International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
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CATTLE MEDICAL DIAGNOSIS AND PREDICTION USING MACHINE LEARNING Harsh J. Shah1, Chirag Sharma 2, Chirag Joshi 3 1,2,3-Member,
Young Engineer’s Club, Science Kidz Educare, Mumbai, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------prevent any outbreaks. This will not only reduce the need Abstract - Cattle Livestock Rearing is a major business in
for a large workforce, but also will provide a fool proof method to keep a check on livestock.
India with over 300 million cattle present in India. The total number of cattle throughout the world amounts to around 1 billion. The main products of this industry are milk and milk products, meats, and hides. The cattle unable to supply the former is used for transport and on farms for ploughing. The American Cattle Industry alone is worth about $77 billion. This makes the cattle sector one of the most valued industries in the world. Yet, there is not any significant system to keep health checks on these prized possessions except by workforce. In this age of reducing labour, excess workforce is expensive and does not always guarantee correct examinations. This void of a system causes annual losses of about $4-5 billion in the US alone. This can completely be avoided by using Deep Learning. With our Health Check System, we aim to surmount this challenge by capturing images of key areas in cattle and comparing them with a massive dataset of ill and healthy cattle to decide whether the animal is healthy or needs to be quarantined to prevent further spread of infection. This will provide a major boost to the cattle industry as it will narrow down the chances of a widespread infection causing losses with the help of Deep Learning.
1.1 Traditional Method Steps Involved in Traditional Infection Detection: BVD is diagnosed laboratories.
samples
tested
at
Body Temperature is kept under a strict vigilance and any fluctuations are noted. Milk Production is monitored. A sudden drop in production indicates infection. Nasal discharge and ocular discharge(eyes) are observed. 1.2 Problems Faced: 1. Low Infection Detection Rate. 2. Large Workforce needed.
Learning, Infection Detection, Disease Prevention
3. Low Disease Incubation Period.
1. INTRODUCTION
4. Risk of Outbreak. 5. Probability of Disease spreading to humans.
Livestock Rearing is a massive business today with almost a billion cattle existing throughout the world. The $77 Billion Cattle Industry in America has seen a steady decline in cattle population and has suffered losses due to extreme outbursts of diseases. In 1992, there were about 120,000,000 cattle in the US. Now, it has declined to about 92 million. In 2015, about 3.9 million cattle were lost due to either non-predator or predator causes. This amounts to about $3.7 billion in losses. These deaths are dominated by non-predator causes as they account for 98% of the deaths in cattle and 89% in calves. Majorly, Respiratory Diseases make up about 23.9% of the total non-predator deaths in cattle and 26.9% in calves. A major group of respiratory diseases is the Bovine Viral Diseases. The usual symptoms include face lesions, ocular discharge, and nasal discharge. By using a highly trained prediction model, we can ease the process of infection detection and
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on
Necroscopy findings are also considered.
Key Words: Cattle Rearing, Deep Learning, Machine
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based
Impact Factor value: 7.529
6. Human Intervention destabilises cattle 7. Symptoms difficult to observe.
2. SOLUTION The proposed solution is an easy-to-use software named “Cattle Infection Diagnosis,” which aims to ease the process of ensuring each cattle remains healthy. A setup of 3 cameras is installed to capture images of the designated area and send them over to the control centre aka the laptop. The three cameras are positioned at parts which are the most susceptible to display symptoms and this ensures that the best output is generated while using less resources. These body parts include the eye, the nose section, and the neck. Currently, cattle diagnosis requires dealing with hostile cattle which makes the process
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