Sound Sensitivity Diagnosis System Based Cognitive Internet of Things and Cloud Computing

Abstract

Cognitive IoT is the next step in enhancing the efficiency and performance of complicated sensor-driven systems throughout learning human experience into the materials and circumstances that interact with. This paper introduces a system to diagnose the sensitivity toward sound by improving a mechanism based on facial emotions recognition system that combines with IoT protocols and cloud computing. The proposed system has been performed by incorporation of a cognitive IoT environment consisted of hardware and software components with a cloud. This system has been implemented in a laboratory to recognise the behaviour of people suffering from sensitivity to sound. This behaviour has been adopted by monitoring human face emotions through a live video capturing using camera and image processing using facial emotion recognition software. Emotions values obtained was examined and collected in a cloud using the MQTT protocol. These emotions have been categorised as normal and abnormal. Finally, several cases have been tested using this system, and five levels for sound sensitivity has been adopted. Sound intensity values ranged from 10−12 W/m2 up to 10−4W/m2.