AIMC Topic: Solid Waste

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Unveiling and interpreting the relationships among multi-pollutant emission factors in municipal solid waste incineration by machine learning.

Waste management (New York, N.Y.)
Effective control of key parameters is critical for regulating pollutant emissions in municipal solid waste incineration (MSWI), but existing research on these parameters remains limited and lacks comprehensiveness. This study used over 600,000 indus...

Artificial intelligence in solid waste management in India: current status and future prospects.

Environmental monitoring and assessment
The fast-paced economic development in India has resulted in higher energy use and the generation of solid wastes, posing immense environmental and health problems. With a view to solving these, this review investigates the incorporation of artificia...

Develop intelligent waste bin prototype based on fusion feature recognition of sounds and RGB images.

Waste management (New York, N.Y.)
Sorting municipal solid waste (MSW) at the source is a critical first step toward achieving a circular economy. Previous research has primarily focused on vision-based intelligent algorithms for MSW classification using red-green-blue (RGB) images. S...

Pollution risk assessment in sub-basins of an open dump using drones and geographic information systems.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
The sustainable management of municipal solid waste (MSW) presents a pressing global challenge. This study introduces an innovative methodology for analysing open dumps in Tucumán, Argentina, using unmanned aerial vehicles (UAVs) and DroneDeploy soft...

Identification and information acquisition of high-value construction solid waste combined millimeter-wave radar and convolutional neural networks.

Waste management (New York, N.Y.)
The accumulation of construction solid waste (CSW) leads to the waste of land resources and environmental pollution, becoming a significant social problem. Identifying the amount of high-value CSW is essential for assessing the value of accumulated C...

Machine learning-assisted assessment of municipal solid waste thermal treatment efficacy via rapid image recognition and visual analysis.

Waste management (New York, N.Y.)
Decentralized thermal treatment is a common method for municipal solid waste (MSW) disposal in rural areas. However, evaluating the effect of incineration has always been challenging owing to the difficult and time-consuming measurements involved. He...

Enhancing door-to-door waste collection forecasting through ML.

Waste management (New York, N.Y.)
We explore the application of machine learning (ML) techniques to forecast door-to-door waste collection, addressing the challenges in municipal solid waste (MSW) management. ML models offer a promising solution to optimize waste collection operation...

Novel method for predicting concentrations of incineration flue gas based on waste composition and machine learning.

Journal of environmental management
The complex composition of solid waste leads to the variability of flue gas emissions during its incineration, which poses a challenge to the stable operation of incineration and pollution control systems. To address this problem, the study explored ...

Efficient High Heating Value estimation using Latin Hypercube Sampling and Artificial Neural Network-based approach.

Environmental monitoring and assessment
To maximize energy recovery in waste-to-energy (WTE) systems, the High Heating Value (HHV) of municipal solid waste (MSW) must be accurately estimated. To forecast the HHV of MSW, this study proposes a unique method that combines an Artificial Neural...

Co-firing characteristic prediction of solid waste and coal for supercritical CO power cycle based on CFD simulation and machine learning algorithm.

Waste management (New York, N.Y.)
The co-firing technology of combustible solid waste (CSW) and coal in the supercritical CO (S-CO) circulating fluidized bed (CFB) can effectively deal with domestic waste, promote social and environmental benefits, improve the coal conversion rate, a...