Security Robots Come to Take Some Jobs Away
A new type security robot that for some of us looks like R2D2. The robot called ” Knightscope K5“, the main purpose of it is doing surveillance. K5 has a broadcasting system and equipped with monitoring cams to check everything around itself.
A new type security robot that for some of us looks like R2D2. The robot called ” Knightscope K5“, the main purpose of it is doing surveillance. K5 has a broadcasting system and equipped with monitoring cams to check everything around itself. Instead of human guards robot never sleeps and listen and record everything. Even if it heard something, it could warn the security personnel about what happened. With its 360 degrees high-definition and low light, infrared cameras, the robot sends live images to a security network. The Robot also has a panic button, if you think, you are in danger and K5 is around you or you can find it. You can simply click the panic button to let the authorities know something wrong with the area you are currently on.
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Now, the robot has been used by several tech companies and one shopping mall in Silicon Valley. And the company who made K5 had much useful feedback for the usage of the robot. The startup currently rents each robot for 6,25$ per hour, it cost less than a security personnel, but the robot has no chance to defend itself. It is possible that someone try to push it or harm the device. So the Robot can’t defend itself, that is the reasonK5 is considered as a backup unit for the security personal.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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