Data for: Clinical Mastitis in Cows based on Udder Parameter using Internet of Things (IoT)

Published: 20 November 2020| Version 2 | DOI: 10.17632/kbvcdw5b4m.2
Contributors:
,
, Kartik M

Description

The data is collected from the udder of a cow to detect clinical mastitis. The four flex sensors and a temperature sensor are used to collect the udder data. Milk image is processed to find the quality of milk which also affects clinical mastitis. In the milk quality attribute, 0 indicates the normal milk and 1 indicates the abnormal milk. The data attributes are Cow_ID, Day, Breed, Month after giving birth, previous occurrence of mastitis, size of an udder (udder front left inhale and exhale limit, udder front right inhale and exhale limit, udder rear left inhale and exhale limit, udder rear right inhale and exhale limit), the temperature of a cow, the hardness of an udder from user input via a switch,  and pain due to swelling of an udder. There are two class normal cows indicated as 0 and mastitis cow indicated as 1. By analyzing the data using an efficient algorithm faster track of clinical mastitis in the cow is provided.  The SAC is designed to deploy flex sensors and temperature sensor, using raspberry pi and analog to digital converter data from the sensors are wirelessly collected.  As sensors are connected to the internet the IoT is in the picture to gather data. The IoT is used to monitor animal health so the concept is called the Internet of Animal Health Things (IoAHT).

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Categories

Animal Health Management, Machine Learning, Internet of Things, Mastitis, Deep Learning, Animal Health Monitoring System

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