Sound waves bypass visual limitations to recognize human activity  May 28, 2019 For human activity recognition (HAR) one or a few ultrasonic sensors are used to receive signals, which require many feature quantities of extraction from the received data to improve recognition accuracy. An international team of researchers (China, Japan) has developed a device based on a two-dimensional acoustic array and convolutional neural networks which uses a single feature quantity to characterize the sound of human activities and identify them. They tested their approach using a two-dimensional acoustic array with 256 receivers and four ultrasonic transmitters to gather data related to four different human activities—sitting, standing, walking and […]