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The detection of milk contamination is a critical concern for ensuring food safety and public health. This work presents an AI-based milk contamination detection system integrated with advanced sensor technology. The collected data is processed and analyzed using sophisticated AI models, including Convolutional Neural Networks (CNN) and Gradient Boosting Machines (GBM), to accurately identify contamination. The proposed system is designed to operate autonomously, providing continuous monitoring and immediate alerts upon detecting any anomalies or potential contaminants. This proactive approach ensures timely intervention, reducing the risk of distributing contaminated milk to consumers. Experimental results demonstrate the effectiveness of the system in various scenarios, highlighting its robustness and scalability.
"AI Based Milk Contamination Detection With Sensor", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.b58-b67, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503109.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator