AIR PROJECT

AIR PROJECT

The Consortium (DEISTER, STA, and BETTAIR) combines its experience and knowledge for the development of AIRE, an Artificial Intelligence (AI) platform for predicting and projecting future air-quality scenarios in urban and semi-industrial areas that help end users make decisions with environmental impact.

Current challenge

  • Currently, the density of air-quality monitoring points in cities is insufficient to obtain accurate information at the prediction level.
  • In the era of the Internet of Things (IoT), there is still no robust, maintenance-free, and scalable commercial technology that allows cities to understand and mitigate air pollution.

The Solution:
AIRE Platform

In response to this unquestionable need, the Consortium sets as the general objective of the project the development of the AIRE platform for urban and semi-industrial environments that:
  • Brings together air-quality monitoring technology, provided by traditional stations and IoT devices that enable real-time measurements with very high spatial resolution and with a small investment.
  • Incorporates predictive scenarios based on Artificial Intelligence (AI) techniques, using both micro air-quality data and macro data based on satellite-data analysis.

Within the project's technical developments,
the following is proposed:

Evaluation platform with
enhanced AI models:

  • Development of an air-quality evaluation platform with improved and enhanced AI models, based on existing Copernicus predictive models (macro data), through the incorporation of field measurements (traditional air-quality monitoring stations and IoT sensors – micro data).
  • The application of new AI strategies and techniques will provide greater confidence in the predictive algorithms that form the predictive layer of the AIRE platform in specific areas. These AI strategies and techniques will address the challenge posed by the addition of new micro-level data sources in terms of quality (heterogeneous data, degraded data, incomplete series).

AI strategies for
greater confidence:

  • The feasibility of the platform will be studied through the creation of a single online repository that includes the different tools for diagnosing and predicting actions to improve air quality and the short-term action plans that AIRE: Artificial Intelligence Platform for predicting air quality from sensor data and Copernicus services requires for Public Administrations. This online repository could provide input data for a Digital Twin of the region or area in question and would represent the temporal evolution of its atmospheric activity.

Online repository for
public administrations:

Tool for precise and early
determination:

  • The new AIRE platform will function as a tool and methodology for the precise (improved measurement at a local resolution level beyond the current limitation of satellite image resolution) and early (predictive) determination of air quality in a particular area (maps with air-quality models and a decision-support system).

Strategic collaboration for the AIRE project

To develop the AIRE platform, it is necessary to bring together diverse skills and capabilities, both at the technological level and in the application domain (business rules). The Consortium, led by DEISTER and including STA and BETTAIR as partners, achieves this complementarity by combining DEISTER’s capabilities in high-level software development, STA’s capabilities as a manufacturer of weather stations and air-quality control systems, and BETTAIR’s capabilities in developing low-cost air-quality monitoring sensor devices, also covering the value chain for the AIRE platform.
Looking a little more closely at the activities of the companies that are part of the Consortium, it is worth highlighting that:
DEISTER
Its main objective is the development and commercialization of software applications and products that enable companies to manage their information systems and business processes more efficiently. As a provider of high-tech products, it focuses its efforts on innovation and quality, as well as on training its network of partners and collaborators who facilitate the implementation of its products in companies.
STA
It is a technology company that, since its founding, has consolidated its activity as a manufacturer of weather stations and air-quality control systems. At the present moment, in which the fight against climate change has been defined at the institutional level as a priority objective, a growth opportunity opens for STA within a market where Public Administrations and industrial companies with potentially polluting activities play an important role as clients.

BETTAIR CITIES 

It is a company founded with the mission of empowering cities and communities to effectively mitigate air pollution by providing them with actionable and reliable data through its technology based on low-cost sensors. Its vision is to help cities reduce air pollution worldwide, significantly improving people’s quality of life.

TECHNICAL OBJECTIVES

AIRE: Artificial Intelligence Platform for predicting air quality from sensor data and Copernicus services. The approach to designing and developing the air-quality platform is based on several specific technical objectives related to the technological features and degree of innovation of the project:
  • Deployment of a new generation of low-cost IoT sensors with edge AI (AIoT) that provides accurate measurements of air pollutants including NO₂, NO, O₃, CO, SO₂, and particulate matter, among others, in both urban and semi-industrial areas, where this technology is less validated due to the presence of other pollutants such as NH₃ and H₂S.

OT1.

  • Research on the feasibility of using environmental, meteorological, and spatial data at both the micro level (traditional air-quality monitoring stations, IoT sensors) and the macro level (satellite) to improve current air-quality prediction models (spatiotemporal evolution).

OT2.

  • Development of a predictive model based on existing models provided by the consortium partners and enhanced with the addition of high-quality micro data, which have been pre-validated using AI techniques (heterogeneous data, degraded data, incomplete series).

OT3.

Study and design of a simulation layer based on standardized models that allow the analysis and validation of action plans before their execution or the rapid and effective anticipation of the consequences of chemical emergencies.

OT4.

Design and development of an IoT-based platform for the acquisition, storage, and processing of data from the sensor network and open data sources (for example, time series data from Copernicus, National Geographic Institutes, and similar sources) that provide a heterogeneous data source for the evaluation of environmental indicators.

OT5.

  • Validation of the platform's feasibility through the creation of a single integrated interface that brings together all the aforementioned tools, providing easy-to-use access for the end user, Public Administration, and others.

OT6.

RESULTS

As a result of the project, the AIRE platform has been developed, functioning as a tool and methodology for the precise (improved measurement at a local resolution level beyond the current limitation of satellite image resolution) and early (predictive) determination of air quality in a particular area (maps with air-quality models and a decision-support system).