Apparently Aladdin now has more choices. All kidding aside, while it can't speak or fly, this MIT-developed tactile sensing mat has something (scientifically) magical about it.
Il MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) He developed un tappeto intelligente che può osservare, valutare e catalogare ogni tipo di posizione assunta quando ci si cammina o ci si siede sopra. Un passo avanti verso prodotti estremamente interessanti nel campo della smart home, dell’assistenza sanitaria remota e perchè no, dei videogiochi.
A carpet that assists us
Many of our daily activities involve physical contact with the ground: walk, exercise, rest. These integrated interactions contain a wealth of information that helps us better understand people's movements.
Precedenti ricerche hanno sfruttato l’uso di telecamere singole RGB (from the old Microsoft Kinect onwards), ma non solo. Sono state impiegate anche telecamere omnidirezionali indossabili , e perfino webcam (con tutti gli inevitabili problemi di privacy). Cos’ha questo progetto di diverso?
To deduce the 3D pose with the CSAIL team system, a person simply has to step onto the mat and perform any action. The neural network developed by the team determines what someone is doing just by using tactile information. She's sitting? He is walking? Is she lying down?
Domani ci dirà: sta facendo yoga bene o male? Ha un problema all’anca? Dorme nel modo giusto?
Imagine taking advantage of this model to enable a seamless health monitoring system. To detect falls, for example, or to monitor and assist with motor rehabilitation.Yiyue Luo, lead author of the study
The low-cost, scalable carpet was made with a pressure-sensitive film and conductive thread. It incorporates over nine thousand sensors that cover 10 square meters of carpet (a size larger than the average of any furniture carpet).
How does the tactile sensing mat work?
Each of the sensors on the carpet converts human pressure into an electrical signal, through physical contact between people's feet, limbs, torso and carpet. The system has been specifically trained on synchronized tactile and visual data, such as a video and the corresponding heat map of someone doing a pushup.
The model takes the pose extracted from the visual data, uses the tactile data as input, and finally shows the human pose in 3D.
Indeed, the carpet was able to predict the pose of a person with a margin of error of less than ten centimeters. For the classification of specific actions, then, even the system was accurate 97% of the time.
A coach mat
As mentioned, one of the possible applications is linked to the monitoring of physical activity. Imagine that the mat recognizes our activity, counts the number of repetitions we do (for example for push-ups) and also calculates the corresponding calories burned.
Current limits? The obvious ones: Since much of the pressure distributions on a mat are induced by lower body and torso movement, this information is currently more accurate than upper body data.
Future improvements? Se un tappeto può farlo con una sola persona, immaginate una superficie intera ricoperta da questi sensori. Una intera discoteca potrebbe rilevare lo stato di lucidità di tutti i suoi ospiti dalla coerenza dei loro movimenti. Una cosa come tante altre, l’unico limite è la fantasia.