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The development of a simple, low-cost methodology for obtaining substrate sandbanks parameters.
This methodology, proposed in cooperation with stakeholders, will allow...
CETMAR leads the digitalization of mussel rafts to enable real-time environmental and production monitoring, tailored to stakeholders’ needs. It gathers extensive data to optimize management in the face of climate challenges.
MRM addresses the need of understanding the effects of climate change on mussel aquaculture for enhancing resilience in the sector: extreme events and variations on oceanographical conditions (temperature, salinity, wind patterns, upwelling, pH…) pose serious challenges to the industry including disruptions to production cycles, management operations and infrastructure.
To tackle these issues, MRM focuses on the design and deployment of an autonomous IoT system tailored to the harsh marine environment. This system sensorize mussel rafts using renewable energy, allowing for real-time, continuous monitoring of environmental and production parameters. By minimizing maintenance needs and enabling cost-effective operations, the solution is designed to be both sustainable and scalable.
Beyond the technological innovation, the project aims to generate FAIR-compliant data, to improve scientific understanding of local ocean dynamics, support the development of early warning systems, and inform adaptive management strategies. This knowledge is critical for anticipating and mitigating the impacts of climate-related hazards.
Socially, the project creates a direct line of communication with mussel producers to co-design solutions that reflect real operational needs, foster risk awareness, and promote sector engagement and governance innovation. Through improved access to actionable data, the initiative empowers the sector to adapt proactively, enhancing its resilience and sustainability in the long term.
See more information about this level and the TRL and SRL levels.
The MRM is a digital IoT solution tailored for marine environments, providing real-time environmental and production data to continuously monitor mussel raft behaviour over the long term. Installed on existing infrastructure and powered by solar energy, it autonomously collects and transmits data via telemetry, supporting operational decision-making and resource management. Integrated sensors capture structural and oceanographic parameters, offering insights into natural variability and extreme events. The MRM introduces a more agile, cost-effective, and low-maintenance approach to marine monitoring. The MRM is recognized by producers, regional authorities, and the scientific community as a valuable tool for testing adaptation strategies and enhancing resilience. While core components are affordable, oceanographic sensor costs may vary depending on required accuracy. Overall, the MRM fosters a shift in perception in which monitoring becomes a key ally in the sustainable management of aquaculture systems.
Following the selection of mussel rafts, a co-design process is undertaken with raft owners to gather feedback and ensure their needs are met. Then, real-time monitoring requires the selection and installation of sensors to assess both structural and environmental conditions.
The system tracks raft movements, precise location, mussel ropes weight increase, and potential vandalism. A GPS device enables early warnings of mooring failure. A combination of gyroscope, accelerometer, and magnetometer detects displacement, rotation, orientation, and sudden changes. Load cells estimate mussel growth.
Meteorological and oceanographic parameters include air temperature, pressure, salinity, water transparency, and water column temperature—key for assessing marine heat waves, low salinity waves or changes in wind patterns.
At the same time, the monitoring hardware is designed and installed, and
communication protocols for real-time data transmission developed (real-time
version with telemetry). The main components include a Campbell CR1000X datalogger, a Vaisala WXT530 weather station, a Seabird Inductive CTD, a Seapoint turbidimeter, one main IMU node, and three sub-nodes (ULC) with the sensors that provide data on the conditions to which the raft is exposed, both structurally and environmentally.
Data collected by the datalogger is transmitted in real time via a Milesight UR32 router using a SIM card. Campbell Sci’s LoggerNet software allows remote connection to check system status, update programs, and configure the datalogger. The entire system is powered by photovoltaic panels.
Finally, data acquisition frequencies are optimized and managed through a data architecture developed in Django, an open-source web framework that integrates database management, user authentication, content administration, and task automation.
In the final stage, real-time data is displayed on a dashboard built with Grafana. This intuitive and user-friendly platform supports, visualization of the data and downloading time series data for both human users and machine applications.
A set of minimum requirements must first be discussed and agreed upon with producers to address both their daily operational needs on the rafts and the associated scientific and technological objectives:
Technological Requirements:
The system is designed to operate autonomously for data collection and energy, allowing minimal intervention. The installation must operate autonomously for at least 15 days.
CETMAR leads the digitalization of mussel rafts to enable real-time environmental and production monitoring, tailored to stakeholders’ needs. It gathers extensive data to optimize management in the face of climate challenges.
MRM addresses the need of understanding the effects of climate change on mussel aquaculture for enhancing resilience in the sector: extreme events and variations on oceanographical conditions (temperature, salinity, wind patterns, upwelling, pH…) pose serious challenges to the industry including disruptions to production cycles, management operations and infrastructure.
To tackle these issues, MRM focuses on the design and deployment of an autonomous IoT system tailored to the harsh marine environment. This system sensorize mussel rafts using renewable energy, allowing for real-time, continuous monitoring of environmental and production parameters. By minimizing maintenance needs and enabling cost-effective operations, the solution is designed to be both sustainable and scalable.
Beyond the technological innovation, the project aims to generate FAIR-compliant data, to improve scientific understanding of local ocean dynamics, support the development of early warning systems, and inform adaptive management strategies. This knowledge is critical for anticipating and mitigating the impacts of climate-related hazards.
Socially, the project creates a direct line of communication with mussel producers to co-design solutions that reflect real operational needs, foster risk awareness, and promote sector engagement and governance innovation. Through improved access to actionable data, the initiative empowers the sector to adapt proactively, enhancing its resilience and sustainability in the long term.
The main components of the system have been tested separately, and an initial integration exercise has been conducted.
The MRM is a digital IoT solution tailored for marine environments, providing real-time environmental and production data to continuously monitor mussel raft behaviour over the long term. Installed on existing infrastructure and powered by solar energy, it autonomously collects and transmits data via telemetry, supporting operational decision-making and resource management. Integrated sensors capture structural and oceanographic parameters, offering insights into natural variability and extreme events. The MRM introduces a more agile, cost-effective, and low-maintenance approach to marine monitoring. The MRM is recognized by producers, regional authorities, and the scientific community as a valuable tool for testing adaptation strategies and enhancing resilience. While core components are affordable, oceanographic sensor costs may vary depending on required accuracy. Overall, the MRM fosters a shift in perception in which monitoring becomes a key ally in the sustainable management of aquaculture systems.
Following the selection of mussel rafts, a co-design process is undertaken with raft owners to gather feedback and ensure their needs are met. Then, real-time monitoring requires the selection and installation of sensors to assess both structural and environmental conditions.
The system tracks raft movements, precise location, mussel ropes weight increase, and potential vandalism. A GPS device enables early warnings of mooring failure. A combination of gyroscope, accelerometer, and magnetometer detects displacement, rotation, orientation, and sudden changes. Load cells estimate mussel growth.
Meteorological and oceanographic parameters include air temperature, pressure, salinity, water transparency, and water column temperature—key for assessing marine heat waves, low salinity waves or changes in wind patterns.
At the same time, the monitoring hardware is designed and installed, and
communication protocols for real-time data transmission developed (real-time
version with telemetry). The main components include a Campbell CR1000X datalogger, a Vaisala WXT530 weather station, a Seabird Inductive CTD, a Seapoint turbidimeter, one main IMU node, and three sub-nodes (ULC) with the sensors that provide data on the conditions to which the raft is exposed, both structurally and environmentally.
Data collected by the datalogger is transmitted in real time via a Milesight UR32 router using a SIM card. Campbell Sci’s LoggerNet software allows remote connection to check system status, update programs, and configure the datalogger. The entire system is powered by photovoltaic panels.
Finally, data acquisition frequencies are optimized and managed through a data architecture developed in Django, an open-source web framework that integrates database management, user authentication, content administration, and task automation.
In the final stage, real-time data is displayed on a dashboard built with Grafana. This intuitive and user-friendly platform supports, visualization of the data and downloading time series data for both human users and machine applications.
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