Technology
SEA-SENSE uses a four-layer architecture — edge sensing, connectivity, cloud processing, and digital twin integration — built on open standards for interoperability. The system is designed around the NGSI-LD data specification and is compatible with the FIWARE ecosystem.
Architecture Overview
The SEA-SENSE monitoring system follows a structured data pipeline. Environmental sensors deployed at cultivation sites collect measurements in real time. Sensor data is aggregated by a local gateway, which handles protocol conversion and transmits it to cloud services using the NGSI-LD standard. In the cloud, data is processed, stored, and made available through APIs. Digital twin platforms consume this data for visualisation, analysis, and decision support. Each layer is designed to operate independently and communicate through standardised interfaces.
Sensors and Edge Devices
Environmental sensors measure the parameters most critical to seaweed cultivation: water temperature, light intensity (photosynthetically active radiation), pH, dissolved oxygen, salinity, and nutrient concentrations. Sensors are selected and configured for two distinct deployment contexts — indoor hatchery tanks and exposed offshore structures. At the edge, local processing handles data sampling, filtering, and buffering, ensuring that intermittent connectivity does not result in data loss.
Connectivity and Gateway
The gateway aggregates data from multiple sensors at a site and manages upstream communication to the cloud platform. In hatchery environments, the gateway connects via Wi-Fi or Ethernet. For offshore deployments, it supports protocols suited to remote marine conditions, such as LoRaWAN or cellular networks. The gateway converts raw sensor data into NGSI-LD format before transmission, so that data arriving at the cloud layer is already standardised.
Cloud Platform and NGSI-LD
Cloud services handle data ingestion, storage, processing, and API delivery. The platform is built to be compatible with FIWARE components, including NGSI-LD context brokers for managing real-time context information. RESTful APIs provide data access for digital twin platforms, dashboards, and third-party consumers. An alarm engine evaluates incoming data against configurable thresholds, triggering notifications when parameters exceed acceptable ranges.
Digital Twin Integration
The monitoring system feeds real-time data into digital twin environments, where cultivation sites can be visualised spatially with environmental data overlaid on site maps or models. Digital twins enable operators and researchers to observe conditions across an entire site at a glance, identify patterns, and explore scenarios — for example, projecting the impact of a sustained temperature change on cultivation outcomes.
Standards and Interoperability
SEA-SENSE is built on open standards to ensure that monitoring data is reusable, comparable, and integrable with other systems.
| Standard | Role in SEA-SENSE |
|---|---|
| NGSI-LD | Data model and API specification for context information management |
| FIWARE | Reference architecture and compatible platform components |
| Smart Data Models | Alignment with community-maintained data model catalogues |