Save Cities are Smart Cities


Save Cities are Smart Cities

Find additional savings by reducing IP network demand

In terms of smart security, a smart city, a smart campus, a smart building and a smart home have a lot in common.

Elected city officials, city planners, their teams and contractors share a common charge with business officers, property managers, school administrators and homeowners — protect their most valuable resources.

In 2023, managing financial resources is increasingly critical for everyone. A key to affordable smart security is to use automated and intelligent tools to reduce costs. In municipalities, the idea is to use smart video surveillance systems to trigger event notifications and reduce the need to pay large numbers of staff to watch all the cameras, all the time.

In addition, these tools deliver additional savings by reducing demand on the IP network and the need for storage capacity of recordings. Why? Because instead of recording all the time, your video surveillance system records when triggered.

By now, most people are aware of video analytics, including people entering, people exiting, people counting, line crossing and the defining detection zones. The ability to hide things within the camera’s field of view is especially important in municipal applications to preserve the rights of private property owners while monitoring public spaces.

Deep learning AI goes beyond video analytics. It is a tool that can help city officials provide security to employees and citizens in a cost-effective way. Smart cameras place the power of AI deep learning at your fingertips, with object detection and tracking. The cameras detect only the objects you want, significantly reducing false alarms, conserving recording storage and enabling a more efficient monitoring solution. AI video surveillance allows operators to choose what to detect and where; users can set up multiple scenarios specific to their monitoring needs without complex calibration.

AI software processes video streams to detect and classify every object appearing in the detection zone. Deep learning engines perform object detection, automatically classifying the objects in the scene: people, cyclists, cars, buses and vans, trucks, motorcycles, bicycles and bags. AI categorizes moving objects and people, distinguishing them from environmental items such as spiders, shaking shadows and moving lights. The result is a reduction in false alarm rates, saving storage and enabling more efficient monitoring.

AI cameras combine multiple zones and virtual tripwires to create elaborate, multiple trigger point rules for a more accurate event detection level. AI analytics provides scalability and optimization of resources across a system. New analytics can be added to your sites, making your systems future-proof without infrastructure expansion.

Two of the most popular ways to apply artificial intelligence to physical security is through license plate recognition (ANPR) and vehicle recognition (MMCR — Make, Model, Color). ANPR IP camera uses the AI engine to detect and extract the numbers and letters in license plates, converting the pixels to usable digital data. Imagine using these tools to automatically capture a traffic offender and follow the vehicle as it crosses into the view of other cameras, based on the license plate number and physical characteristics of the vehicle.

While the debate regarding facial recognition continues, there are ways that cities can use this intelligent tool in smart and ethical ways. Like license plate and vehicle recognition, facial recognition can be used to grant access and capture incidents of unwanted activity.

For example, with the faces of city workers stored in a database, facial recognition systems can be used to grant secure access to buildings and facilities. Even if the city does not capture the faces of others, the system can recognize that a person is not in the database and a stranger alert can be automatically sent to security staff and law enforcement.

We have spoken about video AI in terms of cameras. Indeed, having these tools “at the edge” saves processing resources at the server. But what about all those existing cameras already installed in cities, buildings and businesses? There are AI appliances that add this intelligence to any connected stream and then supplies the intelligent streams to the servers.

Of course, VMS is the heart of any video surveillance system. You will want to make sure to choose a VMS that makes these tools easy to manage and use.

A smart video surveillance system can pay for itself after capturing the details of a single incident. While the use of intelligence can reduce the need for security staff, these tools provide security personnel with the ability to monitor more area and respond more quickly when incidents occur.

This article originally appeared in the September / October 2023 issue of Security Today.


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