The document discusses the necessity of data acquisition, processing, and management in livestock farming, emphasizing the need for mechanization and digitalization due to growing global food demands. It highlights the benefits of smart farming technologies, such as AI, IoT, and RFID systems, for enhancing production efficiency, minimizing labor costs, and improving animal welfare. Additionally, it covers various sensor technologies and data acquisition processes to optimize livestock management and maintain food security.

1. LIVESTOCK FARM DATA ACQUISITION-PROCESSING
AND MANAGEMENT
Hari Om Pandey
Livestock Production and Management
ICAR-IVRI, Izatnagar, Bareilly-243122, (UP), INDIA
hariomvet@gmail.com

2. q By 2050, the projected global human population will be
over 9 billion
q Land and water will become increasingly competitive
resources.
q Livestock producers will need to maximize production
sustainably
q This fuels incentives for responsible research and
innovation to solving pressing problems in livestock sector
q Hence need for mechanisation and digitalisation of
farming arises
Introduction

3. ØImprovement in livestock production, animals’ welfare, and
farming processes, allowing to ease monitoring operations that can
help farmers.
ØEra of advanced technologies where tremendous
amount of data is produced by multiple sources such
as sensors, devices, etc.
ØSmart Farming uses a large amount of connected
technologies producing also a huge amount of data in
order to maximize productions by reducing: human
efforts, environment impact and wasting natural
resources
Livestock data in smart farming

4. § Facts and statistics collected together for reference or analysis.
§ The quantities, characters, or symbols on which operations are performed by a
computer, which may be stored and transmitted in the form of electrical signals
and recorded on magnetic, optical, or mechanical recording media.
§ Things known or assumed as facts, making the basis of reasoning or calculation
§ Data requires interpretation to become information.
§ Data representing quantities, characters, or symbols on which
operations are performed by a computer are stored and recorded
on magnetic, optical, electronic, or mechanical recording media,
and transmitted in the form of digital electrical or optical signals.
§ Data structures can store data of many different types, including
numbers, strings and even other data structures.
Data ??

5. Livestock Farm Mechanization

6. optimizing
production efficiency
Precise work
Safe operations/
minimizing risk
reducing cost /Tackling
cost of labour
(25-35%)
conservation of
resources
BENEFITS OF MECHANISATION
minimizing environmental impact
optimizing quality of the crop
increasing profit
Advantages of Livestock Farm Mechanization
Precision agriculture, site-specific farming, site specific
crop management, prescription farming, and satellite farming
,,,
,,,, and better management
decisions (Sørensen et al. 2010, 2011; Rains and Thomas 2009;
Zhang et al. 2002).

7. Timeliness of operations
(15-20% less)
Precise
work/better
dicision
Minimizing
risk/Safe operations
Tackling cost of labour
(25-35%)
Input savings/
reducing cost
BENEFITS OF MECHANISATION
optimizing
production efficiency
/optimizing quality
Improved farmer dignity
More economic
returns/increasing profit
Advantages of Livestock Farm Mechanization
Precision agriculture, site-specific farming, site specific
crop management, prescription farming, and satellite farming
(Sørensen et al. 2010, 2011; Rains and Thomas
2009; Zhang et al. 2002).

8. Labour and time benefits
Source:FICCI,www.indiaagristat.com;
Financial evaluation of mechanization options,www.fao.org
• 15-20% saving of time
• More time for animal care
• Increased efficiency and per man productivity
• 25-35% labour saving
Use of power for agriculture (kW/ha)
Source of power and % shares
AgWorker Animal Tractor PowerTiller Diesel
Engine
Electric
Motor
Advantages of Livestock Farm Mechanization

9. Benefits of livestock farm mechanization
Production benefits: a case of milk
1960-61
20
million
tonnes
1980-81
31
million
tonnes
2000-01
80
million
tonnes
2018-19
187
million
tonnes
Early 1990s: Commercial
milking machines introduced
Milk
production
Source:Ministry of Agriculture and Farmer’sWelfare,GOI

10. Environmental benefits
1 tonne of paddy straw burning =
3 kg particulate matter, 60 kg CO, 1460 kg CO2, 199 kg ash and 2 kg SO2
• Decreased greenhouse gas emissions by feed waste management
• Green energy generation (dung + feed waste utilization)
1 tonne of paddy straw utilization = 3500 MJ clean energy
• Greenhouse gas emissions ~20% can be controlled through dung management
Source:Guidelines for crop residue
managementwww.agricoop.nic.in,2019
Source:https://www.thehindubusinessline.com/news/indias-methane-emissions-stabilising-conform-to-un-
report/article9912925.ece
Advantage of Livestock Farm Mechanization

11. Social benefits
§ Decrease in workload of hardworking farm women with advanced gender
sensitive machines
§ Use of advanced machinery like drones, AI and sensors attracts youth
§ Ergonomically safe farm machinery operation with lesser efforts – happy
farmers
§ Farmer has more time for a socio-economic life away from
laborious/drudgery prone work
Advantage of Livestock Farm Mechanization

12. Mechanization in livestock
Scope of mechanization: advanced livestock farms

13. Use of Artificial Intelligence (AI) in livestock farms
AI for health monitoring
• Motion detection sensors +AI system
• Movement behaviour of cattle noted byAI smart collars
• Data basedAI determinations: animal illness, ready to breed, or production status
• Heat stress, feeding efficiency and Estrus in cows also detected
• Robotic systems +AI + RFID tags aid in mechanized vaccination

14. Use of Drones, Robots and 3D printing
Drones
§ Locating and tracking cows
§ Monitoring of resting and grazing
§ Thermal imaging for health monitoring
Robots
§ Milking machines and automatic teat cleaners
§ Farm sanitization systems
3D printing
§ Printing of machine parts in dairy sector
§ Printing of animal products (even feed?)

15. Internet of Things (IoT) and blockchain in livestock farms
Internet of Things
§ Exchanging data between devices over the internet
§ Helps in smart and automated information gathering and merging.
§ Farm record keeping, management and biosecurity
§ Used in farm management information systems (FMISs) that
supports the automation of data acquisition and processing,
monitoring, planning, decision making, documenting, and
managing the farm operations.
§ Cloud based system, enables feed, waste management
Blockchain
§ Connecting supply chain: industry to consumers
§ Food security and traceability enhanced
§ Competitive edge to manufacturers
§ Can be easily applied for milk and milk products

16. Use of sensors and big data in livestock farms
Lying
Rumination Drinking
Moving Feeding
Heat Standing
• Real time sensors
• Wearable smart collars
• Data send through devices
• Data collection and evaluation centre
• Analysis for big data for animal trends
• Animal interaction and behaviour
monitoring

17. Data acquisition(DAQ) is the process of automatically importing data from an instrument/circuit into
a computer.
Sensor(eg .temperature to
voltage)
Amplification,filtering
Communication bridge between sensor
and computer
Through USB
DAQ acts as an interface between the signal from outside and the computer.
What is Data Acquisition
Data acquisition (commonly abbreviated as DAQ or DAS) is the process of sampling signals that
measure real-world physical phenomena and converting them into a digital form that can be
manipulated by a computer and software

18. q Sensor
q Signal Conditioning
qAnalog-to-Digital Converter (ADC)
qComputer with DAQ software for signal logging and analysis
Components for data acquisition system
Data Acquisition Systems

19. § Transducer-used for data handling; converts one form of energy to another but sensor directly
measures electrical quantities
§ Signal conditioning- Weak signals from transducer are converted to strong signals
§ Data conversion- Analogue converted to digital signals
§ Multiplexing-Several analogue or digital input signals are forwarded as a single output line.
Steps Involved In Data Acquisition

20. SENSORS
A sensor can be defined as a device which
measures or detects changes in its
environment and collects the data for
interpretation by a human or a machine.
§ The measurement of a physical phenomenon, such as the temperature,
the level of a sound source, or the vibration occurring from constant
motion, begins with a sensor.
§ A sensor converts a physical phenomenon into a measurable electrical
signal.

21. Sensor technologies based on the animal farming market :-
1. Sensors for feeding systems and precision milking robots
2. Hardware sensors such as camera or vision sensors
3. Infrared thermal imaging sensors to monitor body temperatures
to detect disease and stress
4. Facial recognition vision sensors
5. Radio Frequency Identification (RFID): Tagging with this allows
users to automatically and uniquely identify and track.
6. Pedometers
SENSORS

22. vPiggery:
Ø includes 2D and 3D cameras,
Ø microphones,
Ø thermal imaging,
Ø accelerometers,
Ø radio frequency identification (RFID),
Ø facial recognition and
Ø acoustic analysis
§ Drawback-Due to the curious nature of the pigs they are likely to chew devices that are
placed almost anywhere on the body or in the pen, making ear-tag RFID technology the
most promising solution
vPoultry- Infrared thermometers have been used to monitor the body temperature of
broilers.Acoustic analysis used to monitor change in chicken vocalisations.
SENSORS IN DIFFERENT SPECIES

23. Signal conditioning is the technique of making a signal from a sensor or transducer suitable
for processing by data acquisition equipment.
It is the first step of computerised data acquisition.
Signal Conditioning

24. § The output of most physical measurement signal conditions is an analogue signal.
§ It is necessary to convert this signal to a series of high-speed digital values so that it can be
displayed and stored by the data acquisition system.
§ As such, anA/D card orA/D subsystem is used to convert this signal.
Analog-to-Digital Converters (ADCs or AD Converters

25. Analog-to-Digital Converters (ADCs or AD Converters
Computer with DAQ software for signal
logging and analysis

26. Three types of data acquisition categories are:-
1) Image acquisition
TYPES OF DATAACQUISITION SYSTEM

27. 3) Video acquisition:
Allows the digital video recording.
The biometric data acquisition can be made upon request or can be scheduled by the system manager,
according to the researcher needs for monitoring the experiment or activity
2) one-dimensional signal acquisition
TYPES OF DATAACQUISITION SYSTEM

28. LIVESTOCK FARM DATA ACQUISITION

29. 3/17/23
INTRODUCTION
29
Mechanical methods:
•Tagging/Notching
•Branding
•Tattooing (Wismans,1999)
Biometric Methods:
• Nose Prints (Mishra,et.al.1994) (Battaglia, 2001)
• Iris Scanning
• Retinal imaging (Whittier et al.2003)
• DNA Profiling (Heaton et al. 2002)
Electronic Methods:
(Radio Frequency Identification)
(McAllister et al. 2000)
Methods of Identification

30. 3/17/23
30
— Not suitable for all species
— Can be replicated/counterfeit
— Branding-Vogue method (Welfare issues)
— Tattooing-need close observation
— Traditional animal identification are inferior
— Larger herd – poorer management practices
— Individual animal management is not possible
— Skilled labour problem for record keeping in govt. farms
(Trevarthen, 2007)
(Schwartzkopf-Genswein, 1998)
Demerits of Conventional Methods of Identification

31. 3/17/23
31
— Uses radio waves to link database with identification chips/tags
(Wu Hong-da, 2012)
Radio Frequency Identification
(RFID)

32. 3/17/23
RFID-TRANSPONDES
32
(Caja et al., 1999)
— Collars
— Ear tags
— Rumen bolus
— Implants
Transponder

33. 3/17/23
RFID-TRANSPONDERS
33
— Electronic collars - similar to neck chains
— Tag with an electronic number- readable
by a scanner.
— Electronic collars are easy to use
— Draw backs-
— Nuisance & choking
— Hooked on protrusions.
Electronic Collars

34. 3/17/23 RFID-TRANSPONDERS 34
Antenna
— Contain silicon chips and an
antenna
— Information stored is strictly
accordance with the ISO
standards
— Passive tags are lighter, less
expensive, and unlimited
life.
(Kampers et al. 1999)
e-ID Tags

35. 3/17/23 RFID-TRANSPONDERS 35
primary
alter
nate

36. 3/17/23
RFID-TRANSPONDERS
36
Balling gun.
§ Placed a balling gun
§ Irretrievable until the time of slaughter
§ Showed higher readability than visual tag (99.5 vs
89.8%). (Garin et al. 2005)
Electronic Bolus

37. 3/17/23
RFID-TRANSPONDERS
37
— Microchips -with antenna, under the skin
of animal
— Site- near the neck or near the base of the
ear
— Permanent and relatively painless to
implant.
The Kopordem farm atValpoi in SattariTaluk in North Goa has become the first farm in
India to use RFID microchips
Microchip implant

38. 3/17/23 RFID-TRANSPONDERS 38
ready-to-use sterile pack
injecting rfid tag in cattle reader shows unique ID
(http://pragra.wordpress.com/ )
Microchip implant

39. 3/17/23
RFID-READERS
39
q Fixed e.g. in milking parlour or abattoir
q Handheld, attached to a handheld computer (used in field)
(Blasi et al. 2000)
Reader

40. 3/17/23 RFID-READERS 40
— Greater range for reading tags (aprox100 cm)
— Direct network link with central database
— operations require individual identification
— Identifying cow entering milking parlor
— Automatic feeding
— Milk meters to record milk production
— Drafting gate operations
Fixed reader

41. 3/17/23
RFID-READERS
41
— Identification in the field
— Data from database can be copied to
this
— Read and display number on digital
screen
— Information viewed, recorded and
updated in field.
— Later uploaded to central database
Portable reader

42. 3/17/23
RFID-SOFTWARE
42
— Digital information storage
— Store individual data into a database
— Data entered manually or automatically
— Automating entry enables data to be stored reliably and
accurately
— Provides information required to make a decision or conduct an
action
Herdman was designed by Abdul Samad, Dean, Bombay vet college
(http://www.rfidjournal.com/article/view/7621)
Herd Management Software

43. 3/17/23 RFID-NETWORKS 43
Communication of devices b/w
one another, with RFID readers
and software.
— Wired
— Wireless
— Hybrid
(Trevarthen & Michael,2008)
Digital Network

44. 3/17/23
RFID-NETWORKS
44
— Wired:
— Cheaper than wireless network
— Reliability problems (rodents, general wear and tear)
— Wireless:
— Eliminates the need for cords/cables
— New devices are quite easy to introduce
— Hybrid:
— preferred where only some devices require portability
Cont…

45. 3/17/23
MECHANISM OF RFID
45
(Tan et al., 2007).
READER
Transponder
of reader
RFID Working Mechanism

46. 3/17/23
IMPLICATIONS
46
ØSimplified herd recording
ØAutomatic weighing
ØMilk production recording
ØFeeding Automation
ØReproduction
Management
ØHealth Monitoring
ØLivestock Insurance
ØComputerised storage of
breeding & veterinary record
ØAutomatic identification of
cows that need to be milked
separately.
ØBehaviour Study
ØTraceability (RFID)
ØAnimal movement tracking
ØHabitat Monitoring
RFID system is a key technology for the automation
Implication in Animal Husbandry

47. 3/17/23 RFID-NETWORKS 47
1
2
(http://www.dardni.gov.uk)
Electronic weighing

48. 3/17/23
IMPLICATIONS OF RFID
48
Sensor system for milking robot
Animal identification, Teat location, Monitoring
AMS function, Concentrate feeding, Milk quality & Composition
-Electrical Conductivity
-Temperature
-Chemical Composition &
-Color, SCC, Particle size
Recording of Milk

49. 3/17/23
IMPLICATIONS OF RFID
49
— Electronic Estrus Detection
— By body temperature variation
— Activity monitoring system –
Animal Activity appeared to rise by 30 to 200% (Smith and Saunders,
2005)
— Parturition Sensor
— Sense the body temperature and gives signal
Reproduction Management

50. 3/17/23
IMPLICATIONS OF RFID
50
— RFID helps:
— Monitor health of herd (e.g. physiological parameters, mastitis)
— Individual medication and vaccination records
— Tracking and segregating at early stages
— Leading to successful isolation and treatment
(Jansen & Eradus, 2009)
Health Monitoring

51. 3/17/23
RFID-NETWORKS
51
Transponder
In animal
Reader
(Handheld
or
Stationary)
DATABASE
(Trevarthen & Michael,2008)
Traceability System

52. 3/17/23
IMPLICATIONS OF RFID
52
Maintaining Database

53. 3/17/23
53
§ Quick, Easy, and Accurate access of information of
individual animal
§ Difficult to replicate /counterfeit
§ Efficient management
§ Time & Labour saving
§ Dynamic data storage
§ Data can easily view, analyze, manipulate & sort
§ Aid in taking immediate decisions
Advantages of RFID

54. Accurate body measurement of live cattle using three depth cameras and non-
rigid 3-D shape recovery
Ruchay, 2020
§ Body condition scoring of livestock is widely used as a subjective method
for assessing energy reserves and making management decisions for
livestock.
§ Recent advances in three-dimensional sensor technology provide
innovative tools for the design of automated contactless systems for
assessing the animal body condition.
§ An automated computer vision system capable to generate an accurate
three-dimensional model of live cattle.
§ The system is based on a non-rigid 3-D shape reconstruction utilizing data
from depth cameras.
§ The design methodology includes three Microsoft Kinect v2 cameras,
computer vision, signal filtering of point clouds, pattern recognition using 3-
D feature extraction techniques, and statistical analysis using point and
interval estimations.
§ Approach can serve as a new accurate method for non-contact body
measurement of

55. Accurate body measurement of live cattle using three depth cameras and non-
rigid 3-D shape recovery
Ruchay, 2020
The estimated body measurements are defined as follows:•
WH (Withers height) : vertical distance from the highest point of the withers to the ground surface
at the level of the forelegs.
•HH (Hip height) : vertical distance from the highest point of the hip bones to the ground surface at
the level of the hind legs.
•CD (Chest depth) : vertical distance from the back to the floor of the chest at the shallowest part of
the chest.
•HG (Heart girth) : circumference of the body at a point immediately posterior to the front leg and
shoulder and perpendicular to the body axis.
•IW (Ilium width) : distance between the outermost points of the ilium bones perpendicular to the
back.
•HJW (Hip joint width) : distance between the hip joint points perpendicular to the back.
•OBL (Oblique body length) : distance from the anterior extremity of the humerus to the posterior
internal extremity of the ischium.
•HL (Hip length) : distance from the outer point of the ilium bone to the posterior internal extremity
of the ischium.
•CW (Chest width) : distance between the posterior corner points of the shoulder perpendicular to
the back.

56. Accurate body measurement of live cattle using three depth cameras and non-
rigid 3-D shape recovery
Ruchay, 2020
Synchronized data captured by three Kinect
cameras: (a) RGB image from C1, (b) depth map
from C1, (c) RGB image from C2, (d) depth map
from C2, (e) RGB image from C0, (f) depth map
from C0.

57. The wireless DataAcquisition Systems have enabled the application of this technology in
retrieving data from animals
Integrated with modern information technologies such as sensors, communications,
computer and networks, data acquisition system can be connected with most common
sensors for environmental factors of livestock, such as air temperature and humidity, CO2,
and some other harmful gases, production disease, mastitis etc
.
The monitoring activities of animals, still demand interest to develop equipment for
data collection
APPLICATIN IN LIVESTOCK

58. 1.Identifying,predicting & preventing diseases using sensors
.
Sensors constantly monitor key animal health parameters such as movement, airquality, and consumption of
feed and fluids.
Abnormalities or deviations detected are helpful in prevention.
2.Detection of calving time
with an accuracy up to 90%
Changes in the ingestive behavior of dairy cows due to the onset of calving is the key basis for
detection.
3.Environment monitoring of buildings
When livestock are kept in enclosed buildings, impact of air quality, temperature, humidity, etc.
needs to be considered. Monitoring of environmental factors reduce the detrimental effects on the
health.
Examples in livestock farms includes such applications as-
EXAMPLE OF DATA ACQUISITION SYSTEM

59. 5. Feed and water intake determination
4. Estrus detection
Use of pressure sensitive sensors ,pedometers, collars are used for detection of estrus
6. Rumen sensors
helps measure pH, temperature, motility, pressure, etc. to discover new insights into nutritional
research,animal health and behaviour,animal emissions activity
EXAMPLE OF DATA ACQUISITION SYSTEM

60. With the development of the Internet and the cow feeding of intensive open and
extensible dairy farm, remote data acquisition systems which has the functions of
network data sharing, data publishing and remote monitoring is the trend of
times(Xiong etal,2005)
The monitoring activities of animals, still demand interest to develop equipment for
data collection. The wireless sensor network research advances have enabled the
application of this technology in retrieving data from animals and their employment
was evaluated by Kettlewell et al. (1997) and Silva et al. (2005).
EXAMPLE OF DATA ACQUISITION SYSTEM

61. The physical variables obtained from cow house and individual cattle such as environmental
temperature, humidity, harmful gas concentration, cow body temperature, milk yield, activity, feed
intake and so on is converted to digital signals (Xiaxhing Huo,2013)
EXAMPLE OF DATA ACQUISITION SYSTEM

62. Source-Remote Data Acquisition System at the dairy farm based on Data socket technology(Xiaojing Huo etal,2013)
Remote data acquisition system at the dairy farm

63. Measurement of Real-time environmental data in Livestock house
including carbon dioxide , ammonia gas conc, etc
Source:-Design of LH Environmental Perception System based on wireless sensor network(Weizheng Shen etal,2016)
Change ofAmmonia Gas Content in 24h

64. Data acquisition for feed weight consumed
A. System structure, B. Software structure
The camera was placed at 140 cm above the head .(Computer vision system for measuring individual cow feed
intake using RGB-D camera and deep learning algorithms Ran Bezena etal,2020)
DATA ACQUISITION FOR FEED CONSUMED
Depth and colour images of feed
were acquired from an RGB-D
camera, which was placed above
the feed table
These images were used to build a
CNN regression model for
weight intake prediction
Computer vision system for
measuring individual cow feed
intake using RGB-D camera and
deep learning algorithms

65. DAQ system aims to provide:-
Ø Flexibility and user-friendly configuration for
Ø Capacity for acquiring large number of data with ease of dynamic real-time analogue and
digital configuration
Ø Convenience of table and graphical displays,
Ø Integration of stand-alone instruments into the system
DRAWBACKS OF DAQ
ØThe development of the measurement system, especially the software, is a very
time consuming and expensive process.
ØDue to lack of knowledge, the adoption of data acquisition system among the
farmers is very scarce.

66. § Presently in some animal farms
§ Expected to extend in more livestock sites by further development both in
hardware and software to meet smart farming
§ In near future could revolutionise global livestock production and management
in a positive way.
§ Leads to improvement of the livestock:
ü production,
ü animals’ welfare, and
ü farming processes that will allow to ease monitoring operations that can help
farmers.
CONCLUSION

68. References:-
1. Remote Data Acquisition System at the dairy farm based on Data socket technology(XiaojingHuo,2013
2. Air Quality Monitoring and DataAcquisition for Livestock and Poultry Environment Studies Ji-Qin Ni Purdue UniversityAlbert J.
Heber Purdue University Matthew J. Darr Iowa State University, darr@iastate.eduTengT. Lim Purdue University ClaudeA. Diehl
Purdue University
3. Design and Implementation of Livestock House Environmental Perception System Based onWireless Sensor Networks
4. Weizheng Shen, Guanting Liu, Zhongbin Su, Rongyu Su andYu Zhang
5. Tech,A.R.B.,Arce,A.I.C.1A, Silva,A.C.S.1B and Costa, E.J.X. 2012.A wireless data acquisition system for cattle behavior
monitoring in zootechnics E-Science1ZAB-FZEA.Arch. Zootec. 61 (234): 175-185. 2012..
6. Computer vision system for measuring individual cow feed intake using RGB-D camera and deep learning algorithms Ran Bezena,b,
Yael Edanb, Ilan Halachmia,b
7. IoT sensors for smart livestock management(Wataru I wasaki etal,2019)
8. Recent advances in wearable sensors for animal health management
9. IoTTechnologies for Livestock Management:A Review of Present Status, Opportunities, and FutureTrends
(Bernard Ijesunor Akhigbe etal 2021)
LPM 513:Lecture1-Mechanisation in livestock by Dr.AyonTarafdar,Scientist,LPM Division