Cognitive Internet of Things (CIoT) is the next leap towards enhancing the accuracy and effectiveness of Internet of Things (IoT) technology used in combination with cognitive computing that has a significant role in healthcare and diseases diagnosis. The work in this paper proposes a system to diagnose the sensitivity toward sound and light by developing a mechanism based on facial emotions recognition system that integrate with IoT protocols and cloud computing. The proposed system was achieved by establishing a cognitive IoT environment composed of hardware and software components that practically implemented in a laboratory to identify the behavior of people suffering from sensitivity toward sound and light. This behavior was observed 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 (MQTT) protocol. These emotions were classified as normal and abnormal. Normal state give the impression that the surrounding environment is appropriate for people senses and they do not suffer from any discomfort, therefore the system works on a mechanism to increase the intensities of sound or light in this environment and vice versa.
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