How Machine Learning is Helping Us Strengthen Home Security
Lifestyle Robots are no longer the subjects of film or aspiration; they’re here and at the forefront of innovation in home security.
Robots are leveraging machine-learning techniques in security intrusion-detection robots. These, for the most part, consist of smaller mobile robots with cameras and movement-detection sensors, which move around a building or home looking for intrusion.
These robots are designed to detect anomalous behavior, such as someone walking through a building at night and reporting back to a remote security center. They can leverage up to four high definition cameras, sensors, a license-plate recognition camera, four microphones, a weather sensor for measuring barometric pressure, carbon dioxide levels, temperature, navigation equipment and electric motors — all packed into a dome-shaped body with a big rechargeable battery and a computer.
Wi-Fi is used to communicate with other robots and with people who can remotely monitor the cameras, microphones and other sources of data. These robots have a 24-hour battery and when running low, it seeks out its own charging pad. If you walk in front of it, it will stop abruptly. Try to stop it, and its built-in alarm will begin to chirp as a warning while sending a low-level alert to a remote monitoring center. If you are the one who needs help and a robot is nearby, you can press a button near the top of its head to call someone. Engineers and roboticists have truly thought a lot about building a tamperproof security guard for the home.
Understanding the risks
There is the risk of our robots being hacked, however. Therefore, additional measures need to be taken, such as implementing extra security authentication or perhaps facial recognition of the owner when opening panels. There is also a real risk of privacy invasion — especially in the case of a robot which has complete freedom to roam inside the house — so we must ensure that the surveillance footage is securely stored. Finally, there is also the possibility of software bugs. All software runs this risks but in the case of home security robots, it can often be a mission critical feature.
Going forward, companies will roll out even better contextual home automation/security service robots running machine-learning algorithms that are dynamically able to respond to various unexpected scenarios.