Periodic Reporting for period 2 - iFLUX (Real-time flow and flux measurements for combating groundwater supply and pollution.)
Reporting period: 2023-07-01 to 2024-10-31
Groundwater is a critical resource for communities, industries, and ecosystems, yet managing it effectively has long been a challenge. Governments, industries and communities are investing in a water resilient future. Groundwater monitoring and data acquisition are prerequisites for any effective management of groundwater resources and preservation, in terms of both the groundwater quality and the availability of the groundwater resource itself.
iFLUX has developed a groundbreaking real-time flux sensor that measures groundwater flow speed and direction with unmatched accuracy. This innovation, combined with a robust data logger and smart IoT connectivity, ensures seamless data collection and reliability in any setting. Our intelligent data platform transforms this data, combined with various other data inputs, into actionable insights. Users receive live data updates, anomaly detection, and analytics—all through a user-friendly dashboard.
Innovation doesn’t stop at development—it’s about impact. We crafted a bold go-to-market strategy to ensure iFLUX reaches those who need it most. By targeting water utilities, construction industries and urban or nature based solutions we’re addressing critical groundwater challenges while unlocking significant economic and environmental value.
As part of the project iFLUX engaged stakeholders from the start, ensuring our solutions met real-world needs. Through pilot projects we validated our technology in diverse environments, addressing challenges like contamination control, water balance optimization, and saltwater intrusion. Stakeholder feedback shaped our iterative development process, ensuring that our tools deliver tangible value.
This project, made possible by the EIC grant, is about more than innovation—it’s about protecting our planet. By empowering stakeholders with real-time insights, we’re helping to safeguard groundwater resources, reduce contamination, and support sustainable ecosystems for future generations.
iFLUX has developed a groundbreaking real-time flux sensor that measures groundwater flow speed and direction with unmatched accuracy. This innovation, combined with a robust data logger and smart IoT connectivity, ensures seamless data collection and reliability in any setting. Our intelligent data platform transforms this data, combined with various other data inputs, into actionable insights. Users receive live data updates, anomaly detection, and analytics—all through a user-friendly dashboard.
Innovation doesn’t stop at development—it’s about impact. We crafted a bold go-to-market strategy to ensure iFLUX reaches those who need it most. By targeting water utilities, construction industries and urban or nature based solutions we’re addressing critical groundwater challenges while unlocking significant economic and environmental value.
As part of the project iFLUX engaged stakeholders from the start, ensuring our solutions met real-world needs. Through pilot projects we validated our technology in diverse environments, addressing challenges like contamination control, water balance optimization, and saltwater intrusion. Stakeholder feedback shaped our iterative development process, ensuring that our tools deliver tangible value.
This project, made possible by the EIC grant, is about more than innovation—it’s about protecting our planet. By empowering stakeholders with real-time insights, we’re helping to safeguard groundwater resources, reduce contamination, and support sustainable ecosystems for future generations.
Thanks to EIC support, iFLUX has accelerated the development and validation of its advanced groundwater monitoring technology. A new flux sensor, enhanced with modular water quality measurement capabilities, was designed for real-time data collection with exceptional accuracy. A robust data logger was also engineered for long-term autonomous operation, ensuring scalability and reliability in diverse environments. A cloud-based dataflow and analytical pipeline were created to process and analyze large-scale groundwater data. The platform incorporated machine learning algorithms for anomaly detection and advanced insights. A user-friendly dashboard provided intuitive visualizations and real-time alerts, making actionable insights accessible to stakeholders. Together, these innovations delivered a field-ready solution for groundwater management.
The technology was validated through pilot demonstrations at 3 drinking water companies addressing challenges such as saltwater intrusion, water balance optimization, and retention time validation. These real-world tests confirmed the system's adaptability, reliability, and operational value.
Stakeholder feedback was an integral part of refining the technology, ensuring it met practical needs and regulatory standards. The result is a market-ready product offering real-time monitoring, advanced analytics, and user-centric design, significantly advancing sustainable groundwater management.
The technology was validated through pilot demonstrations at 3 drinking water companies addressing challenges such as saltwater intrusion, water balance optimization, and retention time validation. These real-world tests confirmed the system's adaptability, reliability, and operational value.
Stakeholder feedback was an integral part of refining the technology, ensuring it met practical needs and regulatory standards. The result is a market-ready product offering real-time monitoring, advanced analytics, and user-centric design, significantly advancing sustainable groundwater management.
Further evolutions on the LOC (lab-on-a-chip) sensor market could allow for a more cost-efficient solution, allowing integration of LOC sensors within the iFLUX sensor. Currently integrations occur via separate sensors on the data dashboard, and many important quality parameters are not yet available commercially.
To further enhance and automate anomaly detection and correction capabilities, more data capture and analysis is required over a longer timeframe to allow for more complex and correlated anomalies.
Deployment of the sensor would also benefit from a reduction in the sensor size, allowing for smaller diameters wells, resulting in more cost efficient installation.
To further enhance and automate anomaly detection and correction capabilities, more data capture and analysis is required over a longer timeframe to allow for more complex and correlated anomalies.
Deployment of the sensor would also benefit from a reduction in the sensor size, allowing for smaller diameters wells, resulting in more cost efficient installation.