Recently, IoT has developed to the extent that it can independently realize and analyze its surrounding environment and apply this knowledge in new environments [1-5]. The speed and accuracy of IoT in receiving and processing commands have improved rapidly because of developments in computer performance, internet networks, network
In this paper, we measure human physiological changes from different body parts to quantify human mental stress level by using multimodal bio-sensors. By integrating these physiological responses, we generate bio-index and rule for the prediction of mental status, such as tension, normal, and relax. We also develop an inspection service middleware for analyzing health parameters such as electroencephalography (EEG), electrocardiography (ECG), oxygen saturation (SpO2), blood pressure (BP), and respiration rate (RR). In this service middleware, we use the multi-level assessment model for mental stress level that consists of three steps as follows; classification, reasoning, and decision making. The classification of datasets from bio-sensors is enabled by fuzzy logic and SVM algorithm. The reasoning uses the decision-tree model and random forest algorithm to classify the mental stress level from the health parameters. Finally, we propose a prediction model to make a decision for the wellness contents by using Expectation Maximization (EM).
In this paper, we propose a new design scheme of N-Screen emulator based on Cloud and then implement the emulator, in order to solve the critical point of N-Screen emulator based on Cloud. This method, without the emulator in the server, will be able to confirm the features of the emulator with a browser using Web Service. This means that the identical service is possible without regard to personal computer or mobile environment. Also, in order to emulating each different web browser engine of the various devices separately, we revise and manage the WebKit engine to be suitable to the characteristics of each device. In the previous design method, the
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