Expert System-Based Assessment for Vermicomposting Development

Authors

  • John Mark E. Nacionales College of Computer Studies, University of Antique, Sibalom, Antique, Philippines Author
  • Ma. Ydda M. Casuncad College of Computer Studies, University of Antique, Sibalom, Antique, Philippines Author
  • Joshua N. Daquila College of Computer Studies, University of Antique, Sibalom, Antique, Philippines Author
  • John Jowil D. Orquia College of Computer Studies, University of Antique, Sibalom, Antique, Philippines Author
  • Ryan Ercel O. Paderes College of Computer Studies, University of Antique, Sibalom, Antique, Philippines Author

DOI:

https://doi.org/10.69478/BEST2025v1n2a030

Keywords:

Vermicomposting, Expert System, Internet of Things

Abstract

Poor vermibed conditions are one of the contributors to the degradation of vermicompost which includes nutrition imbalance, where the essential nutrients are not distributed evenly, like nitrogen, phosphorus, and potassium, which contribute to the healthy growth of plants. It is essential to monitor the environmental conditions of the vermibed to maintain high-quality vermicompost. However, lack of expertise, geographical limitations, and the complexity of environmental factors are a few of the challenges and burdens in manual vermibed assessment. This study explores the development of expert system-based assessment for vermicomposting to address these challenges by automating data analysis, reducing manual assessment burdens, and minimizing human error that can help our farmers to vermicompost successfully. By considering key environmental parameters such as temperature, moisture content, and pH level, this ensures that they can have consistent and objective evaluations, real-time insights for adjustments to the bed, and enhanced accessibility to expert-level assessments regardless of their location or resources.

Published

2025-07-19

How to Cite

Expert System-Based Assessment for Vermicomposting Development. (2025). Business, Education, Social Sciences, and Technology, 1(2). https://doi.org/10.69478/BEST2025v1n2a030

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