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Title Advanced Predictive Analytics For Bio-Waste Management Using Yolov8-Spp To Enhance Waste Prediction And Sustainability In Smart Cities
ID_Doc 6537
Authors Balasubramanium S.; Nagu B.; Bansal S.; Faruque M.R.I.; Al-mugren K.S.
Year 2025
Published Scientific Reports, 15, 1
DOI http://dx.doi.org/10.1038/s41598-025-09433-w
Abstract The large volumes of bio-waste pose significant health and sanitation hazards. Effective bio-waste management involves value addition and conversion processes to enable the utilization of municipal biological waste as low-carbon energy sources. This research suggests a new predictive analytics model using the YOLOv8-SPP algorithm for improved waste management. With precise structuring and data processing, YOLOv8-SPP enhances waste identification and segmentation of various wastes with the vision of facilitating proper anticipation of future trends in waste production. The enhanced framework is remarkably 92% accurate in predicting waste production compared to the 78% accuracy achieved with other data types. The deployment also had the effect of the recycling rate growing by 20% and reducing waste treatment expenses by 15%. The findings justify the success of executing state-of-the-art analytics to optimize waste management processes in intelligent cities. © The Author(s) 2025.
Author Keywords Bio-Waste management; Renewable energy; Smart cities; Sustainability; YOLOv8-SPP


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