Data & Artificial Intelligence
Revolutionize environmental engineering with the power of data and AI
Welcome to the world of using data and artificial intelligence in environmental engineering. As the production of environmental data accelerates, many valuable insights remain underutilized. At ixsane, we believe in optimizing actions through analysis and strategic use of data. With powerful algorithms and AI, we offer innovative solutions to enhance performance and operational management of environmental infrastructure.
Optimizing actions through data analysis and utilization
The production of environmental data is rapidly increasing, yet many data points are underutilized or poorly exploited. Data collected for regulatory purposes, with inconsistencies or managed by different stakeholders, represent untapped potential for understanding local phenomena that can be harnessed. Real-time data processing algorithms also provide innovative solutions that we can implement to improve the performance and operational management of infrastructure or generate useful information.
Combining domain expertise and data
ixsane provide its clients with strong domain expertise and data capabilities by leveraging its Engineering and Innovation departments. Our engineers and experts support clients from statistical analysis of data to the implementation of data integration platforms that generate specific information, alerts, or actions tailored to their needs.
Achieving more efficient wastewater networks with Artificial Intelligence
We intervene in the implementation of optimized real-time management solutions using AI algorithms for wastewater networks. This solution reduces discharges into the natural environment during rainfall events and minimizes or eliminates the need for additional water retention structures.
Accelerating the design of eco-materials with Artificial Intelligence
To promote the circular economy and encourage the reuse of degraded soils or materials in high-value applications, we expedite and optimize the formulation of new materials using algorithms and Artificial Intelligence. These algorithms, developed for our clients or utilized internally, reduce unnecessary trials, optimize recycling rates, and enhance the performance of new materials.
References
DK EAU
DK EAU: Operational-oriented R&D project for improving the management of the wastewater network in the Urban Community of Dunkirk (59).
- Technological demonstrator of a dynamic and real-time intelligent management system for wastewater networks.
- Implementation of an information and alert system, enhancing knowledge of the game and the role of local stakeholders, as well as surface flow.
Functional mapping of canals
NWE-Regeneratis Project
New solutions for the valorization of materials from industrial brownfields
- Improving soil fertility for the production of bio-sourced catalysts from plants grown on contaminated sites
Aerial view with images of the current state of the site
Production of bio-sourced catalysts
Context and Project objective:
Metal working industry represents 13 % of Potential Contaminated Sites (PCS) in the EU. While recent metallic waste streams are usually treated, older waste (aggregated material with high ferrous metal content, scrap, other metals, white and black slags and other streams) are considered as a source of pollution, expensive to manage/eliminate.
NWE-REGENERATIS aims to transform this problem into an opportunity, as large volumes of resources can be recovered by urban-mining.
To do this, the NWE-REGENERATIS project aims to test and implement on 3 sites new methodologies and innovative technical approach for new economic models for resource recovery from former metallurgical sites and deposits.
This includes a site inventory structure adapted to the objective of material recovery and the use of Artificial Intelligence algorithms as decision support, potential studies by geophysical techniques, innovative material recovery techniques uses and synthesis of catalysts from plants planted on contaminated sites.
IXSANE contributions:
· Improvement of contaminated sites diagnostics methods with resource oriented investigation
· Improving soil fertility
· Production of eco-catalyst from vegetal growing on contaminated sites in partnership with JUNIA
· Artificial intelligence to strengthen decision for site management
Partnership:
Belgium : Société Publique d'Aide à la Qualité de l'Environnement (SPAQUE), Centre Technologique International de la Terre et de la Pierre (CTP), Université de Liège, OVAM, ATRASOL, DUFERCO
United Kingdom : Materials Processing Institute (MPI), Cranfield University
France : BRGM, IXSANE, TEAM2, JUNIA
Germany : Technische Hochschule Köln, Bergischer Abfallwirtschaftsverbnd (BAV)
Project Budget :
NWE-REGENERATIS Project is funded through the INTERREG NWE programme and the European Regional Development Fund (ERDF).
· Total budget ERDF: € 4.26 million
· Total budget: € 7.10 million
Start of the project: 2019
End of the project: 2023