EEG and IOT based indoor atmosphere control system

The EEG signal is a signal that is generated equally by users with physical discomfort, and is in the spotlight as a next generation interface. In this paper, we propose an IoT system that controls the indoor environment that supports emotional and logical information processing using the user’s EEG signal. The proposed system consists of an EEG measuring device, EEG simulation software, and indoor environment control device. As experimental data, EEG signal data for emotional information processing generated in a comfortable state and EEG signal data for logical information processing generated during concentration are used. From the measured signal, the ICA algorithm is applied to remove noise and extract only the beta wave. After that, the learning and testing process through the SVM is performed. The subject showed an average accuracy of 82.69% as a result of training to improve the accuracy of the EEG signal through the EEG simulation software. The EEG signal input from the EEG measuring device is transmitted to the EEG simulation software through serial communication, and a control command is generated by classifying emotional information processing and logical information processing. The generated control command is then transmitted to the indoor environment control device through Zigbee communication, and in case of emotional information processing, soft lighting and classical music are output. In case of logical information processing, bright lighting and white noise for learning are output. The proposed system can be applied to BCI-based software and device control, enabling users with discomfort to overcome their physical limitations.