The creepy RF-Pose system developed by MIT's CSAIL can track a person through walls or identify one specific person out of a group of 100 people. Credit: Jason Dorfman/MIT CSAIL MIT has created a system likened to X-ray vision, but the AI can track a person through walls — or identify one specific person out of a group of 100 people — by using wireless signals. MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) calls it RF-Pose.Yeah, that’s not creepy at all. How could they ignore the blaring red alert of potential privacy and spying issues and continue to develop artificial intelligence (AI) that can monitor a person’s movements through a solid wall using wireless radio waves? Apparently for its potential use in healthcare.According to MIT News:The team says that RF-Pose could be used to monitor diseases like Parkinson’s, multiple sclerosis (MS), and muscular dystrophy, providing a better understanding of disease progression and allowing doctors to adjust medications accordingly. It could also help elderly people live more independently, while providing the added security of monitoring for falls, injuries and changes in activity patterns. The team is currently working with doctors to explore RF-Pose’s applications in health care.The research paper, “Through-Wall Human Pose Estimation Using Radio Signals” (pdf) calls RF-Pose “a solution that leverages radio signals to accurately track the 2D human pose through walls and obstructions.” As pointed out on MIT News:Besides sensing movement, the authors also showed that they could use wireless signals to accurately identify somebody 83 percent of the time out of a line-up of 100 individuals. This ability could be particularly useful for the application of search-and-rescue operations, when it may be helpful to know the identity of specific people.Other potential uses cited include using RF-Pose “for new classes of video games where players move around the house, or even in search-and-rescue missions to help locate survivors.” The system counted on the fact that wireless signals in Wi-Fi frequencies are not stopped by solid walls and can reflect off a person’s body. The team used AI “to teach wireless devices to sense people’s postures and movement, even from the other side of a wall. The researchers use a neural network to analyze radio signals that bounce off people’s bodies and can then create a dynamic stick figure that walks, stops, sits, and moves its limbs as the person performs those actions.”You can see it in action in the video below. Future plans for RF-PoseThe CSAIL minds behind RF-Pose are currently working on 3-D output instead of the current 2-D stick figure output. 3D could show “even smaller micromovements,” such as seeing “if an older person’s hands are shaking regularly enough that they may want to get a check-up.” They see it as a plus that patients would not be required to wear sensors or to charge devices.Down the road at some point, CSAIL plans to develop a “consent mechanism” as a technical countermeasure to block surveillance. It would involve a person doing “a specific set of movements in order for it to being to monitor the environment.” Related content news Dow Jones watchlist of high-risk businesses, people found on unsecured database A Dow Jones watchlist of 2.4 million at-risk businesses, politicians, and individuals was left unprotected on public cloud server. By Ms. Smith Feb 28, 2019 4 mins Data Breach Hacking Security news Ransomware attacks hit Florida ISP, Australian cardiology group Ransomware attacks might be on the decline, but that doesn't mean we don't have new victims. A Florida ISP and an Australian cardiology group were hit recently. By Ms. Smith Feb 27, 2019 4 mins Ransomware Security news Bare-metal cloud servers vulnerable to Cloudborne flaw Researchers warn that firmware backdoors planted on bare-metal cloud servers could later be exploited to brick a different customer’s server, to steal their data, or for ransomware attacks. By Ms. Smith Feb 26, 2019 3 mins Cloud Computing Security news Meet the man-in-the-room attack: Hackers can invisibly eavesdrop on Bigscreen VR users Flaws in Bigscreen could allow 'invisible Peeping Tom' hackers to eavesdrop on Bigscreen VR users, to discreetly deliver malware payloads, to completely control victims' computers and even to start a worm infection spreading through VR By Ms. Smith Feb 21, 2019 4 mins Hacking Vulnerabilities Security Podcasts Videos Resources Events SUBSCRIBE TO OUR NEWSLETTER From our editors straight to your inbox Get started by entering your email address below. Please enter a valid email address Subscribe