Deliverables

The SYMBIOSIS project aims to obtain images of detected fish that are classified by type. The system will be deployed in depth of 5-22m in three different marine observatories, each for a period of a month. To explore the perfromance of the system on-the-fly, the images will be transmitted from the submerged unit to the surface unit. Due to the lack of cable connection (a cable may switch and turn), the communication will be performed acoustically. Yet, since the buad rate of the underwater acoustic communication is low (roughly 10kbps) and since the size of the captured images is on the order of 10kB, there is a need to compress the image.

Our imvestigations showed that regular image compression methods fail to reduce the size of the images to a resonable level from the respect of the acoustic modem. For example, the binary black&white image shown in Figure 1 is originally of size 16kB, and is compressed to size 12kB by a lossy JPG protocol (Black & White). For this reason, we turned to develop our own image compression technique that is spesifically tailored to the case considered.

Our method builds upon the understanding that, for the objective of learing of the functionality of the system, the spesific details of the fish in the image are no important. Instead, we would like to compress the image such that the general shape of the target in the image can be observed. This resambles the problem of segmentation, where only the general location of the target is of interest. We thus turn to segmentation techniques. Our methodology is throughly described in the following publications:

• A. Abu and R. Diamant, "Robust Image Denoising for Sonar Imagery", IEEE Oceans, Kobe, Japan, May. 2018 (posted on the project's database and website)

• A. Abu and R. Diamant, "Enhanced Fuzzy-based Local Information Algorithm for Sonar Image Segmentation", submitted to the IEEE Transactions of Image Processing

   

Media impacts

1. aquaculture.world - 20/06/2018  “Innovative autonomous system for identifying schools of fish”

2. aquahoy.com - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

3. bioengineer.org - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

4. brightsurf.com - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

5. diarioperspectiva.com - 20/06/2018 “Un equipo hispano israelí crea un sistema autónomo para identificar bancos de peces”

6. economiadehoy.es - 20/06/2018 “Innovador sistema autónomo para monitorizar bancosde peces”

7. Entornointeligente.com - 20/06/2018 “Innovador sistema autónomo para monitorizarbancos de peces”

8. fishbio.com - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

9. genphys.com - 20/06/2018 “Innovative autonomous system for identifying schools of fish” 

10. innovations-report.com - 20/06/2018 “Innovative autonomous system for identifying schools of fish”
11. pharmajobs.co - 20/06/2018 “Innovative autonomous system for identifying schools of fish”
12. medworm.com - 20/06/2018 “Innovative autonomous system for identifying schools of Fish”

13. pythom.com - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

14. scienmag.com - 20/06/2018 “Innovative Autonomous System For Identifying Schools Of Fish”

15. techsite.io - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

16. terkko.helsinki.fi - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

17. electronics360.globalspec.com - 20/06/2018 “Autonomous Tracking System Can IdentifyFish to Control Over-fishing”

18. spinoff.com - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

19. sciencecodex.com - 20/06/2018 “Innovative autonomous system for identifying schools of fish”

20. fis.com - 21/06/2018 “Innovative autonomous system for identifying schools of fish”

21. notasbit.com - 21/06/2018 “Innovador sistema autónomo para monitorizar bancos de peces”

22. noticiasdelaciencia.com - 21/06/2018 “Innovador sistema autónomo para monitorizar bancos de peces”

23. parallelstate.com - 21/06/2018 “Innovative autonomous system for identifying schools of fish”

24. mundoagropecuario.net - 26/06/2018 “Un innovador sistema autónomo para monitorizar bancos de peces”

25. biotech-spain.com - 27/06/2018 “Un innovador sistema autónomo para monitorizar bancos de peces”

26. digitaltrends.com - 28/06/2018 “Fishy surveillance system could keep tabs on ocean animals”
27. fondriest.com – 23/08/2018 “Autonomous SYMBIOSIS System Monitors Schools of Fish inReal Time”

This report presents six species of teleost (bony) fishes selected based on their high commercial importance, distinct behaviour or appearance and occurrence at either or both study locations of this project – the Eastern Mediterranean Sea and the Canary Islands: Albacore tuna (Thunnus alalunga), dorado (dolphinfish; Coryphaena hippurus), swordfish (Xiphias gladius), Atlantic mackerel (Scomber scombrus), Mediterranean horse mackerel (Trachurus mediterraneus) and Greater amberjack (Seriola dumerili).

First, each species is described in terms of its habitat and ecological niche (e.g., preferred temperature or depth range). A short account of their external features and morphology is then provided.

The schooling behaviour of each species is then summarised in the following section of each chapter; some fish in this report are known to aggregate in the vicinity of buoys or other floating objects at sea (such as the THEMO mooring in Israel), in which case the scientific literature on their behaviour may be biased to those structures. In other cases, information on the densities or vertical dynamics are derived from laboratory experiments, fishery records or long-term tagging programmes. As a result, a certain degree of inconsistency between chapters should be considered regarding the available data or their units of measurement.

In the following section of each chapter, an overview of distinct acoustic features such as target strength, swim bladder physiology, or other backscattering factors are presented when applicable.

Finally, swimming types and speeds are provided for either or both, sustained and burst modes, based on empirical laboratory of in situ measurements