Ultrasounds-based Context Sensing Method and Applications over the Internet of Things

Nowadays Internet of Things (IoT) devices can collect a large amount of data and infer the context they are operating in. One of the most pervasive IoT device is the smartphone. Among the plethora of sensors that such device has, microphone is probably the most versatile. It can be used to infer information about the context by acquiring the environmental sound. In this paper we propose an active ultrasonic-based method able to sense context information. The approach is based on the emission of periodic ultrasonic impulses, called pings, whose echoes are continuously acquired to extract a proper set of features. Using a classifier the context information is then retrieved. Two applications are presented: i) an Indoor/Outdoor Detector (IOD), and ii) an Earphone Wearing State Detector (EWSD). In both cases a smartphone is the employed device. The former senses if the smartphone is in an indoor or outdoor environment while the latter detects if a user is wearing or not his earphones. The obtained results are encouraging for both the solutions that have been stressed in different working conditions and employed within proper application frameworks