Residual municipal solid waste to energy under carbon neutrality: Challenges and perspectives for China

Y Song, X Xian, C Zhang, F Zhu, B Yu, J Liu - Resources, Conservation and …, 2023 - Elsevier
Solid waste management is rapidly developing and undergoing technological
transformation in China. However, Waste Classification (WC) methods and the …

Global models of smart cities and potential IoT applications: A review

A Hassebo, M Tealab - IoT, 2023 - mdpi.com
As the world becomes increasingly urbanized, the development of smart cities and the
deployment of IoT applications will play an essential role in addressing urban challenges …

Predicting residents' adoption intention for smart waste classification and collection system

D Cudjoe, H Zhang, H Wang - Technology in Society, 2023 - Elsevier
Smart waste classification and collection systems improve workload balances while
promoting environmental sustainability. Consumer acceptability is critical for effectively …

A state-of-the-art review on robotics in waste sorting: scope and challenges

AG Satav, S Kubade, C Amrutkar, G Arya… - International Journal on …, 2023 - Springer
An essential component of a waste management system is waste sorting. Correct sorting of
waste is crucial for creating a clean environment for everyone, reducing pollution and …

Three-dimensional quantitative mineral prediction from convolutional neural network model in developing intelligent cleaning technology

W Lin, S Qin, X Zhou, X Guan, Y Zeng, Z Wang, Y Shen - Resources Policy, 2024 - Elsevier
The aim of this study is to explore a three-dimensional (3D) quantitative mineral prediction
method to address the issues of low accuracy and efficiency in mineral resource exploration …

A systematic review of machine learning approaches for trash classification

S Vidhya - 2023 7th International Conference on Trends in …, 2023 - ieeexplore.ieee.org
In the fast-moving environment everyone handles different types of trash. A common man to
large industries produces trash and it is accumulating everywhere. Recycling the trashes to …

MWaste: a deep learning approach to manage household waste

S Kunwar - arXiv preprint arXiv:2304.14498, 2023 - arxiv.org
Computer vision methods have shown to be effective in classifying garbage into recycling
categories for waste processing, existing methods are costly, imprecise, and unclear. To …

Depression Detection with Convolutional Neural Networks: A Step Towards Improved Mental Health Care

H Tufail, SM Cheema, M Ali, IM Pires… - Procedia Computer …, 2023 - Elsevier
Depression is a mental disease affecting 5% of the population, and its prevalence is
increasing. Depression is characterized by feelings of worthlessness, hopelessness …

Multilevel thermoplastic waste segregation and classification with AHGSO using federated learning framework

RS Vignesh, M Monica Subashini - Kybernetes, 2024 - emerald.com
Purpose An abundance of techniques has been presented so forth for waste classification
but, they deliver inefficient results with low accuracy. Their achievement on various …

An Automated Approach to Waste Classification Using Deep Learning

S Loganayagi, D Usha - 2023 Fifth International Conference on …, 2023 - ieeexplore.ieee.org
Waste management has been done by humans through direct monitoring and classification
of the products or items that are to be sorted-out. Waste management are carried out in …