High yielding animals’ health prediction is very important to maintain milk production and prevent loss of production. Tracking health of dairy cattle is too difficult and indeed need some tracking devices which can alert in their smart phone. The primary goal is to develop a prototypemodel for early detection of discomfort (symptoms/ disease) to predict health in dairy animals. The prototype model aims to study suitable physiological and behavioralparameters for monitoring the continuous state of health of animal. Long-term health monitoring of cattle is verydifferent from ambulatory human monitoring systems. The aggregation of physiology, behavioral and environmentaldata is the ideal way to assess state of animal health.
Livestock state-of-health determinations can be facilitated by the acquisition of a suite of physiologicaland behavioral parameters. Long term health monitoring is by wearable sensors, implanted devices, environmentalsensors, wireless data transmission, environmentally protected platforms, on board signal processing for noisereduction Physiological and Behavioral parameters: Core body temperature, Heart rate, Respiratory rate, Behavior(e.g., feed and water intake activity), Ambient temperature, Humidity, Wind patterns.
The primary goal is to identify the symptom /ailment which leads to disease prediction early in order to cut the production losses in cattle for monitoring continuous state of health of the animal. The aggregation of physiologic, behavioural and environmental data is the ideal way to assess the state of animal health. A set of design consideration’s must be addressed when to acquire long term, real time measurements’ in the field (Schoening et al, 2004). IOT based livestock monitoring system dedicated to the automated measurement of dairy cow health state (OlgierdUnold et al, 2020)
Objective:
To maximise animal performance and increase farm efficiency for sustainability and profit maximisation
Method:
The device to be designed should identify each cow and detect her signs of well-being by identifying signs of eating, rumination, standing, lying positionwalkingand inactive or abnormal behaviour to be recorded every 24 hours. The device will provide earlier and reliable health alerts oestrus, calving) that need more attention to treat health issues (Mastitis, Metritis, Repeat Breeding)) before they become problems by detection potential health issues earlier. Real time alert can be generated to help the farmers to take appropriate and quick decisions to avoid productivity losses. To develop a non-invasive wearable sensor system to determine the cattle health. To forecast the dairycattle health for herd heath monitoring To study the behavioural patterns of animals like movements, feed intake etc,monitoring the diseases to curtail the losses in productivity and profitability.
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Y. Ravindra Reddy
Associate Dean College of Dairy Technology
Sri Venkateswara Veterinary UniversityTirupati-517502
Email: yeddularavi88@gmail.com