A5004320394- Air Quality Monitoring and Forecasting
- Vehicle emissions and performance
- Air Quality and Health Impacts
- Atmospheric chemistry and aerosols
- Energy Load and Power Forecasting
- Hydrological Forecasting Using AI
- Sleep and Work-Related Fatigue
- Odor and Emission Control Technologies
- COVID-19 impact on air quality
- Atmospheric aerosols and clouds
- EEG and Brain-Computer Interfaces
- Extremum Seeking Control Systems
- Non-Invasive Vital Sign Monitoring
- Advanced Control Systems Design
- Wind and Air Flow Studies
- Advanced Chemical Sensor Technologies
- Environmental Policies and Emissions
- Fractional Differential Equations Solutions
- Target Tracking and Data Fusion in Sensor Networks
- Fire Detection and Safety Systems
University of Technology Sydney
2013-2023
National Institute of Technology Durgapur
2023
North Bengal Agricultural University
2023
Ton Duc Thang University
2020-2022
Multisensor fusion of air pollutant data in smart buildings remains an important input to address the well-being and comfort perceived by their inhabitants. An integrated sensing system is part a building where real-time indoor quality are monitored round clock using sensors operating Internet-of-Things (IoT) environment. In this work, we propose management merging index (IAQI) humidex into enhanced (EIAQI) sensor on basis. Here, levels measured network waspmote while IAQI fused together...
This paper presents the development of high-performance wireless sensor networks for local monitoring air pollution. The proposed system, enabled by Internet Things (IoT), is based on low-cost sensors collocated in a redundant configuration collecting and transferring quality data. Reliability accuracy system are enhanced using extended fractional-order Kalman filtering (EFKF) data assimilation recovery missing information. Its effectiveness verified through particulate matters at suburban...
Abstract Background Rate models for predicting vehicular emissions of nitrogen oxides (NO X ) are insensitive to the vehicle modes operation, such as cruise, acceleration, deceleration and idle, because these usually based on average trip speed. This study demonstrates feasibility using other variables speed, load, power ambient temperature predict ensure that emission inventory is accurate hence air quality modelling management plans designed implemented appropriately. Methods We propose...
It is essential to maintain air-quality standards and take necessary measures when air-pollutant concentrations exceed permissible limits. Pollutants such as ground-level ozone (O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> ), nitrogen oxides (NOX), volatile organic compounds (VOCs) emitted from various sources can be estimated at a particular location through integration of observation data obtained measurement sites effective...
Models for predicting vehicular emissions of carbon dioxide (CO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> ) are usually insensitive to vehicle modes operation (such as cruise, acceleration, deceleration, and idling) they based on the average speed motor vehicles. In present study, real world on-road second-by-second data used improve accuracy air quality models by considering modal CO in terms vehicles' instantaneous acceleration....
The primary factors contributing to road accidents are drowsiness and fatigue. Additionally, it diminishes productivity within work environments elevates the likelihood of accidents. analysis bio-signals is crucial in examination various physical conditions physiological state an individual. Various biological signals were utilized identify presence fatigue that associated with employed driver or operator drowsiness. Out all these non-invasive signals, electrooculogram (EOG) exhibits...
Emissions from power plants constitute a major part of air pollution and should be adequately estimated. In this paper, we consider the problem estimating nitrogen dioxide (NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">X</sub> ) emission by developing an inverse method to integrate satellite observations atmospheric pollutant column concentrations with species direct sensitivities predicted regional quality model, in order discern biases...
This paper addresses the problem of air pollutant profile estimation by using measurements collected from different weather stations. An algorithm is developed, based on an Extended Kalman Filter to handle missing temporal data and statistical Kriging method interpolate spatial data. Combination extended filtering with Matérn covariance function has proven be useful in exploiting meteorological information build reliable quality models. We have applied developed estimate profiles Sydney...
It is essential to maintain air quality standards and inform people when pollutant concentrations exceed permissible limits. For example, ground-level ozone, a harmful gas formed by NO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</inf> VOCs emitted from various sources, can be estimated through integration of observation data obtained measurement sites effective air-quality models. This paper addresses the problem predicting pollution...
Predicting Carbon Monoxide Emissions with Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Networks (ANNs) Seth Daniel Oduro, Santanu Metia, Hiep Duc, Quang P. Ha Pages 1-9 (2015 Proceedings of the 32nd ISARC, Oulu, Finland, ISBN 978-951-758-597-2, ISSN 2413-5844) Abstract: from motor vehicles need to be predicted ensure appropriate air quality plans. Two most popular techniques for emission data collection are on-board measurement dynamometer testing. This research work...
Prediction of NOx Vehicular Emissions Using On-Board Measurement and Chassis Dynamometer Testing S. D. Oduro, Metia, H. Duc, G. Hong, Q. P. Ha Pages 584-591 (2014 Proceedings the 31st ISARC, Sydney, Australia, ISBN 978-0-646-59711-9, ISSN 2413-5844) Abstract: Motor vehicles' rate models for predicting emissions oxides nitrogen (NOX) are insensitive to their modes operation such as cruise, acceleration, deceleration idle, because these usually based on average trip speed. This study...
An intelligent air quality monitoring system (IAQMS) is one of the key aspects any smart city. The success these systems largely depends on data. Missing data crucial issues in IAQMS, especially small cities where sufficient historical not available. In this study, a fuzzy transfer learning-based imputation (FTLI) method proposed for missing central concept to acquire knowledge through inference from other called source domains Later that applied impute values target IAQMS (target domain)...
The paper is divided into three parts. first part gives a brief introduction to the overall paper, fractional order PID (PIλDμ) controllers and Genetic Algorithm (GA). In second part, it has been studied how performance of an integer controller deteriorates when implemented with lossy capacitors in its analog realization. Thereafter shown that can be effectively modeled by terms. Then, novel GA based method proposed tune parameters such original retained even though realized same capacitors....