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A reliable Electronic Voting Machine (EVM) is proposed and implemented in this study, which is integrated with a biometric fingerprint scanner to ensure a secure election process. This biometric EVM includes features such as an interactive user interface, hack-free design and master lock. The EVM system has the capability of registering user data and storing them in a database through proper authentication. Moreover, the system proposed lowers the requirement for human resources. This paper provides a detailed description of the systematic development of the hardware and software used. The software part includes algorithm development and implementation. A thorough and in-depth understanding of the data and the communication protocols along with the pathways used for storage of data in the devices is provided. Additionally, the cost of the system is 62.82% less than the officially existing EVM machines of India. Furthermore, this study seeks to demonstrate the benefits of such an approach from a technological and a social standpoint.

In this study, a systematic, low-cost, sensor-less solution for generating random alarm to distracted drivers/ nurses is proposed and designed to save them from accidents. A simple Finite State Machine (FSM) based algorithm is proposed for this work which has been implemented using an ATmega 328P – PU microcontroller. For testing the status of the driver/nurse, Linear Feedback Shift Register (LFSR) has been used to generate pseudo-random events at arbitrary intervals. In addition to this, a Register Transfer Level (RTL) diagram has also been investigated, and system output has been verified through Field Programmable Gate Arrays (FPGA) simulation. The prototype system has been deployed in a real-life environment by placing it in dashboard of a driver in a running vehicle or by putting the system on desk of a nurse on duty. The effective alertness of the driver and the nurse is found to be 76% and 87% respectively.

In this paper, a system for measuring the zone temperature profile of a horizontal tube furnace is proposed. This system consists of an ultrasonic transducer, quartz tube, resistive horizontal tube furnace, Arduino micro-controller and relevance vector machine (RVM)-based regression model. The ultrasonic transducer is placed in such a way that the acoustic wave is transmitted and then reflected back from the resistive horizontal tube furnace. The variations in the temperature values inside the tube furnace may affect the receiving voltage of the ultrasonic transducer. The RVM model is employed to predict the temperature using the inputs as the ultrasonic transducer voltage and the distance of the propagating path of the ultrasonic wave. The experimental results demonstrate that the proposed system is effective to measure the temperature inside a horizontal furnace and it shows a correlation coefficient value of 0.9695 with the K -type thermocouple readings. Such a system can be employed in an industrial furnace to measure the temperature with a higher accuracy.