Aquaculture is an important marine industry in Canada and one of the few enterprises offering employment in coastal communities. Aquaculture production in Atlantic Canada has led industry innovation via sensor networks for fish farms. However, without the appropriate data architecture and analytics, the value of these high-resolution data will achieve only a fraction of their potential in decision support, smart farming, and increased sustainability. The main goal of this project is exactly to develop a data architecture to efficiently store the large and constantly growing measurement data, and to build on top of this infrastructure a set of data analytics tools that can better support decision making within precision aquaculture.

In this context, the main objectives of this project are to:

• Create a data architecture to organize and archive existing data streams produced by fish farm sensor networks.
• Anticipate data sources from developing sensors (e.g. image based) and their inclusion in developing the data architecture.
• Provide a broad range of analytics to extract value from existing and future Big Data to understand larger trends and to forecast fish health, growth, mortality, and feeding.
• Develop protocols for data security, longevity, access, and quality assurance.

We recognize a future for fish farming where ocean technology provides critical input to decision support and management of fish husbandry, health, and welfare. Our goal is to make transformative changes in the capability of fish farmers to monitor the farm environment, and forecast conditions that compromise fish growth and health. We emphasize that these efforts are made to serve a broader context than just use of the coast for aquaculture. A variety of activities in the coastal zone (fishing, marine safety, tourism etc.) can benefit from a marine spatial planning approach that incorporates hardware/analytics platforms and a marine version of the Internet of Things.