a project to join

Sensor Fusion Lab (SFL) is a Barcelona-based engineering SME that designs field-ready sensing devices, embedded firmware and Edge AI for environmental and industrial monitoring. We cover the full device chain: sensor selection and signal conditioning, electronics design, low-power firmware (C/C++, Zephyr, FreeRTOS on STM32, nRF52, ESP32), embedded Linux gateways, IoT connectivity (LoRa/LoRaWAN, BLE, cellular) and on-device AI (TFLite, STM32Cube.AI, computer vision on Sony IMX500).

In a Water4All consortium, SFL can take monitoring concepts from TRL 4 to validated pilots (TRL 6-7): design and manufacture of sensor nodes, firmware, on-device calibration and anomaly detection, secure data transfer to partners' digital twins or decision-support platforms, and field deployment. Our designs follow the EU Cyber Resilience Act.

Ongoing projects:

Pulse: low-power IoT metering node (ESP32-S3, Zephyr, LoRa, secure element).
Edge AI retrofit monitoring in two food-industry pilots, combining new sensors with computer vision that reads analogue gauges, plus an AI agent on the edge gateway.

Team: 12+ years in embedded engineering, including Horizon 2020 R&D and mission-critical deployments at an Antarctic research station.

Keywords: Edge AI, embedded firmware, IoT sensor networks, computer vision monitoring.

Topic 1. Integrated Monitoring and Assessment for Sustainable Water Management
Topic 3. Smart, Secure and Adaptive Water Infrastructures for Sustainable Water Management

SFL wants to join a Water4All consortium under Topic 1 (Integrated Monitoring and Assessment) and/or Topic 3 (Smart, Secure and Adaptive Water Infrastructures) as the technology partner that turns monitoring concepts into working field hardware.

Many water projects have strong models, digital twins and decision-support tools, but depend on sparse, costly or legacy field data. Our interest is in closing that gap: dense, low-cost and low-power sensor networks, edge processing that sends events instead of raw data, and vision-based retrofit of existing analogue instruments in treatment plants, sewers, rivers, irrigation or buildings.

We can lead or contribute to a work package on:

Design and manufacture of multi-parameter sensor nodes for pilot sites (level, flow, turbidity, conductivity, pH, electrochemical sensing).
Low-power firmware, LoRaWAN/cellular connectivity and secure, CRA-ready devices.
On-device anomaly detection, sensor drift compensation and computer vision.
Integration with partners' data platforms, digital twins and SCADA, plus field deployment and maintenance during pilots.

We are especially interested in projects with a clear use case and pilot site (utility, municipality, industrial or agricultural operator), and partners who bring hydrology, water quality or modelling expertise. For SFL, Water4All is a way to validate our Edge AI and sensing platforms in real water systems and to build long-term transnational partnerships.

edge ai, embedded systems, iot, sensors, wireless sensor networks, water quality monitoring, real-time monitoring, anomaly detection, computer vision, smart water infrastructure

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