IIIT Hyderabad Publications |
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Analysis and Calibration techniques towards the development of PoF based pressure sensing CarpetAuthor: VRUSHALI ARUTE Date: 2022-03-31 Report no: IIIT/TH/2022/28 Advisor:Azeemuddin Syed AbstractPlastic optical fibres (POF) can be made sensitive to various parameters. Therefore, a implementation of tomographic imaging based on POF sensors is a good application in pressure sensing domain. The system uses photons to transmit information along the sensor and deliver a signal at a detector of the sensor, this Photonic Guided Path Tomography (PGPT) is used to design carpet. It is found that the POF based pressure sensing platform has several limitations such as photodiode output voltage variations, difference in the sensor response for horizontal and vertical fiber and acquiring data at unexpected intervals. Optical pressure sensors also suffer from the drawback of instability due to LED, photodiode, POF, or all. These limitations can lead to incorrect estimation of output voltage. Stabilization of output voltage is an essential factor to be taken into consideration. To remove such limitations and improve pressure imaging of floor sensor carpet for clear contrast is a big challenge in the optoelectronics systems. To surpass the above limitations, we have developed time based calibration using time windowing technique to reduce the standard deviation of photodiode output voltage variations by 98%. We have also described space and weight calibration techniques based on the convex and concave shape of fiber bend. These techniques help in improving the Landweber image reconstruction algorithm to obtain significant clarity and improvement in object pressure images. The major work demonstrates time, space and weight based calibration techniques for pressure monitoring in the low-cost plastic optical fiber (POF) sensor carpet. The proposed work also reports an artificial intelligence (AI) based algorithm to determine the accuracy of positioning of the load. Experimental results demonstrate that this algorithm gives a mean square error of 0.875 cm in position detection on the carpet. The proposed work also done using IoT application, to get real time data in remote sensing. Here, Message Queuing Telemetry Transport (MQTT) and ThingSpeak server used for communication. The images constructed using wired communication and remote sensing are almost similar in terms of quality and information. The work discusses the potential for a compact and cost-effective pressure sensor carpet, which integrates with the living environment and the outside world. Full thesis: pdf Centre for VLSI and Embeded Systems Technology |
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