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Intelligent Sensor Network and System Technologies for Fish Farming

Final Report Summary - SENSORFISH (Intelligent Sensor Network and System Technologies for Fish Farming)

In the project a strong network and increased collaboration between groups in Europe, China, USA and Canada working on intelligent sensor network and system technologies for fish farming has been established. The exchanges planned in this project helped the European researchers to connect better to the international partners active in this area and to execute international research on a high level. The expertise of the partners involved in this proposal ranged from the marine to inland fishery, from micro-electronics nanotechnology to wireless sensor network, from information & communication technologies to marine & fishery technologies. It was found out that the methodological approaches from different groups, which are sometimes complementary could be beneficial to achieve new scientific results and breakthroughs.
The project also strengthened the objectives of nationally funded research projects which are related to the project in some way, and widen the perspectives towards future calls at either the national or European level. For example, the consortium could acquire a new EU project FP7-ENV-2013-WATER-INNO-DEMO.
New information useful to different user groups (farmers, investors, managers etc.) could be collected and documented. Questionnaires were designed and distributed to 84 fish farmers from 16 provinces, and 16 interviews and on-the-spot investigation were carried out to collect and analyze the needs of fish farmer for an online monitoring and remote control in China.
With the information, the partners could explore advanced sensing principles and fabrication technologies for intelligent embedded sensors, as well as protocols of smart sensors for fish farming. New platforms, operating systems, storage schemes, and communication protocols for wireless sensor network for fish farming could be identified. For example newly developed mobile sensor platform C-Watch Remotely operated vehicle (ROV), which was used to measure 3D water quality in aquaculture areas, seas and channels. The information gain with the platform can be used for water quality monitoring, diagnosis, early warning, automatic control and decision making for fish farms. Furthermore, smart monitoring strategies using a minimum of hardware sensors and using soft-sensors to estimate unknown rates and concentration in the recirculation system for insight into the dynamics and for advanced (model-based) control were designed. Advanced (model-based) control strategies for safe, energy efficient and economically optimal fish farming were developed for aquaponic systems.
A project website was developed and is accessible through: http://www.sensorfish.eu
with some of the results of the project results and activities.
At one on the partners an image analysis method for counting the number of eggs and determining if the juvenile salmon had undergone smoltification and thereby were ready to be transferred from fresh water tanks into saltwater sea cages was developed.
During the sensorfish project period the Welfaremeter buoy has been deployed at three different farms in Norway (Figure 2). This has provided us in the project and the farmers with detailed data about the water environment which has been important both in the daily running of the farm (calculating feeding rates) and in long term planning (future layout of the farm).

To solve the common problems of aquaculture farms: ineffective information monitoring techniques and low level of online water quality monitoring and control. The China-EU Center for Information & Communication Technologies in Agriculture (CICTA), China Agricultural University has designed a remote monitoring system for aquaculture (Figure 3). The system for aquaculture adopts the intellisense technology, wireless communication technology, expertise information processing technology to realize the goal of Ecology, high yield, health and safety in aquaculture production.

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