AIMC Topic: Refuse Disposal

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Mitigating spread of contamination in meat supply chain management using deep learning.

Scientific reports Mar 23, 2022
Industry 4.0 recommends a paradigm shift from traditional manufacturing to automated industrial practices, especially in different parts of supply chain management. Besides, the Sustainable Development Goal (SDG) 12 underscores the urgency of ensurin...
Refuse Disposal Carbon Footprint Artificial Intelligence Deep Learning Meat
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An Intelligent System for Proper Management and Disposal of Unused and Expired Medications.

International journal of environmental research and public health Mar 1, 2022
For years, several countries have been concerned about how to dispose of unused pharmaceuticals that can endanger human health and the environment. Moreover, some people are in desperate need of medical attention and medications, but they lack the fi...
Humans Artificial Intelligence Pharmaceutical Preparations Algorithms Recognition, Psychology Saudi Arabia Refuse Disposal
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Implementation of an early warning system with hyperspectral imaging combined with deep learning model for chlorine in refuse derived fuels.

Waste management (New York, N.Y.) Feb 21, 2022
Chlorine content is one of the most important parameters in Refuse Derived Fuels (RDFs) used as a fuel in cement kilns. The main problem with the use of RDF is that chlorine in the waste weakens the cement, increases the risk of corrosion in the kiln...
Deep Learning Refuse Disposal Garbage Chlorine Hyperspectral Imaging
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The fourth industrial revolution in the food industry-Part I: Industry 4.0 technologies.

Critical reviews in food science and nutrition Feb 3, 2022
Climate change, the growth in world population, high levels of food waste and food loss, and the risk of new disease or pandemic outbreaks are examples of the many challenges that threaten future food sustainability and the security of the planet and...
Humans Refuse Disposal Food Industry Food Artificial Intelligence Internet
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A novel MADM algorithm for landfill site selection based on q-rung orthopair probabilistic hesitant fuzzy power Muirhead mean operator.

PloS one Oct 21, 2021
With the rapid development of economy and the acceleration of urbanization, the garbage produced by urban residents also increases with the increase of population. In many big cities, the phenomenon of "garbage siege" has seriously affected the devel...
Probability Fuzzy Logic Waste Disposal Facilities Humans Refuse Disposal Decision Making Algorithms
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Fuzzy-based adaptive learning network using search and rescue optimization for e-waste management model: case study.

Environmental science and pollution research international Oct 1, 2021
In recent days, the expansion of e-waste disposal should be increased due to environmental hazards, contamination of groundwater, an unconcerned consequence on marine life, human health, and decrease in the fertility of the soil. The majority of the ...
Refuse Disposal Waste Management Electronic Waste Machine Learning Recycling
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Prediction of biogas production in anaerobic co-digestion of organic wastes using deep learning models.

Water research Sep 24, 2021
Interest in anaerobic co-digestion (AcoD) has increased significantly in recent decades owing to enhanced biogas productivity due to the utilization of different organic wastes, such as food waste and sewage sludge. In this study, a robust AcoD model...
Food Refuse Disposal Digestion Biofuels Bioreactors Sewage Anaerobiosis Methane Deep Learning
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On the Prediction of Biogas Production from Vegetables, Fruits, and Food Wastes by ANFIS- and LSSVM-Based Models.

BioMed research international Sep 24, 2021
This study is aimed at modeling biodigestion systems as a function of the most influencing parameters to generate two robust algorithms on the basis of the machine learning algorithms, including adaptive network-based fuzzy inference system (ANFIS) a...
Fuzzy Logic Refuse Disposal Least-Squares Analysis Linear Models Computer Simulation Fruit Biofuels Algorithms Support Vector Machine Vegetables Food
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A smart municipal waste management system based on deep-learning and Internet of Things.

Waste management (New York, N.Y.) Aug 27, 2021
A proof-of-concept municipal waste management system was proposed to reduce the cost of waste classification, monitoring and collection. In this system, we utilize the deep learning-based classifier and cloud computing technique to realize high accur...
Refuse Disposal Garbage Internet of Things Waste Management Deep Learning
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Variables Influencing per Capita Production, Separate Collection, and Costs of Municipal Solid Waste in the Apulia Region (Italy): An Experience of Deep Learning.

International journal of environmental research and public health Jan 17, 2021
Municipal solid waste (MSW) must be managed to reduce its impact on environmental matrices and population health as much as possible. In particular, the variables that influence the production, separate waste collection, and costs of MSW must be unde...
Italy Costs and Cost Analysis Solid Waste Waste Management Deep Learning Refuse Disposal Cities Humans
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