Prerit Saxena

Work place: Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India



Research Interests: Requirements Analysis, Data Structures and Algorithms, Analysis of Algorithms, Mathematical Analysis, Numerical Analysis, Comparative Programming Language Analysis


Prerit Saxena is an alumni of Dr. B.R Ambedkar National Institute of Technology Jalandhar. He has completed his Bachelors of Technology in Instrumentation and Control Engineering in the year 2014. During his graduation, he has actively been involved in the research in innovative technologies, smart sensors and sensor data analysis.

After graduation, he has been working in the field of data analysis and is currently employed as an analyst by one of the leading consulting firms in pharmaceutical domain. In future, he plans to explore the field of analytics and data science. Prerit has a publication on a traffic light system using data from piezoelectric sensors.

Author Articles
Real-Time Fuel Quality Monitoring System for Smart Vehicles

By Prerit Saxena Roop Pahuja Manmeet Singh Khurana Sumrit Satija

DOI:, Pub. Date: 8 Nov. 2016

A novel method of monitoring the quality i.e. the percentage of purity of diesel fuel in real-time environment in smart vehicles is presented here. The method incorporates temperature compensated density measurement using a dual load cell and temperature sensor. The mass of the small fixed volume of diesel sample and temperature of diesel are measured by the pre-calibrated load cell based amplifier set up and a smart miniature temperature sensor respectively. The amplified voltage of the load cell provides the measure of the density of the fuel. Further, the measured value of fuel density is temperature compensated and compared with standard reference values to indicate percentage of purity of the diesel sample. The method is automated with an intelligent virtual instrument that provides all the means of testing the fuel sample and displaying results with high level of accuracy ~ 99.8 %. The model offers a way of providing vital real time information to user and has great future prospects. Also, the data collected can be analyzed for developing complex mathematical models to suggest optimized driving parameters for vehicles.

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