Artificial Intellegent in fisheries schema

AI in fisheries

1. ARTIFICIAL
INTELLIGENCE IN
FISHERIES
Credit Seminar
On
Major Advisor
Dr. M. L. Ojha
Asst. Professor
Present By
Mr. Chahat Sevak
M.F.Sc. 2
nd
Year (I sem) (Aquaculture)
Department of Aquaculture
College of Fisheries, MPUAT
Udaipur-313001 (Rajasthan)

2. DEFINITION
In computer science, artificial intelligence, sometimes
called machine intelligence , is intelligence demonstrated
by machine, in contrast to natural intelligence displayed
by human for the purpose of not only to identify caught
fishes but also to monitor dead zones and the current in
the sea and measure pollution.

3. ARTIFICIAL INTELLIGENCE
Making computers to think
Automation of activities like decision making and
learning like humans.
High productivity
Automatic operation
Facility controlled
Ecological and safety

4. TOOLS AND
APPLICATION OF
ARTIFICIAL
INTELLIGENCE
Data base management system – It is an data collection
system of fisheries like as item organized and in use.
Application software – AI software is managing the
data collected by systematically for use and compare
the data and for research.
Geographical Information system – production,
maintenance and updating of distribution maps of
marine species of commercial importance.

5. Satellite optical
E-logbook – This is log records which keep track of
catches(origin and volume) and gear used.
AI is used to reducing waste feed by using sensor to
detect hunger and by controlling release the right
amount of food

6. USES OF AI
1. Biomass estimation
2. Visual health and quality inspection
3. Pellet detection
4. Optimizing feed efficiency
5. Modeling the environmental impact of fishing
activity by regulate the fishing zones.

7. UMITRON CELL (Smart fish feeder)
UMITRON cell is a smart feeding system for aquaculture,
and the world’s first real time ocean based fish appetite
detection system.
UMITRON cell

8. • Robotic cages, called
aquapods, such as the
SeaStation by
InnovaSea.
•Aquapod is a free-
floating fish farm that
can accommodate
several hundred
thousand fish.
•Cages might seem
costly when compared
to other costs of
aquaculture
Robots farm our fish

9. Fish Seed Screening identification and selection of
healthy fish seed is very important in fish farming. Often
it become laborious and need to employ many workers for
screening of healthy fish seed. The Kindai University’s
Aquaculture Research Institute, Japan is using Microsoft
Azure machine learning studio to identify and remove odd
– shaped fish seed from the rearing
Fish Seed Screening

10. Fish seed screening

11. Vision based sensors on AI devices makes it possible to analyze
the swimming pattern, size, injuries etc on the cultured animal.
These data are preserved in order for comparison in future.
‘Xpertsea’ is an aquaculture innovation company that offers an AI
device called ‘Xpercount’ which applies machine learning and
camera to weigh, count, image and size shrimp in seconds. These
collected data are analysed for detecting the periodic health of
stock
Routine Check-up of Stocks

12. •Drones also offer applications for aquaculture
both above and below the water.
•Drones can be utilized for monitoring offshore fish
farms.
•Inspecting underwater cages for damage or holes.
•Apium Swarm Robotics use drones to survey the
ocean and provide analysis through the use of
sensor technology.
•Drones are also able to collect information(fish
stock analysis and environmental tracking) that
can be used to create algorithms that further
develop the technology or applications available
in the production of aquaculture
Drones in aquaculture

13. Drones in aquaculture

14. •Drones and robots use sensors to navigate
underwater and collect data such as water pH,
salinity, oxygen levels, turbidity and pollutants.
•Analysis of oxygen levels and water
temperature, even heart rate.
•eFishery, which uses sensors to detect the
hunger level of the fish and feed them
accordingly.
•AKVA Group builds an entire cage with
cameras, sensors, feeding and recirculation
systems for use in open ocean
Sensors for aquaculture

15. eFishery sensor technology

16. Artificial intelligence empowers
aquaculture decision-making
•Collecting most of their information from
sensors
•Sensing+Aqua technology to create predictive
analytics for enhanced data-driven decision-
making.
•A robotic fish known as Shoal uses AI, or
swarm intelligence (SI), to detect pollution
underwater.
•The robots are sent out as a group and must
be able to navigate their environment

17. Augmented reality (AR) adds
a new dimension to dives
•There is great potential for the use of AR in the
aquaculture industry.
•The U.S. Navy uses DAVD (Divers Augmented
Vision Display), which superimposes high-
resolution sonar imagery on a diver’s visual
world.
•With Augment Reality, divers find the health
status and a variety of environmental
parameters

18. Internet of Things
IOT is the technological revolution of computing
and communications that makes the robot capable
of performing tasks, as assigned by a remote user
or that transfers information obtained through
sensors to producers for analysis on smart phones.

19. •Monitoring DO levels
•Monitoring PH values
•Water management
•Send the SMS to farmer about the status of
these values.
•Farmer switches on/off the pumps, motors ,
aerators or the diffusers based on response.
•Monitoring fishes behaviors using Digital
image processing application.
Internet of Things

21. Image processing for monitoring
fishes
•Capturing the images of fishes with water proof
cameras.
•Enhancing the images using digital image
processing techniques.
•Observing the movements, populations of fishes,
their productivity, etc.

22. ADVANTAGES
1.Complete monitoring
2.Human touch
3.Whole value chain
4.Error reduction
5.Digital assistance
6.Reduce labour cost by one time investment.
7.Maintenance of AI system has high cost
too.
8.Another great disadvantage of AI is that, it
creates unemployment for the laborers.

23. DISADVANTAGES
1. High cost
2. Unemployment
3. Not improvement with experience
4. Construction cost increases
5. Requires more electric energy input

24. CONCLUSION
By the use of AI great strides in mechanized fisheries are
being made, full automation is still a long way off. But
fully investing in AI plus automation can significantly
produce more sea food to feed the growing population
while reducing the cost and environmental foot print.
Even though AI is developed, complete automation is not
available yet. Scientists are working on technology that
can work without human interference in then process.AI
aquaculture farms can be maintained and managed in a
much easier way with nearly 95% accuracy in operations.
Production of aquaculture goods can increase rapidly if
AI is used in a proper way.

25. REFERENCES
http://contentwisestep.com/advantagedisadvantage-intelligence
https://thefishsite.com/articles/a-practical-guide-to-using-ai-in-aquaculture
https://marel.com/fish/
https://thefishsite.com/articles/a-practical-guide-to-using-ai-in-
aquaculture
https://www.researchgate.net/publication/
222703947_Process_control_and_artificial_intelligence_software_for_aqua
culture
https://codebots.com/artificial-intelligence/the-3-types-of-ai-is-the-third-
even-possible
https://www.ship-technology.com/features/ai-in-shipping/

26. THANK
YOU…