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TRAFAIR Deliverables List

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The Trafair project (https://trafair.eu/) brings together 10 partners from two European countries (Italy and Spain) to develop innovative and sustainable services combining air quality, weather conditions, and traffic flows data to produce new information for the benefit of citizens and government decision-makers.

Air pollution causes 400,000 deaths per year, making it first environmental cause of premature death in Europe. Among the main sources of air pollution in Europe, there are road traffic, domestic heating, and industrial combustion. Nowadays, the situation is particularly critical in some member states of Europe. In February 2017, the European Commission warned five countries, among which Spain and Italy, of continued air pollution breaches. These countries fail to address repeated breaches of air pollution limits for nitrogen dioxide (NO2) whose most emissions result from road traffic. The European Commission urged these Member States to take action to ensure good air quality and safeguard public health. In this context, public administrations and citizens suffer from the lack of comprehensive and fast tools to estimate the level of pollution on an urban scale resulting from varying traffic flow conditions that would allow optimizing control strategies and increase air quality awareness.

TRAFAIR raises awareness among citizens and public administrations about the air quality within an urban environment and the pollution caused by traffic.
The project aims at monitoring air quality by using sensors in 6 cities and making air
quality predictions thanks to simulation models. The two main goals of the project are:
1) monitoring urban air quality by using sensors in 6 European cities: Zaragoza (600,000 inhabitants), Florence (382,000), Modena (185,000), Livorno (160,000), Santiago de Compostela (95,000) and Pisa (90,000);
2) making urban air quality predictions thanks to simulation models based on weather forecast and traffic flows.

Monitoring air quality means to set up a network of low-cost sensors spread within the city to monitor levels of pollutions in areas that are not covered by the legal air quality stations.

What DISIT lab with Snap4City platform has done for TRAFAIR, exploiting the High Performance Computing insfrastructure and machine learning solutions of DISIT lab:

  • development of the traffic flow reconstruction model and tools
  • implementation of the traffic flow reconstruction algorithm and processes for: Firenze, FIPILI, Livorno, Pisa, Santiago di Compostela
  • development of the GRAL Based solution for predicting NOX over the cities of Firence, Livorno and Pisa
  • Validation of the GRAL vs actual values
  • deploy of a number of air quality sensors with the support of CNR IBE
  • development of specific Dashboards for accessing to data, heatmaps, traffic flow, etc., drill down and animations on heatmaps
  • development of views into mobile Apps to allow the users to access at air quality data and predictions
  • dissemination and promotion activities 
  • etc. 

The following is a list of deliverables produced for the TRAFAIR projects. Public deliverables can be downloaded.



Activity 1  
D1.1 Identification of data sources and data collection concerning pollution, traffic and weather forecast
D1.2 Automatic/semi-automatic population of a local dataset for data on pollution, traffic data and weather forecast.
D1.3 Automatic/semi-automatic population of local datasets (1st release)
D1.4 Identification of the most relevant smart city ontologies
D1.5 Identification of the most relevant smart city ontologies
D1.6 Collection of additional input data for each city  
D1.7 Crowdsourced road traffic data: INRIX, TOM TOM, BING, Google traffic, HERE traffic API, Open Transport Map
D1.3 Automatic/semi-automatic population of local datasets (1st release)
D1.6 Collection of additional input data for each city
D1.8 Automatic/semi-automatic population of local datasets (2nd release)
   
Activity 2  
D2.1 Urban sensor networks status v1 
D2.2 Sensor data acquisition: tool and technical description (including data access and storage) (1st release). 
D2.3 Sensor data acquisition (2nd release)
D2.4 Best practice manual for air quality sensor maintenance (1st version)
D2.5 Installation, maintenance and calibration procedures for the air quality sensors
D2.6 Collection of sensor data
D2.7 Urban sensor network status - final version
D2.8 Sensor data acquisition (including data access and storage) (final release)
D2.10 Installation, maintenance and calibration procedures for the air quality sensors  
D2.11 Installation, maintenance and calibration procedures for the air quality sensors  
D2.9 Best practice manual for air quality sensor maintenance (final version) 
   
Activity 3  
D3.1 Models setup and specific guidelines definition
D3.2 A parallelized version of the GRAL atmospheric dispersion model (1st version) 
D3.3 QR1 Report for the use of High-Performance Computing technologies QR1
D3.3 QR2 Report for the use of High-Performance Computing technologies QR2
D3.4 Modelling quality objectives and benchmarking (1st version)
D3.5 Models generation: results and evaluation (1st version)
D3.6 Development of a coarse urban air pollution map in semi-real time (1st version)
D3.7 Summary report about the results and the performance of parallelization strategies for GRAL which have been tested.
D3.8 Parallel-Micro-Swift-Spray and GRAL comparison
D3.9 Modelling quality objectives and benchmarking (final version), and outlier detection in air quality sensors and GRAL simulation
D3.10 Final report on results and performance of parallelization strategies for the Lagrangian particle tracking model and code release (final version)
D3.11 Evaluation of the final parallelized version of GRAL including non-traffic emission sources
D3.12 Development of a coarse urban air pollution map in semi-real time (final version)
D3.14 Description and evaluation of the traffic model applied in each city. 
D3.15 Models generation: results and evaluation (final version) (Evaluation of the GRAL outputs following  the guidelines defined in D3.9)
   
Activity 4  
D4.1 A report on the analysis of the existing best practices, standards and services for air quality data releasing
D4.2 Metadata and open geo-referenced urban air quality dataset (1st release)
D4.2 Metadata and open geo-referenced urban air quality dataset (1st release)
D4.3 Metadata and open geo-referenced urban air quality dataset (2nd release)
D4.4 Metadata and open geo-referenced urban air quality dataset (final version)
D4.5 Policies and tools for updating the air quality dataset
D4.6 Report of Metadata Quality Assurance (MQA) tool for RDF datasets Metadata
   
Activity 5  
D5.1 Collection of user requirements for end-user mobile applications, i.e., for citizens, students, tourists, workers, etc.
D5.2 The first version of an interactive map that display the coarse urban air pollution map in semi-real time 
D5.3 Mobile apps, Public Administration (PA) tools and map visualization tools (1st release). 
D5.4 Development of mobile apps, PA tools and map visualization tools (2nd release). 
D5.5 Development of mobile apps, PA tools and map visualization tools (final release).
   
Activity 6  
D6.1 Project Plan
D6.2 Dissemination Plan_v1
D6.3 Dissemination Plan_v2
D6.4 Progress activity reports for internal monitoring _ v1
D6.5 Dissemination Plan_v3
D6.6 Progress activity reports for internal monitoring _v2
D6.7 Project Plan - 2 year
D6.8 Progress report on dissemination activities_v2
D6.9 Progress activity reports for internal monitoring _ v3
D6.10 Preliminary Sustainability Plan_v1
D6.11 Progress report on dissemination activities_final
D6.12 Progress activity reports for internal monitoring _final
D6.13 Sustainability Plan_final

Other examples and connected scenarios:

 

TRAFAIR: INEA CEF-TELECOM Project
co-funded by European Union
AGREEMENT No INEA/CEF/ICT/A2017/1566782

Disclaimer: The contents of this publication are the sole responsibility of DISIT Lab - DINFO -UNIFI and do not necessarily reflect the opinion of the European Union. 

 

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