A decision support system for herd health management for dairy farms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F24%3A100868" target="_blank" >RIV/60460709:41110/24:100868 - isvavai.cz</a>
Alternative codes found
RIV/60460709:41210/24:100868
Result on the web
<a href="https://cjas.agriculturejournals.cz/pdfs/cjs/2024/12/04.pdf" target="_blank" >https://cjas.agriculturejournals.cz/pdfs/cjs/2024/12/04.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.17221/178/2024-CJAS" target="_blank" >10.17221/178/2024-CJAS</a>
Alternative languages
Result language
angličtina
Original language name
A decision support system for herd health management for dairy farms
Original language description
Industrial dairy farms boast highly advanced health monitoring and disease diagnosis systems. But without easily accessible, user-friendly web platforms for real-time decision-making, most dairy farmers cannot proactively manage herd health management and optimize treatments based on disease prediction and prevention. To bridge this gap, we have developed a web application of a Decision support system (DSS) for dairy health management based on machine learning. The system architecture combines a Flask backend with a React frontend and scalable cloud data storage and includes preprocessing, data integration, predictive modelling, and cost analysis. DSS forecasts herd diseases with an accuracy 6.66 mean absolute error and 2.35 median absolute deviation across predictions. Its core predictive capabilities rely on long short-term memory (LSTM) neural networks to forecast disease progression from historical records and on a linear trend model to project cuts in treatment costs. The system calculates medication dosages and cost per disease, streamlines supplier selection, and simulates various treatment scenarios, thereby identifying high-cost diseases with potential savings. In other words, this DSS application processes disease and treatment data by incorporating veterinary records into advanced data analytics and neural networks, thereby predicting diseases, optimizing disease prevention and treatment strategies, and reducing costs. As such, this DSS application provides dairy farmers with a tool for strategic decision-making, veterinary treatment planning, and cost-effective disease management towards improving animal welfare and increasing milk yield.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
40200 - Animal and Dairy science
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Czech Journal of Animal Science
ISSN
1212-1819
e-ISSN
1805-9309
Volume of the periodical
69
Issue of the periodical within the volume
12
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
14
Pages from-to
502-515
UT code for WoS article
001311127800001
EID of the result in the Scopus database
2-s2.0-85213414199