RFID-Based Microwave Biosensor for Non-Contact Detection of Glucose Solution

Due to the increasing number of diabetic patients, early monitoring of glucose levels is particularly important; therefore, glucose biosensors have attracted enormous attention from researchers. In this paper, we propose a glucose microwave biosensor based on RFID and achieve a non-contact measurement of the concentration of glucose solutions. The Reader is a complementary split-ring resonator (CSRR), and the Tag is comprised of a squared spiral capacitor (SSC). A polydimethylsiloxane microfluidic quantitative cavity with a volume of 1.56 μL is integrated on the Tag to ensure that the glucose solution can be accurately set to the sensitive area and fully contacted with the electromagnetic flux. Because the SSC exhibits different capacitances when it contacts glucose solutions of different concentrations, changing the resonant frequency of the CSRR, we can use the relationship to characterize the biosensing response. Measurement results show that bare CSRR and RFID-based biosensors have achieved sensitivities of 0.31 MHz/mg·dL−1 and 10.27 kHz/mg·dL−1, and detection limits of 13.79 mg/dL and 1.19 mg/dL, respectively, and both realize a response time of less than 1 s. Linear regression analysis of the abovementioned biosensors showed an excellent linear relationship. The proposed design provides a feasible solution for microwave biosensors aiming for the non-contact measurement of glucose concentration.

An Automatic Measurement Method of Test Beam Response Based on Spliced Images

Information such as cracks and deflections is the important basis for structural safety. Existing methods have not achieved simultaneous detection. In most existing computer vision measurement systems, the view is fixed due to the fixed position of the camera. Thus, it is difficult to obtain the structures’ overall crack and deflection information. An automatic response measurement method is proposed in this study including ( 1 ) continuous image acquisition and signal transmission system based on self-walking bracket and Internet of Things (IoT), ( 2 ) an image splicing method based on feature matching, and ( 3 ) a crack and deflection measurement method. The self-walking bracket allows the industrial camera to move at a fixed distance to obtain the continuous image of the beam. Next, the spliced image is obtained through the PCA-SIFT method with a screening mechanism. The cracks’ information is acquired by the dual network model. The simplified AKAZE feature detection algorithm and the modified RANSAC are used to track the natural features of the structures. The curve fitting is performed to obtain the deflection curve of the beam under different loads. Experimental results show that the method can directly reflect the crack and deflection information of the beam. The average deviation of width is 11.76%, average deviation of length is 8.18%, and the average deformation deviation is 4.50%, which verifies the practicability of the method and shows great potential to apply it in actual structures.