A5059996942- Air Quality Monitoring and Forecasting
- Advanced Chemical Sensor Technologies
- Air Quality and Health Impacts
- Gas Sensing Nanomaterials and Sensors
- Insect Pheromone Research and Control
- Vehicle emissions and performance
- Water Systems and Optimization
- Water Quality Monitoring Technologies
- Analytical Chemistry and Sensors
- Atmospheric chemistry and aerosols
- Energy Efficient Wireless Sensor Networks
- Water Quality Monitoring and Analysis
- Advanced Sensor Technologies Research
- Data Stream Mining Techniques
- Anomaly Detection Techniques and Applications
- Artificial Immune Systems Applications
- Photovoltaic System Optimization Techniques
- Water Treatment and Disinfection
- Solar Radiation and Photovoltaics
- Energy Load and Power Forecasting
- Environmental Monitoring and Data Management
- IoT-based Smart Home Systems
- Impact of Light on Environment and Health
- Food Supply Chain Traceability
- Smart Materials for Construction
National Agency for New Technologies, Energy and Sustainable Economic Development
2015-2024
ENEA Portici Research Centre
2008-2022
Sensors (United States)
2022
Università degli studi di Cassino e del Lazio Meridionale
2010-2012
Torino e-district
2009
GTx (United States)
2008
University of Naples Federico II
2003
The 1st EuNetAir Air Quality Joint Intercomparison Exercise organized in Aveiro (Portugal) from 13th–27th October 2014, focused on the evaluation and assessment of environmental gas, particulate matter (PM) meteorological microsensors, versus standard air quality reference methods through an experimental urban monitoring campaign. IDAD-Institute Environment Development Mobile Laboratory was placed at traffic location city centre to conduct continuous measurements with equipment analysers for...
Semi-supervised learning is a promising research area aiming to develop pattern recognition tools capable exploit simultaneously the benefits from supervised and unsupervised techniques. These can lead very efficient usage of limited number samples achievable in many artificial olfaction problems like distributed air quality monitoring. We believe it also be beneficial addressing another source knowledge we have face when dealing with real world problems: concept sensor drifts. In this paper...
In the current era, Artificial Intelligence (AI) is becoming increasingly pervasive with applications in several applicative fields effectively changing our daily life. this scenario, machine learning (ML), a subset of AI techniques, provides machines ability to programmatically learn from data model system while adapting new situations as they more by are ingesting (on-line training). During last years, many papers have been published concerning ML field solar systems. This paper presents...
Outdoor exposure to particulate matter (PM2.5 and PM10) in urban areas can vary considerably depending on the mode of transport. This study aims quantify this difference during daily travel, by carrying out a micro-sensor measurement campaign. The pollutant was assessed simultaneously over predefined routes order allow comparison between different transport modes having same starting ending points. During six-week campaign, average reference values for PM background concentrations were 13.72...
Building's energy demand is influenced by many factors, such as: weather conditions, building structure and characteristics, consumption of components (lighting HVAC systems), level occupancy user's behavior. As consequence multi-variable impact on building's consumption, theoretical models based first principles are not able to forecast actual a generic building. In this paper, an Artificial Neural Network (ANN) model applied real case consisting in dataset monthly historical electric...
Chemicals detection and quantification is extremely important for ensuring safety security in multiple application domains like smart environments, building automation, etc. Characteristics of chemical signal propagation make single point measure approach mostly inefficient. Distributed sensing with wireless platforms may be the key reconstructing images sensed environment but its development currently hampered by technological limits on solid-state sensors power management. We present...
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...
Novel model of citizenship calls for a new approach to the policy making, characterized by wish be part information building process. The citizen wants become an active member smart city. This has its impact also on air quality monitoring and control In this work, we try answer these needs investigating centered concept. goal is enable individuals monitor their exposure pollution simultaneously contribute creating map state urban through sharing data.
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)...
Indoor Air Quality assessment is an emerging application field for chemical sensing due to raising concerns about indoor VOC pollution levels. Local and distributed of chemicals concentrations also significant safety (gas spills detection, monitoring) security applications as well HVAC automation energy efficiency. Mobile robot based wireless sensor network approaches are under investigation providing efficient solutions. Here, we report results obtained by a intelligent electronic noses in...