Artificial intelligence (AI) plays important roles in vermicomposting processes by optimizing conditions through analyzing factors like temperature, moisture, and pH levels, predicting feeding rates based on waste composition and environmental factors, monitoring key parameters in real-time via AI-powered sensors, ensuring compost quality meets desired standards, automating tasks such as turning compost and adjusting conditions for increased efficiency, and providing decision support to operators for informed decision-making.
Dear Sunil Meghwanshi ,
Studies on developing strategies to predict the stability and performance of the composting process have increased in recent years. Machine learning (ML) has focused on process optimization, prediction of missing data, detection of non-conformities, and managing complex variables. This review investigates the perspectives and challenges of ML and its important algorithms such as Artificial Neural Networks (ANNs), Random Forest (RF), Adaptive-network-based fuzzy inference systems (ANFIS), Support Vector Machines (SVMs), and Deep Neural Networks (DNNs) used in the composting process.
Article Artificial Intelligence and Machine Learning Approaches in C...
Regards,
Shafagat
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