Methods for Sensor Based Farrowing Prediction and Floor-heat Regulation: The Intelligent Farrowing Pen
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The document outlines a Ph.D. dissertation by Aparna U. focused on developing an automated system for monitoring sow behavior in farrowing pens to predict the onset of farrowing and optimize related management decisions, such as floor-heat regulation. This system utilizes sensors and algorithms to reduce piglet mortality by incorporating real-time observations and historical data. The study provides a comprehensive framework, including a Markov model to understand behavioral phases and improve prediction accuracy.
Methods for Sensor Based Farrowing Prediction and Floor-heat Regulation: The Intelligent Farrowing Pen
- 1. Prediction Estimation Decision Tool Final Remarks Methods for Sensor Based Farrowing Prediction and Floor-heat Regulation The Intelligent Farrowing Pen Ph.D. Dissertation Aparna U. Dept. of Animal Science Aarhus University Denmark 18 March, 2014 Aparna U. The Intelligent Farrowing Pen 1 / 42
- 2. Prediction Estimation Decision Tool Final Remarks Objective To develop and validate an automated system that monitors the pre-parturition behaviour of the sow in the farrowing pen, predicts the onset of farrowing would further help the farm manager to optimize the decisions related to parturition and post-parturition - e.g. optimal oor-heat regulation system by integrating several sensor information purpose to reduce the piglet mortality *Study was supported by The Danish National Advanced Technology Foundation Aparna U. The Intelligent Farrowing Pen 2 / 42
- 3. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm
- 4. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy
- 5. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters
- 6. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters
- 7. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm
- 8. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Prediction Algorithm
- 9. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Prediction Algorithm Estimation Algorithm
- 10. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Prediction Algorithm Estimation Algorithm Optimal Floor-Heat Regulation System
- 11. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Prediction Algorithm Estimation Algorithm Optimal Floor-Heat Regulation SystemAparna U. The Intelligent Farrowing Pen 3 / 42
- 12. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Prediction Algorithm Aparna U. The Intelligent Farrowing Pen 4 / 42
- 13. Prediction Estimation Decision Tool Final Remarks Gestation Period Behavioural States Mating Farrowing 115±2 days Aparna U. The Intelligent Farrowing Pen 5 / 42
- 14. Prediction Estimation Decision Tool Final Remarks Gestation Period Behavioural States Mating Farrowing 115±2 days Nest-Building Aparna U. The Intelligent Farrowing Pen 5 / 42
- 15. Prediction Estimation Decision Tool Final Remarks Gestation Period Behavioural States Mating Farrowing 115±2 days Nest-Building Resting Aparna U. The Intelligent Farrowing Pen 5 / 42
- 16. Prediction Estimation Decision Tool Final Remarks Gestation Period Behavioural States Mating Farrowing 115±2 days Nest-Building RestingBefore Nest-Building Aparna U. The Intelligent Farrowing Pen 5 / 42
- 17. Prediction Estimation Decision Tool Final Remarks Gestation Period Behavioural States Mating Farrowing 115±2 days Nest-Building RestingBefore Nest-Building 110 days Into Farrowing Pen Aparna U. The Intelligent Farrowing Pen 5 / 42
- 18. Prediction Estimation Decision Tool Final Remarks Farrowing Pen Number of sows observed: 64 Aparna U. The Intelligent Farrowing Pen 6 / 42
- 19. Prediction Estimation Decision Tool Final Remarks Sensor set-up at the pen level Number of sows observed: 64 Aparna U. The Intelligent Farrowing Pen 7 / 42
- 20. Prediction Estimation Decision Tool Final Remarks Online Recording of Sensor Observation for a Sow - An idea Water consumption Aparna U. The Intelligent Farrowing Pen 8 / 42 qq q q q q qqqq q qqq q q q q qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq q q q q qqq q qqq q q q q qqqqqqqqqqqqqqqqqqqqqqqqqqqqqq q qq q q q qqqqqq q qqq q q q qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq q q qq q q q qqqqq q q q qqqq 114 115 116 117 02468 days since mating waterconsumption(log) 17:30:00
- 21. Prediction Estimation Decision Tool Final Remarks Sensor observation for a sow - meanActivity q q q q q q q q q q q q q q q q q q q q q q q qq q q q qqq q q q qq q q q q q q q q q q q q q q q q q q q q q qq q q q q q q q q q q qqq q q qq q q q q q q q q q q q q q q q q q q q q q q q q q qq q q q q qq q q q q q q qq q qq qq q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q qq q q q qq q qqq q q q q q q q q q q q q q q q q q q q q q q q q q q q q qq q q q q q q q qq q q q q q q q q q q q q q q qq q q q q q qq q q q q q q q q q q q q q q q q q q q q q q q q q q q q qq q q q q qq q q q q q q q q q qq q q q q q q q q q q q q q q qq q q q q q q q q q q q q q q q q q q q qq q q q q q q q q q q q q q q q q qq q q q q q qq q q qq q q q q q q q q q q q q qq q q q q q q q q q q q q q q q q q q q qq q q q q qq q q q q qq q q q q q q q q q q q q q q q qq q q q q q q 345678910 Day of Farrowing:2009−01−15 03:47:09 Time Of Day meanActivity(logtransformed) Jan 06 Jan 08 Jan 10 Jan 12 Jan 14 case−1 Aparna U. The Intelligent Farrowing Pen 9 / 42
- 22. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F time line:- t0 t Tt: remaining time to onset of farrowing Stochastic process
- 23. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F time line:- t0 t Tt: remaining time to onset of farrowing Stochastic process ?Markov process
- 24. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F time line:- t0 t Tt: remaining time to onset of farrowing Stochastic process ?Markov process (ω1, ς1) (ω2, ς2) (ω3, ς3)
- 25. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F time line:- t0 t Tt: remaining time to onset of farrowing Stochastic process (ω1, ς1) (ω2, ς2) (ω3, ς3) Markov process semi-Markov process
- 26. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F time line:- t0 t Tt: remaining time to onset of farrowing Stochastic process (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang Markov process semi-Markov process
- 27. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 28. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 29. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 30. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 31. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 32. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 33. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 34. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 35. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 36. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 37. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 38. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 39. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 40. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 41. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 42. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang States into smaller divisions - Behavioural Phases 'phases' reect the time since mating
- 43. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang (m1, λ1) (m2, λ2) (m3, λ3) 'semi' Markov Process over phases Aparna U. The Intelligent Farrowing Pen 10 / 42
- 44. Prediction Estimation Decision Tool Final Remarks Farrowing process as a Markov Model Farrowing process - continuous time Before Nest-Building Nest-Building Resting F (ω1, ς1) (ω2, ς2) (ω3, ς3)Erlang (m1, λ1) (m2, λ2) (m3, λ3) 'semi' Markov Process over phases Phase-type Convolution of three Phase-type distributions Aparna U. The Intelligent Farrowing Pen 10 / 42
- 45. Prediction Estimation Decision Tool Final Remarks Farrowing and Prediction Process Farrowing process - continuous time Before Nest-Building Nest-Building Resting F 'Markov Model' Aparna U. The Intelligent Farrowing Pen 11 / 42
- 46. Prediction Estimation Decision Tool Final Remarks Farrowing and Prediction Process Farrowing process - continuous time Before Nest-Building Nest-Building Resting F 'Markov Model' Prediction process t0 tI t2 t3 - discrete time points Aparna U. The Intelligent Farrowing Pen 11 / 42
- 47. Prediction Estimation Decision Tool Final Remarks Farrowing and Prediction Process Farrowing process - continuous time Before Nest-Building Nest-Building Resting F 'Hidden' + 'Markov Model'αt : distribution of phases Tt :time to onset of farrowing ∼ PH(αt, S) Prediction process t0 tI t2 t3 - discrete time points Aparna U. The Intelligent Farrowing Pen 11 / 42
- 48. Prediction Estimation Decision Tool Final Remarks Farrowing and Prediction Process Farrowing process - continuous time Before Nest-Building Nest-Building Resting F 'Hidden' + 'Markov Model'αt : distribution of phases Tt :time to onset of farrowing ∼ PH(αt, S) Prediction process t0 tI t2 t3 - discrete time points Sensor Pr(Yt | Phaset) YI Y2 Y3 Aparna U. The Intelligent Farrowing Pen 11 / 42
- 49. Prediction Estimation Decision Tool Final Remarks Farrowing and Prediction Process Farrowing process - continuous time Before Nest-Building Nest-Building Resting F 'Hidden' + 'Markov Model'αt : distribution of phases Tt :time to onset of farrowing ∼ PH(αt, S) Prediction process t0 tI t2 t3 tN - discrete time points Sensor Pr(Yt | Phaset) YI Y2 Y3 Aparna U. The Intelligent Farrowing Pen 11 / 42
- 50. Prediction Estimation Decision Tool Final Remarks Prediction of Onset of Farrowing t0 tI t t + δ tI + Nδ ? Yt αt+δ: distribution of phases in the next prediction point Prediction of αt+δ At each prediction point, 1 calculates αt+δ using time transition (Markov chain) 2 updates αt+δ using the sensor information Aparna U. The Intelligent Farrowing Pen 12 / 42
- 51. Prediction Estimation Decision Tool Final Remarks Prediction of Distribution of Phases αt+δ Aparna U. The Intelligent Farrowing Pen 13 / 42 400 600 800 1000 0.000.020.040.060.080.10 Behavioural Phases probabilityofphases Before Nest−Building Nest−Building day−109.4
- 52. Prediction Estimation Decision Tool Final Remarks Prediction of Onset of Farrowing Prediction of αt+δ At each prediction point, 1 calculates αt+δ using time transition (Markov chain) 2 updates αt+δ using the sensor information Tt+δ: time to onset of farrowing ∼ PH(αt+δ, S) Statistical measures... Expected time to onset of farrowing Aparna U. The Intelligent Farrowing Pen 14 / 42
- 53. Prediction Estimation Decision Tool Final Remarks Prediction of Onset of Farrowing Prediction of αt+δ At each prediction point, 1 calculates αt+δ using time transition (Markov chain) 2 updates αt+δ using the sensor information Tt+δ: time to onset of farrowing ∼ PH(αt+δ, S) Statistical measures... Expected time to onset of farrowing Probability of onset of farrowing in 12 hours Aparna U. The Intelligent Farrowing Pen 14 / 42
- 54. Prediction Estimation Decision Tool Final Remarks Validating the Prediction - how??? Aparna U. The Intelligent Farrowing Pen 15 / 42
- 55. Prediction Estimation Decision Tool Final Remarks Validating the Prediction - how??? Aparna U. The Intelligent Farrowing Pen 15 / 42
- 56. Prediction Estimation Decision Tool Final Remarks Online Prediction Curve - an example Aparna U. The Intelligent Farrowing Pen 16 / 42 q 107 108 109 110 111 050100150 days since mating ETF(hours)
- 57. Prediction Estimation Decision Tool Final Remarks Warning periods - success Vs failure Aparna U. The Intelligent Farrowing Pen 17 / 42
- 58. Prediction Estimation Decision Tool Final Remarks Example of False-warning Period Aparna U. The Intelligent Farrowing Pen 18 / 42 qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq q q q q q q qq q qq q q q q q q qqq qqqqqqqqqq 112 113 114 115 050100150200250 days since mating ETF(hours)
- 59. Prediction Estimation Decision Tool Final Remarks Validating the Prediction Algorithm Sensor Sample True Warning Dur. Error size Warnings (hours) % Mean SD (hours) Water 38 21 11.7 2.2 3.4 Video 55 98 14.4 12.5 1.6 Water-Video 35 97 11.5 4.6 0.7 *threshold set at 12 hours Aparna U. The Intelligent Farrowing Pen 19 / 42
- 60. Prediction Estimation Decision Tool Final Remarks Validating the Prediction Algorithm Sensor Sample True Warning Dur. Error size Warnings (hours) % Mean SD (hours) Water 38 21 11.7 2.2 3.4 Video 55 98 14.4 12.5 1.6 Water-Video 35 97 11.5 4.6 0.7 *threshold set at 12 hours Aparna U. The Intelligent Farrowing Pen 19 / 42
- 61. Prediction Estimation Decision Tool Final Remarks Validating the Prediction Algorithm Sensor Sample True Warning Dur. Error size Warnings (hours) % Mean SD (hours) Water 38 21 11.7 2.2 3.4 Video 55 98 14.4 12.5 1.6 Water-Video 35 97 11.5 4.6 0.7 *threshold set at 12 hours Aparna U. The Intelligent Farrowing Pen 19 / 42
- 62. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm
- 63. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Estimation Algorithm Aparna U. The Intelligent Farrowing Pen 20 / 42
- 64. Prediction Estimation Decision Tool Final Remarks Estimation of HPMM Parameters by maximizing the likelihood function Aparna U. The Intelligent Farrowing Pen 21 / 42
- 65. Prediction Estimation Decision Tool Final Remarks Estimation of HPMM Parameters by maximizing the likelihood function Stochastic Expectation-Maximization algorithm (SEM algorithm) -iterative method Uses time of mating and farrowing information in addition to sensor information Phases are allocated by weighted sampling - Stochastic Aparna U. The Intelligent Farrowing Pen 21 / 42
- 66. Prediction Estimation Decision Tool Final Remarks Estimated Sojourn time distribution Behavioural State Duration Number Rate (hours) of (per hour) Mean SD Phases Before Nest-Building 751.20∗ 29.58 645 0.86 Nest-Building 17.02 0.80 458 26.91 Resting 0.53 0.22 6 11.40 Gestation period, days 117 1.2 1109 - *in addition to 85 days Aparna U. The Intelligent Farrowing Pen 22 / 42
- 67. Prediction Estimation Decision Tool Final Remarks Estimated Sojourn time distribution Behavioural State Duration Number Rate (hours) of (per hour) Mean SD Phases Before Nest-Building 751.20∗ 29.58 645 0.86 Nest-Building 17.02 0.80 458 26.91 Resting 0.53 0.22 6 11.40 Gestation period, days 117 1.2 1109 - *in addition to 85 days Aparna U. The Intelligent Farrowing Pen 22 / 42
- 68. Prediction Estimation Decision Tool Final Remarks Estimated Sojourn time distribution Behavioural State Duration Number Rate (hours) of (per hour) Mean SD Phases Before Nest-Building 751.20∗ 29.58 645 0.86 Nest-Building 17.02 0.80 458 26.91 Resting 0.53 0.22 6 11.40 Gestation period, days 117 1.2 1109 - *in addition to 85 days Aparna U. The Intelligent Farrowing Pen 22 / 42
- 69. Prediction Estimation Decision Tool Final Remarks Estimated Sojourn time distribution Behavioural State Duration Number Rate (hours) of (per hour) Mean SD Phases Before Nest-Building 751.20∗ 29.58 645 0.86 Nest-Building 17.02 0.80 458 26.91 Resting 0.53 0.22 6 11.40 Gestation period, days 117 1.2 1109 - *in addition to 85 days Aparna U. The Intelligent Farrowing Pen 22 / 42
- 70. Prediction Estimation Decision Tool Final Remarks Conditional Distribution of Sensor Observation Challenges with conditional model changing pattern with calender time - Behavioural Phases/States Aparna U. The Intelligent Farrowing Pen 23 / 42
- 71. Prediction Estimation Decision Tool Final Remarks Conditional Distribution of Sensor Observation Challenges with conditional model changing pattern with calender time - Behavioural Phases/States diurnal rhythm conditioned on the Phase/State Aparna U. The Intelligent Farrowing Pen 23 / 42
- 72. Prediction Estimation Decision Tool Final Remarks Conditional Distribution of Sensor Observation Challenges with conditional model changing pattern with calender time - Behavioural Phases/States diurnal rhythm conditioned on the Phase/State model selection Aparna U. The Intelligent Farrowing Pen 23 / 42
- 73. Prediction Estimation Decision Tool Final Remarks Conditional Distribution of Sensor Observation Challenges with conditional model changing pattern with calender time - Behavioural Phases/States diurnal rhythm conditioned on the Phase/State model selection dependency of the variables Aparna U. The Intelligent Farrowing Pen 23 / 42
- 74. Prediction Estimation Decision Tool Final Remarks Conditional Distribution of Sensor Observation Challenges with conditional model changing pattern with calender time - Behavioural Phases/States diurnal rhythm conditioned on the Phase/State model selection dependency of the variables dependency on the phases Aparna U. The Intelligent Farrowing Pen 23 / 42
- 75. Prediction Estimation Decision Tool Final Remarks Conditional Distribution of Sensor Observation meanActivity - sdActivity - grid activity Pr(Yt | Si ) ∼ N(µ (Y ) i , σ2 i (Y ) )ζ Simple linear model sine-cosine functions - harmonic variables Aparna U. The Intelligent Farrowing Pen 24 / 42
- 76. Prediction Estimation Decision Tool Final Remarks Conditional Distribution of Sensor Observations 0 5 10 15 20 56789 Mean Level of meanActivity Time (hrs) meanActivity q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q state−1 state−2 state−3 Aparna U. The Intelligent Farrowing Pen 25 / 42
- 77. Prediction Estimation Decision Tool Final Remarks Pattern of Water Consumption * * * * * * * * * ***** * *** ** *********** * ** * * * * * * * * * * * *** * ** * * * * * * * *** * ***** * ********** * ** * ** * * * * * * * * * * ** * * * * * * * * * ******** * **** * ******** * ** * * * * * * ** * ** ** * ** * * * * * * * * * * * ** * ***** * **** * * ******** * * * * * * * * * * * * * ** * * * ** * ** * * * * * * ****** * ****** * *** * * * *** ** * * * * * * * * ** * * * ** ** * ** * **** * ********* * *** * * * * * * * * * * * * * * * * * * * * * ** * * * * * ** * ** * * * * * * * * * * * *** * * * * * * * * * ** * ** * * * * ** ** ** * * * * * ** * *** * * * * * *** * * * * * * * * * ** * * * * * * * * * * * * * ** * * * * * * *********** ** **** * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ** * ****** ** * * ********** * * * * *** * * * *** * * * * * * * * * * ************** * * ****** * * ** * * * * * * ** * ** * * * * * * * * * * *** 106 108 110 112 114 116 118 02468 sinceMating LWater * * ** * * * * * ***** * *** ** *********** * ** * * * * * * * * * * * *** * ** * * * * * * * *** * ***** * ********** * ** * ** * * * * * * * * * * ** * * * * * * * * * ******** * **** * ******** * ** * * * * ** ** * ** ** * ** * * * * ** * * * * * ** * ***** * **** * * ******** * * * * * * * * * * * * * ** ** * ** * ** * * * * * * ****** * ****** * *** * * * *** ** * * * * * * * * ** * * * ** ** * ** * **** * ********* * *** * * * * * * * * * * * * * * * * * * * * * ** * * ** * ** * ** * * * * * * * * * * * *** * * * * * * * * * ** * ** * * * * ** ** ** * * * * * ** * *** * * * * * *** * * * * * * * * *** * * * * * * * * * * * * * ** * * * * * * *********** ** **** * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ** * ****** ** * * ********** * * * * *** * * * *** * * * * * * ** * * ************** * Aparna U. The Intelligent Farrowing Pen 26 / 42
- 78. Prediction Estimation Decision Tool Final Remarks Pattern of Water Consumption * * * * * * * * * ***** * *** ** *********** * ** * * * * * * * * * * * *** * ** * * * * * * * *** * ***** * ********** * ** * ** * * * * * * * * * * ** * * * * * * * * * ******** * **** * ******** * ** * * * * * * ** * ** ** * ** * * * * * * * * * * * ** * ***** * **** * * ******** * * * * * * * * * * * * * ** * * * ** * ** * * * * * * ****** * ****** * *** * * * *** ** * * * * * * * * ** * * * ** ** * ** * **** * ********* * *** * * * * * * * * * * * * * * * * * * * * * ** * * * * * ** * ** * * * * * * * * * * * *** * * * * * * * * * ** * ** * * * * ** ** ** * * * * * ** * *** * * * * * *** * * * * * * * * * ** * * * * * * * * * * * * * ** * * * * * * *********** ** **** * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ** * ****** ** * * ********** * * * * *** * * * *** * * * * * * * * * * ************** * * ****** * * ** * * * * * * ** * ** * * * * * * * * * * *** 106 108 110 112 114 116 118 02468 sinceMating LWater * * ** * * * * * ***** * *** ** *********** * ** * * * * * * * * * * * *** * ** * * * * * * * *** * ***** * ********** * ** * ** * * * * * * * * * * ** * * * * * * * * * ******** * **** * ******** * ** * * * * ** ** * ** ** * ** * * * * ** * * * * * ** * ***** * **** * * ******** * * * * * * * * * * * * * ** ** * ** * ** * * * * * * ****** * ****** * *** * * * *** ** * * * * * * * * ** * * * ** ** * ** * **** * ********* * *** * * * * * * * * * * * * * * * * * * * * * ** * * ** * ** * ** * * * * * * * * * * * *** * * * * * * * * * ** * ** * * * * ** ** ** * * * * * ** * *** * * * * * *** * * * * * * * * *** * * * * * * * * * * * * * ** * * * * * * *********** ** **** * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ** * ****** ** * * ********** * * * * *** * * * *** * * * * * * ** * * ************** * Aparna U. The Intelligent Farrowing Pen 26 / 42
- 79. Prediction Estimation Decision Tool Final Remarks Probability of Water Consumption at given time of day and state 0 5 10 15 20 0.00.20.40.60.8 time of day (hours) probabilityofdrinking q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q state−1 state−2 Aparna U. The Intelligent Farrowing Pen 27 / 42
- 80. Prediction Estimation Decision Tool Final Remarks Estimation of HPMM Parameters Challenges with conditional model changing pattern with calender time - Behavioural Phases/States diurnal rhythm conditioned on the Phase/State model selection dependency of the variables ? dependency on the phases ? Conclusion Duration of the Nest-Building state is similar to other studies Computational time - 26mins per iteration Aparna U. The Intelligent Farrowing Pen 28 / 42
- 81. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm
- 82. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Optimal Floor-Heat Regulation System
- 83. Prediction Estimation Decision Tool Final Remarks Overview of the Study HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Optimal Floor-Heat Regulation System Aparna U. The Intelligent Farrowing Pen 29 / 42
- 84. Prediction Estimation Decision Tool Final Remarks Floor-heat Regulation on Pen Level Time since onset of farrowing Floor-temperature −20 0 20 40 60 80 10 15 20 25 30 35 40 HeatOn HeatO Farrowing Malmkvist et. al. (2006)→ survival of one extra piglet per litter
- 85. Prediction Estimation Decision Tool Final Remarks Floor-heat Regulation on Pen Level Time since onset of farrowing Floor-temperature −20 0 20 40 60 80 10 15 20 25 30 35 40 HeatOn HeatO Farrowing Malmkvist et. al. (2006)→ survival of one extra piglet per litter
- 86. Prediction Estimation Decision Tool Final Remarks Floor-heat Regulation on Pen Level Time since onset of farrowing Floor-temperature −20 0 20 40 60 80 10 15 20 25 30 35 40 HeatOn HeatO Farrowing Malmkvist et. al. (2006)→ survival of one extra piglet per litter
- 87. Prediction Estimation Decision Tool Final Remarks Floor-heat Regulation on Pen Level Time since onset of farrowing Floor-temperature −20 0 20 40 60 80 10 15 20 25 30 35 40 HeatOn HeatO Farrowing Malmkvist et. al. (2006)→ survival of one extra piglet per litter
- 88. Prediction Estimation Decision Tool Final Remarks Floor-heat Regulation on Pen Level Time since onset of farrowing Floor-temperature −20 0 20 40 60 80 10 15 20 25 30 35 40 HeatOn HeatO Farrowing Malmkvist et. al. (2006)→ survival of one extra piglet per litter
- 89. Prediction Estimation Decision Tool Final Remarks Floor-heat Regulation on Pen Level Time since onset of farrowing Floor-temperature −20 0 20 40 60 80 10 15 20 25 30 35 40 HeatOn HeatO Farrowing Phase-(A) Phase-(B) Phase-(C)Malmkvist et. al. (2006)→ survival of one extra piglet per litter Aparna U. The Intelligent Farrowing Pen 30 / 42
- 90. Prediction Estimation Decision Tool Final Remarks Floor-heat Regulation on Pen Level Time since onset of farrowing Floor-temperature −20 0 20 40 60 80 10 15 20 25 30 35 40 HeatOn HeatO Farrowing Phase-(A) Phase-(B) Phase-(C)Malmkvist et. al. (2006)→ survival of one extra piglet per litter Aparna U. The Intelligent Farrowing Pen 30 / 42
- 91. Prediction Estimation Decision Tool Final Remarks Floor-heat Regulation on Pen Level Time since onset of farrowing Floor-temperature −20 0 20 40 60 80 10 15 20 25 30 35 40 Farrowing HeatOn HeatO Phase-(A) Phase-(B) Phase-(C)Aparna U. The Intelligent Farrowing Pen 30 / 42
- 92. Prediction Estimation Decision Tool Final Remarks How to choose threshold??? Aparna U. The Intelligent Farrowing Pen 31 / 42
- 93. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) Aparna U. The Intelligent Farrowing Pen 32 / 42
- 94. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) Aparna U. The Intelligent Farrowing Pen 32 / 42
- 95. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) belief time phase sensor obs. temperature decision heating cost t1 t2 U1 U2 Y1 C1 d1 H1 Aparna U. The Intelligent Farrowing Pen 32 / 42
- 96. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) belief time phase sensor obs. temperature decision heating cost t1 t2 U1 U2 Y1 C1 C2 d1 H1 Aparna U. The Intelligent Farrowing Pen 32 / 42
- 97. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) belief time phase sensor obs. temperature decision heating cost t1 t2 U1 U2 Y1 C1 C2 d1 d2 H1 Aparna U. The Intelligent Farrowing Pen 32 / 42
- 98. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) belief time phase sensor obs. temperature decision heating cost t1 t2 U1 U2 Y1 C1 C2 d1 d2 H1 H2 Aparna U. The Intelligent Farrowing Pen 32 / 42
- 99. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) belief time phase sensor obs. temperature decision heating cost t1 t2 t3 U1 U2 U3 Y1 Y2 C1 C2 d1 d2 H1 H2 Aparna U. The Intelligent Farrowing Pen 32 / 42
- 100. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) belief time phase sensor obs. temperature decision heating cost t1 t2 t3 U1 U2 U3 Y1 Y2 C1 C2 C3 d1 d2 H1 H2 Aparna U. The Intelligent Farrowing Pen 32 / 42
- 101. Prediction Estimation Decision Tool Final Remarks Floor-heat regulation System Partially Observable Markov Decision Process (POMDP) belief time phase sensor obs. temperature decision heating cost t1 t2 tF−1 tF tF+1 U1 U2 UF−1 UF UF+1 Y1 Y2 YF−1 C1 C2 CF−1 CF d1 d2 dF−1 H1 H2 HF−1 I Aparna U. The Intelligent Farrowing Pen 32 / 42
- 102. Prediction Estimation Decision Tool Final Remarks Approximate Solution Approximate POMDP solution Markov Decision Process - optimization for known phases Value Iteration Method Optimize the total expected utility w.r.t. phase number and oor-temperature Greedy Strategies Aparna U. The Intelligent Farrowing Pen 33 / 42
- 103. Prediction Estimation Decision Tool Final Remarks MDP look-up decision table Approximate POMDP Solution Floor-temperature Behavioural Phase ∆Q(opt) Decision(opt) 21 Phase-1 21 Phase-2 ... ... 21 Phase-1000 22 Phase-1 22 Phase-2 ... ... 22 Phase-1000 ... ... *∆Q(opt) : reward of heating Aparna U. The Intelligent Farrowing Pen 34 / 42
- 104. Prediction Estimation Decision Tool Final Remarks Approximating to POMDP Decision Vs Belief state for the given oor-temperature 400 600 800 1000 0.000.010.020.030.040.050.060.07 phases αt t=112 t=114 t=117.6 t=118.1 t=118.3 Aparna U. The Intelligent Farrowing Pen 35 / 42
- 105. Prediction Estimation Decision Tool Final Remarks POMDP Greedy Strategies QMDP - expectation over all the phases Aparna U. The Intelligent Farrowing Pen 36 / 42
- 106. Prediction Estimation Decision Tool Final Remarks POMDP Greedy Strategies QMDP - expectation over all the phases Most likely phase Aparna U. The Intelligent Farrowing Pen 36 / 42
- 107. Prediction Estimation Decision Tool Final Remarks POMDP Greedy Strategies QMDP - expectation over all the phases Most likely phase Random phase Aparna U. The Intelligent Farrowing Pen 36 / 42
- 108. Prediction Estimation Decision Tool Final Remarks POMDP Greedy Strategies QMDP - expectation over all the phases Most likely phase Random phase Voting Aparna U. The Intelligent Farrowing Pen 36 / 42
- 109. Prediction Estimation Decision Tool Final Remarks POMDP Greedy Strategies QMDP - expectation over all the phases Most likely phase Random phase Voting Random action Aparna U. The Intelligent Farrowing Pen 36 / 42
- 110. Prediction Estimation Decision Tool Final Remarks POMDP Greedy Strategies QMDP - expectation over all the phases Most likely phase Random phase Voting Random action *Above greedy strategies return almost identical rewards. Aparna U. The Intelligent Farrowing Pen 36 / 42
- 111. Prediction Estimation Decision Tool Final Remarks Robustness POMDP for Floor-heat Regulation Strategy Decision tool is robust to the changes in room temperature, Aparna U. The Intelligent Farrowing Pen 37 / 42
- 112. Prediction Estimation Decision Tool Final Remarks Robustness POMDP for Floor-heat Regulation Strategy Decision tool is robust to the changes in room temperature, energy supply, Aparna U. The Intelligent Farrowing Pen 37 / 42
- 113. Prediction Estimation Decision Tool Final Remarks Robustness POMDP for Floor-heat Regulation Strategy Decision tool is robust to the changes in room temperature, energy supply, mortality model Aparna U. The Intelligent Farrowing Pen 37 / 42
- 114. Prediction Estimation Decision Tool Final Remarks Robustness POMDP for Floor-heat Regulation Strategy Decision tool is robust to the changes in room temperature, energy supply, mortality model and price of a piglet Aparna U. The Intelligent Farrowing Pen 37 / 42
- 115. Prediction Estimation Decision Tool Final Remarks Robustness POMDP for Floor-heat Regulation Strategy Decision tool is robust to the changes in room temperature, energy supply, mortality model and price of a piglet POMDP strategy performed better than simple heuristic strategy especially when the room-temperature and energy supply was varied Aparna U. The Intelligent Farrowing Pen 37 / 42
- 116. Prediction Estimation Decision Tool Final Remarks Robustness POMDP for Floor-heat Regulation Strategy Decision tool is robust to the changes in room temperature, energy supply, mortality model and price of a piglet POMDP strategy performed better than simple heuristic strategy especially when the room-temperature and energy supply was varied POMDP does not suggest to turn on the heater if it is not benecial Aparna U. The Intelligent Farrowing Pen 37 / 42
- 117. Prediction Estimation Decision Tool Final Remarks Final Remarks... Aparna U. The Intelligent Farrowing Pen 38 / 42
- 118. Prediction Estimation Decision Tool Final Remarks Desired System - data management to decision HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Prediction Algorithm Estimation Algorithm Optimal Floor-Heat Regulation Strategy
- 119. Prediction Estimation Decision Tool Final Remarks Desired System - data management to decision HerdLevelComputer at the pen level Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Prediction Algorithm Estimation Algorithm Optimal Floor-Heat Regulation StrategyAparna U. The Intelligent Farrowing Pen 39 / 42
- 120. Prediction Estimation Decision Tool Final Remarks Future works... Studying the corners of the desired system Aparna U. The Intelligent Farrowing Pen 40 / 42
- 121. Prediction Estimation Decision Tool Final Remarks Future works... Studying the corners of the desired system Including farmer's observation on farrowing into model Aparna U. The Intelligent Farrowing Pen 40 / 42
- 122. Prediction Estimation Decision Tool Final Remarks Future works... Studying the corners of the desired system Including farmer's observation on farrowing into model Improving the methods and the calculation speed of Estimation algorithm Aparna U. The Intelligent Farrowing Pen 40 / 42
- 123. Prediction Estimation Decision Tool Final Remarks Future works... Studying the corners of the desired system Including farmer's observation on farrowing into model Improving the methods and the calculation speed of Estimation algorithm Similar decision support system for other applications Aparna U. The Intelligent Farrowing Pen 40 / 42
- 124. Prediction Estimation Decision Tool Final Remarks Take home message... Contributions Framework of an automated system starting from data management to decision The Intelligent Farrowing Pen Model for monitoring the pre-parturition behaviour of an individual sow Prediction of onset of farrowing - can directly calculate the expected time to farrowing for an individual sow Prediction model as the kernel of a decision support system Modelling sows diurnal rhythm in sensor observations Integrating information from several sensors Aparna U. The Intelligent Farrowing Pen 41 / 42
- 125. Prediction Estimation Decision Tool Final Remarks The Intelligent Farrowing Pen HerdLevelComputer Sensor Observations Herd Database Prediction Algorithm Warning Strategy CentralLevelComputer Historical Data Estimation Algorithm Herd Specic Parameters Heat Parameters Mortality Model Costs Optimization Algorithm Aparna U. The Intelligent Farrowing Pen 42 / 42