Artificial intelligence has potential applications in animal husbandry to improve productivity and management. Current uses include automated milking machines, feeding systems, health monitoring technologies, and herd management software. However, adoption faces challenges like high costs, lack of technical support, and farmer uncertainty. Overcoming these barriers will require demonstrations, training, cooperative investment models, and coordination between public and private sectors.
Smarter production, nutrition, and waste management, as well as increased animal welfare and better education, have the potential to decrease the impact of livestock farming on our natural resources
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Presentation by Olatoye T. A. (FRIN, Nigeria) and Odularu G. O. (FARA, Ghana) for the Agrifood chain toolkit conference: Livestock and fish value chains in East Africa, Kampala, 9-11 September 2013.
Livestock production system for sustainable agricultural system course for natural resource management degree program.
Focuses on production system categorized by intensity and geography.
In India, as not much of attention is paid so far as to this important aspect- animal housing, we find different types of animal houses constructed without careful planning and designing.
Smarter production, nutrition, and waste management, as well as increased animal welfare and better education, have the potential to decrease the impact of livestock farming on our natural resources
Applications of remote sensing and geographic information systems technologie...ILRI
Presentation by Olatoye T. A. (FRIN, Nigeria) and Odularu G. O. (FARA, Ghana) for the Agrifood chain toolkit conference: Livestock and fish value chains in East Africa, Kampala, 9-11 September 2013.
Livestock production system for sustainable agricultural system course for natural resource management degree program.
Focuses on production system categorized by intensity and geography.
In India, as not much of attention is paid so far as to this important aspect- animal housing, we find different types of animal houses constructed without careful planning and designing.
Career Opportunities in Veterinary Science with special focus in India (Covers different professional fields/disciplines that a graduate can choose after completion of B.V.Sc&A.H).
Major economic traits of cattle and buffalopratee5
Selection and judging of the breeding stocks are the first and foremost steps to start with any breeding programme. For this, a no. of phenotypic and behavioral traits are taken into consideration. Breeding plans for cattle and buffalo should aim to meet the quantitative and qualitative demands of milk and meat in the country. From a practical standpoint, traits with a measurable or at least readily recognizable economic value are generally to be given the most emphasis.The economic traits are typically those that affect either the income obtained or the costs of production. So, a thorough understanding of economic traits of livestock is of utmost importance.
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I gave presentation on this topic. Actually, this topic was difficult to search and to concise but have lot of knowledge that's why I selected it for my presentation.
Artificial Insemination Experiences in EthiopiaILRI
Presentation by Emiru Zewudie (ALPPIS) to Ethiopian Fodder Roundtable on Effective Delivery of Input Services to Livestock Development, Addis Ababa, 22 June 2010
Role of livestock in national economy and population dynamics.
Provide livelihood to 2-3rd of rural community.
Also provides employment to 8.8% of the population in India.
20.5 million people depend upon livestock for their livelihood.
Livestock contribute to 16% to the income of small farm households.
Contributes to 4.11% of GDP and 25.6% of total agriculture GDP.
There are hundreds of diseases of livestock and pet animals that can be printed through properly used quality vaccines. This presentation summarises different types of vaccines used by veterinarians to control/ prevent diseases. The presentation enlists the vaccine-preventable diseases of pets and livestock, and also the different vaccines used.
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India is a hyperendemic country for many animal diseases and zoonotic diseases. Every year billions of rupees are spent on disease control, surveillance, monitoring, and vaccination against vaccine-preventable diseases. However, due to the failure of most animal disease control programs for one or other reasons India directly losses about 20 and 25 thousand crores annually due to endemicity of FMD & brucellosis, respectively. The presentation describes the pros and cons of different ongoing disease control programs going on in India.
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN AGRICULTURE
Agriculture is the backbone of India's economy. It is the principal
livelihood for over 58% of the rural households. But it faces difficult
challenges from sowing to harvest. Hence modernisation of agriculture is
most needed to address these challenges. In agriculture there is a quick
adaptation to AI in its various farming techniques where Artificial
Intelligence (AI) is one of the key areas of research in computer science with
its rapid technological advancement and vast area of application, AI is
becoming relevant very rapidly because of its robust applicability in the
problems particularly that cannot be solved well by humans. Such an area of
extreme importance is agriculture where about 80% of the population is
directly engaged on 159.7 million hectares of agricultural land. Such a
venture cannot run smoothly. Hence farming solutions which are AI
powered enable a farmer to do more with less, enhancing the quality, also
providing a quick GTM (go-to-market strategy) strategy for crops. A direct
application of AI (Artificial Intelligence) or machine intelligence across the
farming sector could act to be an apotheosis of shifting of traditional farming
practice today. AI powered agriculture, analysing its service in interpreting,
acquiring and reacting to different situation to enhance efficiency.
Artificial intelligence technology is supporting different sectors in
agriculture to boost productivity and efficiency. AI solutions are assisting to
overcome the traditional challenges in every field. Intervening of AI in
agriculture is helping farmers to improve their farming efficiency and reduce
environmental hostile impacts. The agriculture industry strongly and openly
grasped AI into their practice to change the overall outcome. AI is shifting
the way of food production where the agricultural sector's emissions have
decreased by 20%. Inculcating AI technology in agriculture is helping to
control and manage any uninvited natural condition.
Agriculture is the backbone of India's economy. It is the principal
livelihood for over 58% of the rural households. But it faces difficult
challenges from sowing to harvest. Hence modernisation of agriculture is
most needed to address these challenges. In agriculture there is a quick
adaptation to AI in its various farming techniques where Artificial
Intelligence (AI) is one of the key areas of research in computer science with
its rapid technological advancement and vast area of application, AI is
becoming relevant very rapidly because of its robust applicability in the
problems particularly that cannot be solved well by humans. Such an area of
extreme importance is agriculture where about 80% of the population is
directly engaged on 159.7 million hectares of agricul
Career Opportunities in Veterinary Science with special focus in India (Covers different professional fields/disciplines that a graduate can choose after completion of B.V.Sc&A.H).
Major economic traits of cattle and buffalopratee5
Selection and judging of the breeding stocks are the first and foremost steps to start with any breeding programme. For this, a no. of phenotypic and behavioral traits are taken into consideration. Breeding plans for cattle and buffalo should aim to meet the quantitative and qualitative demands of milk and meat in the country. From a practical standpoint, traits with a measurable or at least readily recognizable economic value are generally to be given the most emphasis.The economic traits are typically those that affect either the income obtained or the costs of production. So, a thorough understanding of economic traits of livestock is of utmost importance.
Improving breeding&reproductive performance of dairy animalsArab Khan
I gave presentation on this topic. Actually, this topic was difficult to search and to concise but have lot of knowledge that's why I selected it for my presentation.
Artificial Insemination Experiences in EthiopiaILRI
Presentation by Emiru Zewudie (ALPPIS) to Ethiopian Fodder Roundtable on Effective Delivery of Input Services to Livestock Development, Addis Ababa, 22 June 2010
Role of livestock in national economy and population dynamics.
Provide livelihood to 2-3rd of rural community.
Also provides employment to 8.8% of the population in India.
20.5 million people depend upon livestock for their livelihood.
Livestock contribute to 16% to the income of small farm households.
Contributes to 4.11% of GDP and 25.6% of total agriculture GDP.
There are hundreds of diseases of livestock and pet animals that can be printed through properly used quality vaccines. This presentation summarises different types of vaccines used by veterinarians to control/ prevent diseases. The presentation enlists the vaccine-preventable diseases of pets and livestock, and also the different vaccines used.
Animal Disease Control Programs in India.pptBhoj Raj Singh
India is a hyperendemic country for many animal diseases and zoonotic diseases. Every year billions of rupees are spent on disease control, surveillance, monitoring, and vaccination against vaccine-preventable diseases. However, due to the failure of most animal disease control programs for one or other reasons India directly losses about 20 and 25 thousand crores annually due to endemicity of FMD & brucellosis, respectively. The presentation describes the pros and cons of different ongoing disease control programs going on in India.
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN AGRICULTURE
Agriculture is the backbone of India's economy. It is the principal
livelihood for over 58% of the rural households. But it faces difficult
challenges from sowing to harvest. Hence modernisation of agriculture is
most needed to address these challenges. In agriculture there is a quick
adaptation to AI in its various farming techniques where Artificial
Intelligence (AI) is one of the key areas of research in computer science with
its rapid technological advancement and vast area of application, AI is
becoming relevant very rapidly because of its robust applicability in the
problems particularly that cannot be solved well by humans. Such an area of
extreme importance is agriculture where about 80% of the population is
directly engaged on 159.7 million hectares of agricultural land. Such a
venture cannot run smoothly. Hence farming solutions which are AI
powered enable a farmer to do more with less, enhancing the quality, also
providing a quick GTM (go-to-market strategy) strategy for crops. A direct
application of AI (Artificial Intelligence) or machine intelligence across the
farming sector could act to be an apotheosis of shifting of traditional farming
practice today. AI powered agriculture, analysing its service in interpreting,
acquiring and reacting to different situation to enhance efficiency.
Artificial intelligence technology is supporting different sectors in
agriculture to boost productivity and efficiency. AI solutions are assisting to
overcome the traditional challenges in every field. Intervening of AI in
agriculture is helping farmers to improve their farming efficiency and reduce
environmental hostile impacts. The agriculture industry strongly and openly
grasped AI into their practice to change the overall outcome. AI is shifting
the way of food production where the agricultural sector's emissions have
decreased by 20%. Inculcating AI technology in agriculture is helping to
control and manage any uninvited natural condition.
Agriculture is the backbone of India's economy. It is the principal
livelihood for over 58% of the rural households. But it faces difficult
challenges from sowing to harvest. Hence modernisation of agriculture is
most needed to address these challenges. In agriculture there is a quick
adaptation to AI in its various farming techniques where Artificial
Intelligence (AI) is one of the key areas of research in computer science with
its rapid technological advancement and vast area of application, AI is
becoming relevant very rapidly because of its robust applicability in the
problems particularly that cannot be solved well by humans. Such an area of
extreme importance is agriculture where about 80% of the population is
directly engaged on 159.7 million hectares of agricul
Artificial Intelligence is one of the emerging technologies in the field of agriculture which tries to simulate human reasoning in intelligent systems. It is making a revolution in agriculture by replacing inefficient traditional methods with more efficient AI based methods. AI is used in agriculture in various ways such as automation, robots, drones, soil and crop monitoring, and predictive analytics. This paper provides various applications of AI tools in agriculture. Matthew N. O. Sadiku | Sarhan M. Musa | Abayomi Ajayi-Majebi "Artificial Intelligence in Agriculture" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38513.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/38513/artificial-intelligence-in-agriculture/matthew-n-o-sadiku
Artificial Intelligence is an approach to make a computer, a robot, or a product to think about how smart humans think. AI is a study of how the human brain thinks, learns, decides and work when it tries to solve problems. And finally, this study outputs intelligent software systems. The aim of AI is to improve computer functions that are related to human knowledge, for example, reasoning, learning, and problem-solving.
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o Increased efficiency: Reduced manual labour, operational costs, improved resource allocation, and optimised workflows.
o Data driven decision making: Farmers can make more informed choices based on data-driven insights, leading to better pest and disease management strategies.
o Automation and predictive analytics: Automation of tasks like pesticide application has reduced human error and resource waste. Predictive analytics models optimise preventive measures.
o Monitoring: Digital solutions enable real-time monitoring by using cell phones.
o Knowledge sharing and innovation: Rapid sharing of knowledge, best practices, and information among farmers, researchers, and stakeholders is possible.
Also, digital transformation opens up avenues for communication among farmers, scientists, and government bodies, resulting in a multitude of indirect benefits: scientists gain better data access, governments improve their policy-making processes, and farmers attain increased crop productivity.
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Agriculture is the mainstay of Indian economy as about 60% of our population depends directly or indirectly on agriculture.Exploration of technology in digital world gave birth to a whole new field of making intelligent machines i.e. Artificial intelligence (AI). AI is making a huge impact in all domains of the industry. Every industry looking to automate certain jobs through the use of intelligent machinery. Factors such as climate change, population growth and food security concerns have propelled the industry into seeking more innovative approaches to protecting and improving crop yield. As a result, AI is steadily emerging as part of the Agricultural industry’s technological evolution. The automation in agriculture is the main concern and the emerging subject across the world. AI in agriculture not only helping farmers to automate their farming but also shifts to precise cultivation for higher crop yield and better quality while using fewer resources.Technological advancement in the future will provide more useful applications to the sector helping the world deal with various farming challenges used to be faced in traditional agricultural practices.
Modern farming has gone through a massive upgrade due to the evolution of the latest technologies. The tech innovations have given a complete overhaul to the agriculture industry.
This post highlights the most recent innovation in Agriculture that are likely to dominate in the future.
Read here for more details!
An overview about Artificial intelligence and its patterns, different tools, framework,industry examples, demo. The deviation from conventional approach.
Digital Disruption, Artificial Intelligence and the Future of JobsAbraham Samuel
This presentation was given at the HR-Tech Conference in Dubai in May 2018. It discusses the impact of artificial intelligence on the future of jobs:
- Digital Transformation: Hype or reality
- The impact of AI and Robotics in the workspace
- What jobs are likely to get displaced
- Can we retool our competencies to stay relevant
- How can HR leverage Digital Transformation
It contains video content too and would, therefore, be best viewed by downloading it and watching it as a PowerPoint Presentation.
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The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
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Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
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Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
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http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
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Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
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Artificial Inteligence in Animal Husbandry.pptx
1. USE OF ARTIFICIAL INTELLIGENCE IN
ANIMAL HUSBANDRY
1
Dr. Milind Nande
2. 2
C
O
N
T
E
N
T
S Introduction
What is AI
History of Artificial Intelligence
Current Global Scenario of Artificial Intelligence
Perspective of Artificial Intelligence
Application of AI in Animal Husbandry
Limitation of Artificial Intelligence
Conclusion
Strategies and Ways to Overcome Challenges
Status of Use of Artificial Intelligence in India
3. Introduction
Global demand for various livestock products will increase up to
70% in next 30 years.
More than half of the world population
is connected to internet through Smartphone.
Animal Husbandry Data are widely available but they are not
used to enough to inform on production relevant task.
In Medical Science potential Artificial Intelligence has been
developed from last four decades.
3
4. • AI is the intelligence exhibited by machine, rather than
human or animals. The intelligent agent perceive its
environment and take action to maximise success.
• It is not Man Vs Machine, however
it is synergy.
• Capability of machine to imitate
intelligent Human behaviour.
What is AI
4
5. Artificial
Intelligence
Machine
learning
Deep
Learning
• A techniques which enables machine to mimic human
behavior.
• ML is subset of AI, which use statistical methods to able
machine to improve with experience.
• DL is subset of ML, which make the computation of
multilayer neural network, that mimic the human brain .
5
6. Artificial Narrow
Intelligence (ANI)
Artificial General
Intelligence (AGI)
Artificial Super
Intelligence (ASI)
Also know as Weak AI.
It Involve applying AI
only to Specific task.
Ex: Alexa, Robtic
Milking Machine
Also Known as Strong
AI, It involve machine
that process the ability
to perform any
Intelligent task that
human can do.
Ex.: Self- driving car
It is a term referring to
the time when
capability of computer
will surpass human.
6
7. Can Machine Think ?
1950 :‘Alan Turning’ published a landmark paper about possibility of
creating machine thinking.
1956 : The Birth of AI - John Mccarthy coined the term “ Artificial
Intelligence” at Dartmouth Conference.
1960 : General Motor Developed Ist Industrial Robot to perform
automated die.
1973:Stanford University Introduced Experimental AI in Medicine.
CASNET Model – consultation programme,
MyCIN – provided list of potential bacterial pathogen and then
recommended Ab treatment.
History of Use of Artificial Intelligence
7
8. 2007: IBM Created Open Domain Questioning Answering System
‘WATSON’ won first prize in television game show ‘Jeopardy’ .
2011: Apple developed ‘Siri and Amazon Developed Alska a natural
language processor.
2015: DL applied to image processing that stimulate the behavior of
interconnected neuron of the human brain.
8
10. AI LANDSCAPE : GLOBALLY
85% of AI/ML World’s Start-up's are based in just 10 countries
NITI Ayog working on to
develop National AI Strategy
Document to define road map for
India.
Karnataka & Telangana Government
invested in creating Centre of
Excellence in Computer Science in
Bangaluru and Hyderabad.
Digital India (2017)
10
11. 1.39 billion population
Urbanization of 35.2%
1.10 billon mobile communication.
79.0% of Total population
624 million internet user.
45.0 % of Total population
06 hr. 36 Minutes of average daily time
spend on use of internet
11
12. A global study on 6,000 adults in the United States regarding consumer’s
understanding of the new technology.
Sr.
No
Respondent’s view Response
1 Understand the term
Artificial Intelligence.
72%
2 Think they use
technology with AI.
33%
3 Actually use an AI-
powered service or
device.
77%
Reality About Artificial Intelligence?
Sr.
No
Respondent’s view Response
1 Didn’t know that AI can solve
problem.
50%
2 Didn’t knew that AI is behind
the technology used in Google
Home and Amazon Alexa.
59%
3 Open businesses using AI. if it
makes life easier. Even if they
don’t understand.
73%
PERCEPTION V/s REALITY
12
13. Conduct research on 100 respondents on AI in Agriculture by asking
Questions on Implementation and Compatibility
AI technology can revolutionize the
traditional farming.
98%
2% YES NO
75%
21%
4%
Yes No Maybe
AI based smart farming can genuinely
help farmers to acquire better yield.
13
14. Perspective of artificial Intelligence
Moore’s Law
IA (Intelligent Augmentation)
Cloud Computing
Machine Learning
14
15. 1. Moore’s Law
• In 1965, Gordon E. Moore,
the co-founder of Intel, made
this observation that became
known as Moore's Law.
• The number of transistors on
a microchip doubles every
two years, though the cost of
computers is halved.
15
16. 2. Intelligent Augmentation
• IA’s concepts revolve around
augmenting human intelligence.
• Creation of knowledge bases, image
processing tools, natural language
tools.
• Virtual Assistants: Google’s: Google
Assistant
16
18. A. Electronic Sensor (Capturing)
• A sensor is a device that detects minute changes in
its environment and sends the information to
a computer processor.
• Measuring Physical, Chemical, Biological
and Environmental Parameters.
Types of sensor
1. Temperature Sensor
2. IR Sensor
3. Ultrasonic Sensor
4. Touch Sensor
5. Light Sensor
6. Gas Sensor
18
19. B. Big data (Processing)
• It is the on-demand
availability of computer
system resources, especially
data storage and
computing power, without
direct active management
by the user.
• Google cloud – It is a suite
of public cloud services
offered by Google.
19
20. 4. Machine Learning (Analyzing)
• Machine learning is the study of
computer algorithms.
• It improve automatically through
experience and by the use of
data.
• Ex: Sensor base technology at
animal farm
Machine learning use in:.
– Email Spam and Malware
Filtering.
– Online Customer Support.
– Search Engine Result Refining.
– Product identification at Amazon
20
22. Condition Algorithms Parameter detected
Mastitis Bag of Words (BoW), Gradient
Boosted Tree (GBT)
Somatic Cell count, Electrical
conductivity
Lameness Fog Computing, Classification
and regression Tree (CART)
Leg Movement, Neck Movement
and Image /video data
Postpartum Disease Random Forest Algorithm
(RFA)
Lactose yield, protein production
and milk yield
Algorithm use for prediction of disease condition in AH
22
23. Artificial Intelligence Use in Animal Husbandry
1. Milking Machine
2. Automated Feed
Pusher
3. Manure Removal
Robot
1. Animal Tracking System
2. Rumination Sensor
3. Activity Sensor
4. Electronic Ear Tag
5. Neck Collar Sensor
6. Camera Monitoring
7. Concentrate Feeding
Station
1. Disease detection
2. Oestrus detection
3. Data transfer into
herd management
system.
4. Concentrate feed
allocation depending
on milk yield
Machine Learning
Electronic Sensor
Electronic Data Processing
23
24. Automatic Milking System
• The Automatic Milking Machines have
Cups with Sensors that can be
attached individually to cows’ teats.
• The machines can also automatically
Clean and Sanitize the teats.
• Machines can also identify Colour,
Impurities, and Quality of milk.
• If the milk is not fit for human
consumption, it is diverted to a
separate container.
24
25. Automatic robot feeder
Automatic robot feeder used
to feed concentrate of mixture
of roughages as per need of
farm animal.
A scraper robot used to clean slatted
floors.
It pushes and scrapes tirelessly, easily
traversing long passage and ensure
clean, slurry-free surfaces.
25
26. survey was conducted on 1355 dairy farmer’s to identify the interest
and concerns dairy farms when they transitioning from
conventional milking systems to AMS
Sr. No Concern Responses
1 Involved in dairy farming for > 20 yr. 74%
2 Expressed interest in transitioning to an
AMS
38%
3 A logistic regression showed that Higher Education and Larger Herd-
size influenced (P < 0.05) interest in AMS,
26
27. A survey among 107 farmers Recently invested in an automatic
milking (AM) system
Sr. No. Respondents view Percentage
1 Most farmers see themselves as a fine tune AM 43%
2 Farmers claim to be labour savers. 64.3%
3 Why they have installed an AM-system
• Social cause 67.3%
• Economic cause 32.7%
4 Implications on leisure and quality of life
• agree to spend more time with their family 86%
• quality of life of their family has improved. 75%
27
28. Drones
• Farmers Kept a manual vigilance.
whenever the livestock moves out of the
farm for grazing.
• Drones can keep track of the cattle and
herd them back from fields to barns.
• Drones can also capture the pictures of
pasture areas.
• Some companies such as TRITHI
Robotics, Dronitech, Sagar Defence
Engineering, DJI
Enterprise and Sunbirds have made
Initiative in building commercial drones in
india.
28
29. Smart Precision Farming
It is use to measure Physiological, Behavioural and Production indicators of individual
animals to improve management strategies, profitability and farm performance.
Use of PDF technologies that makes farmers less
dependent on human labour, supports them in their
(daily) management, and helps them to improve their
farm profitability
PDF monitor health and production and translate the
results in useful information.
29
30. Walking Activity
Pedometer allows monitoring of both Walking and Milking activity in dairy
farm.
Used to observe daily movements, including
milking, eating, standing, and lying, and can
detect changes in this measurement of activity.
Pedometer predicted lameness earlier than the
appearance of the clinical signs. By correlating
pedometric activity (PA) with clinical cases of
lameness.
30
31. Milk yield and Milk Electrical Conductivity
Significant changes in milk yield can be observed as early as 10 days
before diagnosis of an adverse health effect.
Electrical conductivity along with other information (e.g. milk yield, milk
flow, number of incomplete milking) may increase accuracy of detection
mastitis.
31
32. Feeding Behaviour and Intake
Found that healthy animals spent more time at the
feeder than morbid animals, and a greater percentage
of healthy animals visited to feeder immediately after
feed delivery.
Found that changes in short-term feeding behaviour of
dairy cows occurred with the onset of the health
disorders like ketosis, acute locomotory problems, and
chronic lameness.
Observation of feed intake and production by monitoring activity at the
feeder.
32
33. Motion Activity Instrumentation
Instrumentation like Electronic collar, Ear Tag, Pedometer that
consists of sensors that shows variables related to the status of
animal.
Revealed that, Animal Status is estimated by
the history of recent time of position, activity,
temperature, live weight and other
physiological parameter of all individuals in the
herd.
33
34. Animal Behavior Sensors:
Sensors are necessary for a detailed record of
behavior of animals.
Sensors measuring
Head Angle & Head Acceleration
Leg Acceleration & Steps
Swallowing & Jaw Movements,
Biting and Chewing
Sounds, Weight, Heart rate, Core
Temperature etc.
34
35. 35
Rumen pH and Rumen Temperature
Continuous monitoring of ruminal pH is
possible through wireless telemetry which
has the capacity to accurately detect
subacute ruminal acidosis
Rumen sensors to measure
Temperature, pressure/motility and pH in
rumen.
Measurement of Ruminal pH is a reliable and
accurate diagnostic test for Ruminal Acidosis
36. Body Temperature
The largest potential benefit of employing an
automatic body temperature monitoring system
in a dairy farm would be in early detection of
disease, illnesses, or disorders .
body temperature is the first and foremost sign
to be detected during any disorders.
36
37. 37
Estrus Detection System
3D-accelerometers are used to detect estrus
and calving.
The detection of cows in heat has become more
and more difficult due to changes in animal
behaviour and management.
38. Farm Management System
Farmers can track, monitor and manage
Health, Nutrition, Behaviour, Milking
Frequency, Milk Production and activity
level in real-time.
Smart animal trackers can be implanted
in the cattle’s Ears, Tail, legs, Neck or any
part of the body.
Smart cattle health tracking devices are :
Herdman, SmaXtec, Moocall, Smartbow.
38
39. Geographic Information System (GIS)
GIS integrates hardware, software, and data for
capturing, managing, analyzing and displaying
all forms of geographically referenced
information.
reported that GIS predict the possibility of
transmission of infectious diseases between
herds.
Surveillance and monitoring studies, identification and location of
environmental risk factors for disease prediction, prevention and control.
39
40. Developed by NDDB, Anand
•Android tablet-based field IT application.
•Capturing of real time reliable data on
breeding, nutrition and health services
delivered at farmer’s doorstep.
•Send messages to farmers, providing
appropriate advice regarding their animals.
•Workout report are available to the
managerial team and other decision
makers for analysis.
National Livestock Identification Scheme
40
Current Status of Use of Artificial Intelligence in
Dairy Farming of India
41. Private Dairy Farm
Chitale Dairy in Pune.
Mukhiya Dairy, Kanodar, Palanpur, Gujrat.
Lakshya Dairy in Haryana.
Kopordem Farm at Valpoi in North Goa.
•Mumbai Veterinary College did research on Herdsman Software
41
Adopted RFID based animal identification and farm
automation management system.
RFID based animal identification, data recording
and complete farm management system applicable
for small holding dairy farmers at low cost.
42. • Adoption rate depend on various factors like farmers Age, Level of formal
Education, Farm size, types of production and overall expenses' on information and
use of technology.
• Small herd size and heavy investment in technology increase the cost of input .
• Poor availability of AI tools and computer illiteracy of farmers contribute to non-
adoption of technology.
• Unavailability of local technical expertise for interpretation and decision making.
• Different skills will be required the farmers adapt AI technologies.
• Farmers have uncertainty regarding investment in technologies due to a lack of
information.
• Lack of success stories, demonstrated effects,. leading to reduction in the interest
of the farmers to adopt the technology.
Limitation of Artificial Intelligence in AH
42
43. Strategies and Ways to Overcome Challenges
• Creation of Multidisciplinary Teams
involving scientists in various fields, like
dairying, engineers, manufacturers and
economists to study the overall scope of
artificial intelligence.
• For costly AI tools, formation of farmers’
cooperatives, self help groups or
community organizations would be one
of the solutions.
43
44. • Provide complete technical backup support to
the farmers to develop a models, which can be
replicated on a larger scale.
• Promote the technology for progressive
farmers who have sufficient risk bearing
capacity since the technology requires capital
investment.
• Effective coordination among the public,
private sectors for essential for implementing
new strategies to achieve fruitful success.
44
45. Demonstration
Method Demonstration: it is single practice
demonstration and use to show the technique
of doing things or carry out new practices.
Result Demonstration: this method is based on
seeing is beliving. this method is use to show
the superiority of practices
Creating Awareness through Right Extension Approaches
45
46. Training Programme
• It is a process by which individuals are
helped to acquire certain specific skills
related to a given set of operations in
certain specific context only.
• In Study tour : A group of interested
person accompanied and guided by
one or more extension agents moves
out their neighbourhood to study an
learn significant improvement in farm.
46
47. Mass Media
• Mass media means the technology that is
intended to reach a mass audience.
• Current commercially AI used
Companies in dairy industry
47
48. Conclusion
• Artificial Intelligence in Animal husbandry is in its Initial Stage but it has
tremendous opportunities for improvements in individual animal and herd
management on dairy farms.
• Progressive farmers and professional can adopt AI on a limited scale to
shows potential for raising yields and economic returns on fields with
significant variability.
• Additional research needs to be undertaken to examine the adoption
process for not only successful adoption of technology but also to solve
the issues associated with the technology adoption.
48
Perform a task that is normally required intelligence, speech recognition, visual perception, decision making and translation between language.
https://towardsdatascience.com/understanding-the-difference-between-ai-ml-and-dl-cceb63252a6c
https://towardsdatascience.com/artificial-intelligence-in-mechanical-engineering-a9dd94adc492 . a machine learning technique that is inspired by the way a human brain filters information, it is basically learning from examples.
https://docs.microsoft.com/en-us/azure/machine-learning/concept-deep-learning-vs-machine-learning
innovation will continue with lower cost for IoT and computing. After its decades-long run defining innovation in computing, Moore's Law may be moving toward its end in 2021.
https://ap.fftc.org.tw/article/1615
Social reasons: to decrease labour intensity, to spend more time on other activities, to have more flexibility, health problems, challenge, to improve social life, animal welfare
• Economic reasons: to increase milk production, to produce less manure, to have more management information, to improve cow and udder health, to expand the farm, because a labour unit has fallen away, to milk more then twice a day, because the old stable had to be replaced, to optimise labour, because it is difficult to find hired labour.
precision dairy farming (PDF) aims to manage the basic production unit in order to exploit its maximal production capacity.
It can also be defined as information and technology based farm management system to identify, analyze and manage variability within farm management for optimum farm performance, profitability and sustainability