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Companies often turn to robots to make workplaces safer by distancing workers from dangerous tasks. That can do a lot of good, but it just scratches the surface of robots’ potential for safety. Dedicated security robots could help protect people and property more efficiently than ever before.
Security robotics is a relatively new field, but it’s already shown impressive growth. More than 40% of non-manufacturing companies say they plan to implement robots in their security, making security robotics a $2.8 billion industry by 2023.
Much of this growth is recent, and the field could advance even faster thanks to new technologies. Here are five recent innovations that show potential in security robotics.
One of the most important new technologies for security robotics is real-time video analytics. Early security robots either sent live video feeds to remote operators or recorded video data for future use. Advances in machine learning let robots recognize objects and movements in real-time, letting them react independently to their situation.
For example, some new security robots can recognize and scan license plates. These bots can patrol parking lots and garages to compare these plates with police reports, finding wanted suspects’ vehicles or stolen cars. Considering how more than 700,000 drivers fall victim to car theft each year, this functionality could yield impressive results.
In other scenarios, real-time analytics could help security robots identify potentially suspicious situations. They could read people’s movements to detect a potential robbery or other crime and alert human security workers. Alternatively, they could analyze thermal video data to highlight feverish people for COVID-19 prevention.
Of course, video feeds aren’t the only sensory tool today’s security robots have at their disposal. One of the most innovative new features is MAC address recognition. These tools let security robots scan local networks to check devices’ MAC addresses, which are unique digital signatures that identify phones and computers.
Registering MAC addresses can help gauge how many people may be in an area. That data could inform contact tracing procedures for disease prevention and response. It could also help look for suspects in a crowd if police have tied a crime to a specific device.
MAC address recognition could also help detect and stop cybercrime in public places. Network monitoring tools could alert security robots when a device on the network is trying to break into prohibited systems or carry out other illegal acts. Security bots could then search for that device to find the cybercriminal responsible.
One aspect of security robots that may go overlooked is their power source. Lithium-ion batteries are the standard, but these have several complications. While the lithium batteries in cars can last for 250 miles between charges, the ones in robots – especially drones – are far smaller, which limits operation times.
Graphene batteries can help security robots operate for far longer between charges, making them more useful. These batteries can retain 80% of their capacity through 1,400 charging cycles, charge faster than traditional alternatives, last longer, and operate at extreme temperatures. As a result, security robots could become more versatile, appealing to more markets.
Facilities could let bots operate for longer shifts, covering more ground before they have to charge. They could also equip them with more features without fear of draining their battery life prematurely. These benefits are particularly valuable for drones, which now suffer from short flight times and limited weight capacity.
Machine vision is at the heart of many security robots. As impressive as today’s machine vision is, it can only be as effective as the cameras that provide data.
Hyper-spectral (HS) cameras are one of the most promising innovations in this field. These cameras can collect the full color spectrum of a scene, making it easier for machine vision to work.
Most cameras in machine vision processes today only collect red, green, and blue wavelengths. While this doesn’t make a substantial difference to the naked human eye, it limits object recognition in machines. Providing the entire color spectrum could let security robots see the world in more detail, enabling faster and more accurate image recognition.
HS cameras have already seen adoption in recycling and food processing plants with impressive results. Bringing the same technology to security robots could help them detect threats or people in need faster than even a human security guard.
Today’s security robots have more senses than just vision, too. Researchers are working on improving how they hear as well. Machine learning-powered sound recognition works like machine vision but helps robots detect and recognize audio signals like gunshots, breaking glass, alarms, or screams.
New sound recognition algorithms use a library of more than six million audio files, with similar sounds clustered into groups. This organization enables robots to register what type of sound they’ve heard, then narrow it down to possible sources. They can then provide a more accurate alert to security personnel and other people in the area.
Machines may be better at determining where sound waves come from, too. With this functionality, security robots could coordinate emergency response efforts faster and more accurately. Alternatively, they could move closer to the source to gain more information or manage the situation themselves.
Despite these innovations, there are still some roadblocks facing security robotics at the moment. Most notably, many of these technologies raise ethical questions about data security and surveillance.
Human security workers monitor crowds all the time, but when a robot does it, it records what it sees. Some people may feel like this is a breach of privacy, especially if they don’t know that robots are recording them. Collecting and storing this data also subjects it to potential theft and abuse from cybercriminals.
If someone hacked into a security robot or its database, they could spy on people without their knowledge. They could also use this data for more sophisticated cyberattacks, such as using facial recognition data to break biometric security.
Robotics engineers must consider these issues as they pursue more advanced security robotics. Security features like advanced encryption and controls that stop robots from storing video data can assuage some of these concerns. Businesses and local governments will also have to think about how they use and publicize robots to balance safety and privacy.
While some obstacles remain, the future of security robotics looks bright. Several new technologies make these machines more reliable and versatile than ever before. As these innovations become standard, security robot adoption will rise, and the world could become a safer place.
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