Forecasting the status of municipal waste in smart bins using deep learning

HIGHLIGHTS

• who: Sabbir Ahmed et al. from the UniSA STEM, University of South Australia, Adelaide, SA, Australia have published the article: Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning, in the Journal: (JOURNAL)
• what: This study proposes forecasting models comprising of 1D CNN (Convolutional Neural Networks) long short-term memory (LSTM) gated recurrent units (GRU) and bidirectional long short-term memory (Bi-LSTM) for time series prediction of public bins. This study explores the potential deep-learning methods applied to the smart bin dataset to predict waste generation. Specifically, the paper attempts . . .
  

   

  

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