As Smart Cities Expand, the Benefits of Modern Surveillance Come into Focus
Throughout the world, cities are getting smarter as connected devices become increasingly integral to a wide range of processes. Traffic management systems leverage real-time analyzation of video data to help keep people moving. Surveillance cameras help keep them protected and drive efficiencies of emergency first responders. IoT-enabled sensors are even capable of monitoring the structural health of buildings, critical infrastructure, and environmental conditions. These connected devices are designed to make our lives easier, safer, and more convenient, but they bring with them inevitable concerns about issues like privacy. Alleviating these concerns by fostering a more complete understanding of what today’s smart surveillance landscape actually looks like should be a top priority for both city officials and device manufacturers.
Modern Surveillance is Practical, Effective Facial recognition is a great example of a technology that would benefit from an open discussion of the ways it can be used to add value to society without causing harm, particularly as television and movies have given people a somewhat exaggerated impression of how modern surveillance techniques are actually used. In truth, technologies like facial recognition are becoming increasingly commonplace, and their uses are much more practical than Hollywood thrillers might lead you to believe.
Facial recognition is generally used to compare the faces of those it scans to existing databases. This makes it useful for security purposes because it can identify individuals known to be dangerous, or individuals banned from a specific location for a past offense. This is an automated process—there is no direct human involvement until the system flags a potentially dangerous person based on pre-determined conditions.
This helps make surveillance more reliable. Unlike humans, computers are immune to fatigue—which means fewer errors. A human being staring at one (or more) camera feeds can make mistakes even under ideal conditions, and studies have shown that the longer people look at video screens, the less efficient they are at monitoring them. Similarly, the longer we look at images, the less capable we are of identifying differences or patterns. By handing off this responsibility to today’s advanced analytics, we can greatly reduce the impact of operator fatigue. While a human will still need to be involved at some level, today’s surveillance tools can provide that human with crucial and objective context for what they are seeing, resulting in better, more accurate results.
