and pedestrians move around a city.
To develop a more complete understanding of these issues, smart cities are turning to enhanced video surveillance and analytics, which provide deeper, data-driven insights. As a result, smart cities know where their transit and infrastructure budgets may have the greatest impact.
Video as Data
In many cities, some streets see a significant increase in traffic due to changing circumstances, such as the construction of new housing developments. This may have unexpected consequences, such as making it more difficult for drivers to make left turns through heavy traffic.
Traditional traffic counters would show the increase in traffic, but they can’t pinpoint which intersections have become dangerous. Accident reports may help, but they don’t count the much larger number of near misses, so the city doesn’t know where those are trending up.
However, video analytics can provide these kinds of deep insights, with metadata about what the cameras are seeing. Artificial intelligence can turn thousands of hours of video into data and scrutinize it to detect patterns and problems that would otherwise require an army of humans to ferret out. With this kind of analysis, a smart city’s managers know exactly where to add a signal or a median to facilitate left turns.
Meanwhile, in a downtown area, the correlation of data from both traffic cameras and parking occupancy rates might determine that traffic is congested because drivers keep circling the block to find parking. That insight could determine where to add a municipal parking garage or bus stop, or whether to revise building codes so future developments have adequate parking.
Jaywalking represents another problem that video surveillance can address. Video analytics can identify pedestrian trends and patterns that indicate an emerging need for crosswalks with signals, pedestrian bridges or waist-high medians that force people to cross only at intersections. Each of these options comes at a different cost. Which one will be most effective, including in terms of cost? Video analytics can help municipal officials to make informed decisions based on such questions.
Supporting Video Systems
Cameras from vendors such as Bosch and Hanwha have built-in analytics that are capable of identifying pedestrians, vehicles, direction, dwell time and other attributes. A side benefit of this capability is that they can lighten the traffic load for the network. In fact, some cameras are smart enough to know when there’s something worth streaming for real-time or forensic analysis, or when to upload only metadata. When paired with the right video management system and other advanced video analytics software, video data can be exploited in countless ways to improve both city safety and operations.
Municipalities that want to take advantage of enhanced video surveillance should look for camera systems that provide the features they need. They also need a network that can support the flow of data, a video management system to handle this data, storage to make it available when needed and an analytics platform to glean insights. As they build out their video surveillance capabilities, smart cities also should keep scalability in mind, as municipalities that adopt video analytics often identify additional use cases.