A5018803314- Air Quality Monitoring and Forecasting
- Air Quality and Health Impacts
- Nuclear Physics and Applications
- Nuclear reactor physics and engineering
- Magnetic confinement fusion research
- Vehicle emissions and performance
- Data Stream Mining Techniques
- Atmospheric chemistry and aerosols
- Nuclear Materials and Properties
- Advanced Chemical Sensor Technologies
- Fusion materials and technologies
- Laser-Plasma Interactions and Diagnostics
- Distributed and Parallel Computing Systems
- COVID-19 impact on air quality
- Atmospheric aerosols and clouds
- Gas Sensing Nanomaterials and Sensors
- Particle Detector Development and Performance
- Advanced Statistical Process Monitoring
- Nuclear Issues and Defense
- Nuclear and radioactivity studies
- Water Quality Monitoring and Analysis
- Astro and Planetary Science
- Petroleum Processing and Analysis
- Climate Change and Health Impacts
- Catalytic Processes in Materials Science
National Agency for New Technologies, Energy and Sustainable Economic Development
2017-2024
University of Salerno
2020-2024
Sensors (United States)
2022
Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di Frascati
2019
A pervasive assessment of air quality in an urban or mobile scenario is paramount for personal city-wide exposure reduction action design and implementation. The capability to deploy a high-resolution hybrid network regulatory grade low-cost fixed devices primary enabler the development such knowledge, both as source information validating predictive models. real-time cumulative monitoring also considered driver exposome future medicine approaches. Leveraging on chemical sensing, machine...
Scalable and effective calibration is a fundamental requirement for low-cost air quality (AQ) monitoring systems will enable accurate pervasive in cities. Suffering from environmental interferences fabrication variance, these devices need to encompass sensor-specific complex processes reaching sufficient accuracy be deployed as indicative measurement AQ networks. Concept sensor drift often force the process frequently repeated. These issues lead unbearable costs, which denies their massive...
Low-Cost Air Quality Monitoring Systems (LCAQMS) and Machine Learning techniques are enabling a new paradigm in Networks. Nevertheless, compliance with Data Objective (DQO) is still an open point. The assessment of various calibration models proposed literature has ever neglected the Concept Drift, i.e. differences data distributions associated input target variables streaming coming from dynamic nonstationary environments. influence concept drift investigated on maintenance (calibrated)...
There is an increasing scientific interest in studying vehicular traffic pollution road tunnels. This due both to the evaluating effect that different polluting gases can have on driving style of motorists and also hypothesis tunnels could be considered as closed systems which traffic–pollution correlation easier study because it more easily separated from other effects. In this work, a system low-cost IoT sensor nodes for detection carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3),...
COVID19 Pandemic impacts have been associated with Air Quality (AQ) its mortality index being significantly affected by high pollution levels. Significant mobility limitations contributed to slow down the pandemic in Italy having as a side effect definite decrease of Phase 2 while easing those limits still see significant reduction commuting and schools related car traffic emissions. High resolution AQ monitoring can now allow obtain picture if smart cities will be capable reach long sought...
The last decade has seen a significant growth in low-cost air quality monitoring systems (LCAQMS) adoption, mostly driven by the spatial density limitations of traditional regulatory grade networks which restrict their effectiveness several settings. EU's framework advise for deploying one unit per roughly 170,000 people or 15 square kilometers is insufficient capturing high spatio-temporal variance complex urban scenarios. Often these settings are characterized distributed...
Field calibration is recognized as the best performing approach for operational deployment of low cost air quality sensors. In this approach, each individual sensors node co-located with reference analyzers to derive ad-hoc algorithms parameters. This strongly limits scalability, and thus mass these devices improved phenomena knowledge management. Global calibration, aiming a single function be used all multisensors in batch, promising recently tackled artificial olfaction field. work,...
Air pollution is a complex phenomenon driven by emissions and their (photo)chemistry along with weather conditions physical characteristics of the affected scenario. Urban areas remain an extremely challenging scenario for canyon effects traffic car which exacerbate spatio temporal variability air pollutants concentrations. Low cost Quality Sensors based crowdsensing offers solution hyper resolution AQ mapping spatial analysis phenomenon. This work presents design IoT platform supporting...
Future air quality monitoring networks will include fleets of low-cost gas and particulate matter sensors calibrated using machine learning techniques. Unfortunately, it is well known that concept drift one the primary causes losses in data operational scenarios. This work focuses on addressing a NO2 sensor calibration model update triggered via detector. study defines which are most appropriate for use updating process order to maintain compliance with relative expanded uncertainty (REU)...
Future air quality monitoring networks will integrate fleets of low-cost gas and particulate matter sensors that are calibrated using machine learning techniques. Unfortunately, it is well known concept drift one the primary causes data loss in application operational scenarios. The present study focuses on addressing calibration model update NO2 once they triggered by a detector. It also defines which most appropriate to use updating process gain compliance with relative expanded...
The last decade has seen a significant growth in the adoption of low-cost air quality monitoring systems (LCAQMSs), mostly driven by need to overcome spatial density limitations traditional regulatory grade networks. However, urban scenarios have proved extremely challenging for their operative deployment. In fact, these pervasive, accurate, personalized solutions along with powerful data management technologies and targeted communications tools; otherwise, can lead lack stakeholder trust,...
In fusion experiments, and for future international thermonuclear experimental reactor-like reactors, the mitigation of plasma disruptions is a key issue to reduce severe damage that can be caused machine by high heat loads runaway electrons. Pellet injection (PI) massive gas (MGI) are present among most promising candidate techniques mitigate disruption effects. PI consists injecting into solid cryogenic pellets, while MGI involves large amounts different species noble gases means fast...