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Published in:

Volume 3 Issue 11
November-2016
eISSN: 2349-5162

Unique Identifier

JETIR1611002

Page Number

13-15

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Title

Early Stage Disease Detection Platform In Cattles

ISSN

2349-5162

Cite This Article

"Early Stage Disease Detection Platform In Cattles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.3, Issue 11, page no.13-15, November-2016, Available :http://www.jetir.org/papers/JETIR1611002.pdf

Abstract

Developing countries like India , Bangladesh ,Nepal and many more has dairy farming as one of the prior way of occupation .Dairy farm automation plays a crucial role in the increase of productivity in dairy production.Cattle animals are susceptible to many disease some of which can lower the productivity and lower the quality of dairy products and if not detected at an early stage can even lead to death of the cattle .This paper provides a methodology that how the use of machine learning can detect cattle diseases which can provide economical medical solution to place with scarce in medical facilities for farm animals .

Key Words

Artificial Neural Network, cattle Diseases, Feed forward network , HS, machine learning , mastitis ,pattern recognition ,Raspberry pi

Cite This Article

"Early Stage Disease Detection Platform In Cattles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.3, Issue 11, page no. pp13-15, November-2016, Available at : http://www.jetir.org/papers/JETIR1611002.pdf

Publication Details

Published Paper ID: JETIR1611002
Registration ID: 160499
Published In: Volume 3 | Issue 11 | Year November-2016
DOI (Digital Object Identifier):
Page No: 13-15
ISSN Number: 2349-5162

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Cite This Article

"Early Stage Disease Detection Platform In Cattles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.3, Issue 11, page no. pp13-15, November-2016, Available at : http://www.jetir.org/papers/JETIR1611002.pdf




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