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March 3, 2026
An IoT and Machine Learning Approach for Predicting Air Quality Parameters in Poultry Houses
SR
Saif Ahmed Rawdhan
University of Baghdad
MA
Mahmoud A. Abdelhamid
Ain Shams University
AA
ashrf anwer
Ain Shams University
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Key Points
Air quality parameters can be effectively predicted using machine learning techniques.
The integration of IoT devices enhances the accuracy of environmental monitoring in poultry houses.
Data from these systems can lead to better management of poultry health and productivity.
Utilizing these technologies may significantly reduce risks related to air quality in farming.
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An IoT and Machine Learning Approach for Predicting Air Quality Parameters in Poultry Houses | Synapse
Cite This Study
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Rawdhan et al. (Tue,) studied this question.
synapsesocial.com/papers/69a761fcc6e9836116a30146
https://doi.org/https://doi.org/10.1007/s42853-026-00300-8