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Waste Management System: Approach with Iot, Prediction and Dashboard

EasyChair Preprint no. 2514

7 pagesDate: January 31, 2020


After the mechanical transformation and development in innovation in recent decades, there has been a fast increment in the assembling ventures and its squanders. These wastes contain harmful elements and toxic substances. To manage these wastes in an effective way we propose an approach that can provide the toxic gas levels to take measures. This generalized idea can bring out the use of certain electrochemical sensors or cells that detect changes in the levels of the gases in the wastes, the sensors store the data on the cloud as the dataset. Predictive analysis has applied to the collected datasets to give information about the current as well as future level changes that might take place in these toxic wastes. All the statistics and analysis regarding the waste-related data will be displayed on the dashboard in the form of a graph.

Keyphrases: Dashboard, IoT, prediction, prediction analysis, Technical analyst, waste management

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Ramai Varangaonkar and Yashveer Girdhar and Viswanadhapalli Bhanuja and Kumar Kannan},
  title = {Waste Management System: Approach with Iot, Prediction and Dashboard},
  howpublished = {EasyChair Preprint no. 2514},

  year = {EasyChair, 2020}}
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