Design and Implementation of an Integrated Sensor Network for Monitoring Abiotic Parameters During Composting


Naser A.G. Nawi N.M. Zakaria M.R. Kassim M.S.M. Mutalovich A.A. Nasir M.A.M.
November 2025Multidisciplinary Digital Publishing Institute (MDPI)

Sustainability (Switzerland)
2025#17Issue 21

Efficient composting is essential for sustainable organic waste management, yet conventional monitoring approaches are limited by single-parameter measurements and delayed response. This study presents an integrated sensor–AI framework designed to capture the interaction between thermal, chemical, and environmental factors governing composting. A distributed in-pile sensor network continuously measured temperature, moisture, and pH, while ambient parameters and gaseous emissions (O2, CO2, CH4) were recorded to validate process dynamics. Statistical analyses, including correlation and regression modeling, were applied to quantify parameter interdependencies and the influence of external conditions. Results showed strong positive associations between temperature, moisture, and CO2, and an inverse relationship with O2, indicating active microbial respiration and accelerated decomposition. The validated sensors maintained high accuracy (±0.5 °C, ±3%, ±0.1 pH units) and supported real-time feedback control, leading to improved nutrient enrichment (notably N, P, and K) in the final compost. The framework demonstrates a transition from static measurement to intelligent, feedback-driven management, providing a scalable and reliable platform for optimizing compost quality and advancing sustainable waste-to-resource applications.

composting , machine learning models , nutrient enhancement , real-time monitoring , sensor technologies

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Department of Agricultural Machinery and Equipment, Faculty of Agriculture, Tikrit University, Tikrit, 34001, Iraq
Department of Biological & Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, 43400, Malaysia
Institute of Plantation Studies, Universiti Putra Malaysia, Serdang, 43400, Malaysia
Department of Bioprocess Technology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, Serdang, 43400, Malaysia
Research Laboratory Innovative Water Treatment Systems, M. Auezov South Kazakhstan University, Taukehan Street 5, Shymkent, 16000, Kazakhstan

Department of Agricultural Machinery and Equipment
Department of Biological & Agricultural Engineering
Institute of Plantation Studies
Department of Bioprocess Technology
Research Laboratory Innovative Water Treatment Systems

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