Conference Papers

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    Experimental study on linear displacement measurement sensor using RGB color variation technique with PID controller
    (Institute of Electrical and Electronics Engineers Inc., 2017) Murthy, A.; Rao, S.S.; Herbert, M.A.; Karanth P, P.
    This study is based on experimental approach to linear displacement measurement using RGB color coding algorithm. This system is based on the auto-calibration procedure which can be implemented in a circuit, based on the temporal changes in the intensity of light, with the help of a light dependent resistor (LDR). The system consists of two LDRs and an LED placed on one side and an RGB color coded reflective paper on the opposite side. PIC microcontroller is used for powering the LED, processing of data for feedback control and to display the output on an LCD. LDR1 reading is used for displaying the relative linear distance, by mapping the voltage as a function of distance. This reading is used as a feedback to a PID controller to correct for the deviation in the measurement. Extensive experimental observations are conducted to analyze the reliability of the results in accordance to the wavelength of light reflected, the signal voltage and power output of the system. Investigation of the optimum positioning of the LED and the reflective RGB color coded paper is performed by repeatability analysis and hysteresis effects. Furthermore, the efficiency of the system is increased by implementing a PID controller upon investigating the different controller design, viz. P, PI and PID. A high resolution of 0.1 [mm] is obtained for such a simple and economical system, thereby making it highly efficient, in both minute measurements as well as over the entire bandwidth range of the visible light spectrum. © 2017 IEEE.
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    Smart Cane for Assisting Visually Impaired People
    (Institute of Electrical and Electronics Engineers Inc., 2019) Nandini, A.V.; Dwivedi, A.; Kumar, N.A.; Ashwin, T.S.; Vishnuvardhan, V.; Guddeti, R.M.R.
    Blindness disables a person from self-navigating outside well-known environments. It affects their ability to perform several jobs, duties, and activities. They are dependent on external assistance which can be provided by humans, dogs or special electronic devices for better decision making. This motivated us to create a prototype called 'Smart cane for assisting visually impaired people' to overcome the problems they face in their daily life. Our device is a low cost and lightweight system that processes signals and alerts the visually impaired over any obstacle, potholes or water puddles through different beeping patterns. It senses the light intensity of the environment and illuminates the LED accordingly. These are accomplished by incorporating two ultrasonic sensors, a moisture sensor and a LDR sensor along with an Arduino Nano micro-controller. These are placed at specific positions of the cane for efficient guidance. Moreover, a GSM module is also added to the system so that the visually impaired person can send a message to the emergency contact number in case of distress. The developed model showed 89 percent accuracy and 80 percent of the users were satisfied with the developed prototype. © 2019 IEEE.
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    A Shadow Based Low-Cost Hand Movement Recognition System for Human Computer Interaction
    (Institute of Electrical and Electronics Engineers Inc., 2021) Geetha, V.; Salvi, S.; Sahoo, P.; Dodiya, M.; Gupta, S.
    TIn this paper, we propose and implement a real-time hand motion detection system which uses shadows projected by hand and detected by low cost Light Dependent Resistor (LDR). The main advantage of the shadow approach is real-time recognition and its application in Post COVID 19 world where contactless interactions are required. Our proposed approach uses 2D hand motion shadows to determine sequence of light blocking the LDRs and thus making the system less complex and less compute intensive compared to 3D image recognition based systems. The accuracy of the proposed system is tested under various lighting conditions and 82-95\% accuracy is observed under normal lighting conditions. © 2021 IEEE.