ORCID Profile
0000-0002-6256-7470
Current Organisations
Symbiosis International University
,
Agency for Science, Technology and Research
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Publisher: MDPI AG
Date: 22-09-2020
DOI: 10.3390/S20185448
Abstract: Air pollution has been a looming issue of the 21st century that has also significantly impacted the surrounding environment and societal health. Recently, previous studies have conducted extensive research on air pollution and air quality monitoring. Despite this, the fields of air pollution and air quality monitoring remain plagued with unsolved problems. In this study, the Pollution Weather Prediction System (PWP) is proposed to perform air pollution prediction for outdoor sites for various pollution parameters. In the presented research work, we introduced a PWP system configured with pollution-sensing units, such as SDS021, MQ07-CO, NO2-B43F, and Aeroqual Ozone (O3). These sensing units were utilized to collect and measure various pollutant levels, such as PM2.5, PM10, CO, NO2, and O3, for 90 days at Symbiosis International University, Pune, Maharashtra, India. The data collection was carried out between the duration of December 2019 to February 2020 during the winter. The investigation results validate the success of the presented PWP system. In the conducted experiments, linear regression and artificial neural network (ANN)-based AQI (air quality index) predictions were performed. Furthermore, the presented study also found that the customized linear regression methodology outperformed other machine-learning methods, such as linear, ridge, Lasso, Bayes, Huber, Lars, Lasso-lars, stochastic gradient descent (SGD), and ElasticNet regression methodologies, and the customized ANN regression methodology used in the conducted experiments. The overall AQI values of the air pollutants were calculated based on the summation of the AQI values of all the presented air pollutants. In the end, the web and mobile interfaces were developed to display air pollution prediction values of a variety of air pollutants.
Publisher: Elsevier BV
Date: 2020
Publisher: Springer Nature Singapore
Date: 03-07-2022
Publisher: Informa UK Limited
Date: 16-06-2020
Publisher: Emerald
Date: 31-08-2020
DOI: 10.1108/IJPCC-07-2020-0091
Abstract: The purpose of the presented IoT based sensor-fusion assistive technology for COVID-19 disinfection termed as “Smart epidemic tunnel” is to protect an in idual using an automatic sanitizer spray system equipped with a sanitizer sensing unit based on in idual using an automatic sanitizer spray system equipped with a sanitizer sensing unit based on human motion detection. The presented research work discusses a smart epidemic tunnel that can assist an in idual in immediate disinfection from COVID-19 infections. The authors have presented a sensor-fusion-based automatic sanitizer tunnel that detects a human using an ultrasonic sensor from the height of 1.5 feet and disinfects him/her using the spread of a sanitizer spray. The presented smart tunnel operates using a solar cell during the day time and switched to a solar power-bank power mode during night timings using a light-dependent register sensing unit. The investigation results validate the performance evaluation of the presented smart epidemic tunnel mechanism. The presented smart tunnel can prevent or disinfect an outsider who is entering a particular building or a premise from COVID-19 infection possibilities. Furthermore, it has also been observed that the presented sensor-fusion-based mechanism can disinfect a person in a time of span of just 10 s. The presented smart epidemic tunnel is embedded with an intelligent sanitizer sensing unit which stores the essential information in a cloud platform such as Google Fire-base. Thus, the proposed system favours society by saving time and helps in lowering the spread of coronavirus. It also provides daily, weekly and monthly reports of the counts of in iduals, along with in-out timest s and power usage reports. The presented system has been designed and developed after the lock-down period to disinfect an in idual from the possibility of COVID-19 infections. The presented smart epidemic tunnel reduced the possibility by disinfecting an outside in idual/COVID-19 suspect from spreading the COVID-19 infections in a particular building or a premise. The presented system is an original work done by all the authors which have been installed at the Symbiosis Institute of Technology premise and have undergone rigorous experimentation and testing by the authors and end-users.
Publisher: Wiley
Date: 22-03-2018
Abstract: The implementation of water splitting systems, powered by sustainable energy resources, appears to be an attractive strategy for producing high-purity H
Publisher: American Association for the Advancement of Science (AAAS)
Date: 04-2016
Abstract: Doping of graphene with nitrogen imparted bifunctional electrocatalytic activities for efficient energy conversion and storage.
No related grants have been discovered for Anirban Sur.