Six months after GreenMov starting, first results are in!
The 24-month project is funded by the European Commission under the Connecting Europe Facilities (CEF) program. It proposes sustainable mobility and open data for smart ecosystems aligned with the EU Green Deal.
Madrid, April 25, 2022. GreenMov was launched in September 2021 with the aim of harmonizing data models and exploring green mobility services through high-value solutions.
Six months after starting the project, the first results have been released. See below.
Smart data models for green mobility
After defining the methodology to identify the data sources and their data models, several data models have been identified for the three use cases in the project (Nice, Murcia-Molina de Segura and Flanders). Currently, eleven (11) data models have identified. Eight (8) data models have been updated from the Smart Data Models Initiative and its repository to be used in the future similar scenarios and three new data models (Noise Pollution, Vehicle Emission Label, Public Transport) have been submitted for approval.
In order to promote the use of existing European data sources, these data models were compared with the European data portal and European environmental portal.
Additionally, GreenMov is evaluating OSLO (Open Standars for Linked Organizations) vocabularies and application profiles for the mobility domain. GreenMov has just initiated the co-creation of an OSLO Passenger Transport Hub data model to facilitate multimodality: access to and transfer between various transport options.
Smart Services for green mobility
Several Smart Services for Green Mobility have been already defined and will be implemented for the use case cities and potentially reusable for more cities in Europe.
Since February 2022 the identification of the services required by the use case cities and the analysis of the commonalities between them in order to reuse them have been carried out. The services include forecasting the air quality index, traffic flow, and bicycle availability.
Architecture for Context Broker enhancement in concurrent data-intensive scenarios such as mobility.
Main progress has been made on the scalable context broker (i.e. a component that allows retrieving and storing contextual information about data collected from different sources) with the main ambition to link location and time based information with mobility and environment data, as part of the use cases being deployed in Flanders, Murcia-Molina de Segura and Nice.
Scalability is achieved by extending the context broker with cacheable Linked Data fragments using the Linked Data Event Streams (LDES) specification. A Linked Data Event Stream is a collection of immutable objects described in RDF, such as version objects, sensor observations or archived representations.
More specifically, the following results have been achieved so far:
- Implementation of an adaptor pipeline from LDES to NGSI-LD Context Broker (southbound), including schema transformation (RDFS to NGSI-LD meta-model).
- Preliminary implementation of (temporary) adapters from NGSI-LD Context Broker to LDES (northbound), which we call the NGSI-LDES approach.
- Preliminary implementation and publication of a set of data streams in a specific format LDES for use cases, e.g. Blue Bike availability for the Flanders Use Case.
On the other hand, we have introduced improvements in other aspects of our portfolio of activities, namely:
- A preliminary implementation of a bridge between platforms using an older protocol for data exchange (NGSiV2) and platforms using the latest version of Linked Data (NGSi LD).
- Scalability and performance testing on Linked Data context brokers powered by FIWARE
- Development of a mechanism to make our architecture more resilient and easier to retrieve (based on queuing strategy).
Deployment of pilots
The three use cases involved in the project will support us to deploy and validate the data models, services and architectures developed during the project. Let’s recap about them.
Flanders region is leveraging interoperability to allow end users to seamlessly access public transport information, such as train or bicycle availability for their trip, and decide whether they should leave earlier or arrive later based on what is available.
Murcia/Molina De Segura, two near cities in southeast of Spain will allow citizens to switch modes of transport when air quality degrades in order to decarbonize their mobility, by using low-cost air quality sensors and monitoring bicycle availability.
Nice Côte d'Azur Metropolis aims to inform car drivers about the need to change their mode of transport one day in advance in order to decarbonize their mobility, based on local air quality and traffic forecasting.
What is next
In February, GreenMov partners elaborated a study on the data and service requirements to implement the experiments in each project site. This study lists all the datasets to be used in each experiment, but also starts to describe the services to be implemented and provides a first version of the indicators for the experiments.
Since the beginning of March 2022, the various pilots have been working closely with local stakeholders to launch the data collection phase, which will enable the artificial intelligence engineers to apply the necessary forecasting models.
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