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In these days, wearable devices have been developed for effectively measuring biological data. However, these devices have tissue allege and noise problem. To solve these problems, biometric measurement based on a non-contact method, such as face image sequencing is developed. This makes it possible to measure biometric data without any operation and side effects. However, it is impossible for a remote center to identify the person whose data are measured by the novel methods. In this paper, we propose the novel non-contact heart rate and blood pressure imaging system, Deep Health Eye. This system has authentication process at the same time as measuring bio signals, through non-contact method. In the future, this system can be convenient home bio signal monitoring system by combined with smart mirror. [ABSTRACT FROM AUTHOR]

Background: Drinking water has several advantages that have already been established, such as improving blood circulation, reducing acid in the stomach, etc. However, due to people not noticing the amount of water they consume every time they drink, most people drink less water than the recommended daily allowance.Objective: In this paper, a capacitive sensor for developing an automatic tumbler to measure water level is proposed. Different than in previous studies, the proposed capacitive sensor was separated into two sets: the main sensor for measuring the water level in the tumbler, and the reference sensor for measuring the incremental level unit.Methods: In order to confirm the feasibility of the proposed idea, and to optimize the shape of the sensor, a 3D model of the capacitive sensor with the tumbler was designed and subjected to Finite Element Analysis (FEA) simulation. According to the simulation results, the electrodes were made of copper and assembled in a tumbler manufactured by a 3D printer. The tumbler was filled with water and was subjected to experiments in order to assess the sensor's performance.Results: The comparison of experimental results to the simulation results shows that the measured capacitance value of the capacitive sensor changed linearly as the water level varied. This proves that the proposed sensor can accurately measure the water level in the tumbler. Additionally, by use of the curve fitting method, a compensation algorithm was found to match the actual level with the measured level.Conclusions: The experimental results proved that the proposed capacitive sensor is able to measure the actual water level in the tumbler accurately. A digital control part with micro-processor will be designed and fixed on the bottom of the tumbler for developing a smart tumbler. [ABSTRACT FROM AUTHOR]