Deep Learning Applications in Solid Waste Management: A Deep Literature Review

Solid waste management (SWM) has recently received more attention, especially in developing countries, for smart and sustainable development. SWM system encompasses various interconnected processes which contain numerous complex operations. Recently, deep learning (DL) attained momentum providing alternative computational techniques to determine the solution of problems. Researchers have focused on this domain; therefore, significant research been published, last decade. The literature shows that no study evaluates potential DL solve performs a systematic review (SLR) complied 40 studies published between 2019 2021 reputed journals conferences. selected implemented models analyzed application different areas, namely identification segregation prediction generation. defined protocol comprises criteria quality assessment process select review. demonstrates comprehensive analysis SWM. It also highlights domains compares reported performance studies. Based reviewed work, it can be concluded exhibits plausible detect classify types waste. explains convolutional neural network with requirement gaps future recommendations.