Aquaculture & Fishery

Aquaculture involves cultivating freshwater and saltwater populations under controlled conditions and the global output is estimated to be more than half of the fish and shellfish consumed directly by humans.

Industry Challenge

The aquaculture and fishery industries can gain many benefits from increased digitization. These include real-time monitoring and smart control of water quality, feed intake and production equipment maintenance. In addition, digitization can help optimize the supply chain by bettering information flow between the farms, processing plants and distribution and increase processing plant efficiency by adding MES-type functionality.

A core challenge is creating a flexible yet robust data infrastructure that can collect data from a myriad of different sources, efficiently log and model the data and finally make it available for cloud-based applications.

Solutions – What we do:

MES functionality

Prediktor has 20 years of experience providing MES solutions to fish processing plants. Apis can greatly increase product quality and production efficiency through a unique production tracking system and advanced machine integration. This enables recipe management, statistical process control (SPC), Overall Equipment Effectiveness (OEE) and other MES functionality.

IOT Gateway

Prediktor’s Apis platform can act as an IOT Gateway that can collect time-series data from a large amount sources and stream it to the cloud via a single point of access. Apis can also receive data from the cloud and execute commands or forward the data to other systems. This makes Apis the perfect solution for companies that wish to quickly and easily set up a robust infrastructure that enables to take advantage of all the features available in cloud-based environments.

Information modelling

Apis supports information modelling via OPC UA Semantic modelling. Information modelling makes it much easier for Data Scientists or other users and applications to access asset data, as one can structure the data according to equipment in a system-based hierarchical fashion instead of the actual automation structure being used at the asset level. This makes it much easier to find and access relevant data as it is directly linked to the asset the data is relevant to.

With Apis, any number of information models can be implemented simultaneously. This means that one can have many models for different purposes – which is important as the same objects can have different meanings in different contexts.