AI News, Artificial intelligence senses people through walls
Artificial intelligence senses people through walls
X-ray vision has long seemed like a far-fetched sci-fi fantasy, but over the last decade a team led by Professor Dina Katabi from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has continually gotten us closer to seeing through walls.
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.
“We’ve seen that monitoring patients’ walking speed and ability to do basic activities on their own gives health care providers a window into their lives that they didn’t have before, which could be meaningful for a whole range of diseases,” says Katabi, who co-wrote a new paper about the project.
“A key advantage of our approach is that patients do not have to wear sensors or remember to charge their devices.” Besides health care, the team says that RF-Pose could also be used for new classes of video games where players move around the house, or even in search-and-rescue missions to help locate survivors.
A neural network trained to identify cats, for example, requires that people look at a big dataset of images and label each one as either “cat” or “not cat.” Radio signals, meanwhile, can’t be easily labeled by humans.
Since cameras can’t see through walls, the network was never explicitly trained on data from the other side of a wall – which is what made it particularly surprising to the MIT team that the network could generalize its knowledge to be able to handle through-wall movement.
AI detects movement through walls using wireless signals
The scientists mainly see their invention as useful for health care, where it could be used to track the development of diseases like multiple sclerosis and Parkinson's.
And since the technology is 83 percent reliable for identifying people in large groups (as many as 100 people), it could be helpful for search-and-rescue operations where it's important to know who you're looking for.
MIT Device Uses Wi-Fi to ‘See’ Through Walls and Track Your Movements
Anyone who has ever been intrigued by ads for x-ray specs in the back of a comic book will appreciate the latest work out of MIT, which advances technology to “see” through walls.
Using WiFi, a team at Computer Science and Artificial Intelligence Laboratory (CSAIL) is now able to “see” a person on the other side of a wall and precisely track their movements, even if it’s something as subtle as giving a high five, according to new research to be presented at the Conference on Computer Vision and Pattern Recognition next week.
Now, they say they’ve been able to train a neural network to interpret the way radio WiFi signals bounce off a person’s body and translate it into the movement of 14 different key points on the body, including the head, elbows, and knees.
A data set to train the AI didn’t already exist, so the team had to make one by manually creating stick figures of human movements based on images they captured through both the wireless device and a camera.
They’ve been working with experts in the treatment of each of those diseases, where being able to monitor a patient’s daily movements and gait with precision would provide doctors a wealth of information they can’t get from a half hour check up.
New technology can see your body through walls
MIT’s Computer Science and Artificial Intelligence Laboratory has created a system that can see your body through walls, recreating your poses when you walk, sit, or simply stand still.
From the release: 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.
The team says that the system could be used to monitor diseases like Parkinson’s and multiple sclerosis (MS), 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.
- On Friday, January 18, 2019
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