AIMC Topic: Waste Products
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Reducing food waste in the HORECA sector using AI-based waste-tracking devices.
Waste management (New York, N.Y.)
Mar 1, 2025
This study assesses the effectiveness of an intervention employing an AI-based, fully automatic waste-tracking system for food waste reduction in HORECA establishments. Waste-tracking devices were installed in a restaurant within a holiday resort and...
A machine-learning approach to optimize nutritional properties and organic wastes recycling efficiency conversed by black soldier fly (Hermetia illucens).
Bioresource technology
Feb 17, 2025
Suboptimal nutrition in organic waste limits the growth of black soldier fly (BSF) larvae, thereby reducing biowaste recycling efficiency. In this study, weight gain data from BSF larvae fed diets with distinct nutrient compositions were used to buil...
Enhancing waste classification accuracy with Channel and Spatial Attention-Based Multiblock Convolutional Network.
Environmental monitoring and assessment
Jan 25, 2025
Municipal waste classification is significant for effective recycling and waste management processes that involve the classification of diverse municipal waste materials such as paper, glass, plastic, and organic matter using diverse techniques. Yet,...
Plastic debris detection along coastal waters using Sentinel-2 satellite data and machine learning techniques.
Marine pollution bulletin
Oct 10, 2024
Few studies have effectively shown how to use satellites that gather optical data to monitor plastic debris in the marine environment. For the first time, floating macro-plastics distinguishable from seaweed are identified in optical data from the Eu...
Higher heating value estimation of wastes and fuels from ultimate and proximate analysis by using artificial neural networks.
Waste management (New York, N.Y.)
May 30, 2024
Higher heating value (HHV) is one of the most important parameters in determining the quality of the fuels. In this study, comparatively large datasets of ultimate and proximate analysis are constructed to be used in HHV estimation of several classes...
Analysis and forecasting of national marine litter based on coastal data in South Korea from 2009 to 2021.
Marine pollution bulletin
Mar 11, 2023
In this study, statistical analysis and forecasting were performed using coastal litter data of Korea. The analysis indicated that rope and vinyl accounted for the highest proportion of coastal litter items. The statistical analysis of the national c...
Deep learning for detecting macroplastic litter in water bodies: A review.
Water research
Jan 16, 2023
Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic environments, and causes economic and health problems. Accurate detection of macroplastic litter (plastic items >5 mm) in water is essential to estimate t...
Deploying deep learning to estimate the abundance of marine debris from video footage.
Marine pollution bulletin
Aug 22, 2022
The insatiable desire of society for plastic goods has led to synthetic materials becoming omnipresent in the marine environment. In attempting to address the problem of plastic pollution, we propose an image classifier based on the YOLOv5 deep learn...
Artificial Intelligence-Based Robotic Technique for Reusable Waste Materials.
Computational intelligence and neuroscience
May 6, 2022
Waste management is a critical problem for every country, whether it is developed or developing. Selecting and managing waste are a critical part of preserving the environment and maximizing resource efficiency. In addition to reducing trash and disp...
Pixel-level image classification for detecting beach litter using a deep learning approach.
Marine pollution bulletin
Feb 1, 2022
Mitigating and preventing beach litter from entering the ocean is urgently required. Monitoring beach litter solely through human effort is cumbersome, with respect to both time and cost. To address this problem, an artificial intelligence technique ...
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