Real-time prediction program for change in occupants in large exhibition hall based on deep learning
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United States of America Patent
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Oct 8, 2024
Grant Date -
Jun 10, 2021
app pub date -
Nov 9, 2020
filing date -
Dec 10, 2019
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Abstract
Disclosed are a method and apparatus for predicting a change in the occupants within a large exhibition hall in real time based on deep learning. A proposed method of predicting a change in the number of occupants within a space in real time includes dividing, into zones, a space where a number of occupants is to be predicted and pre-processing data related to a number of occupants within the space collected through simulations, generating the pre-processed data in a form of time-series data for deep learning, training a deep learning model for predicting a number of occupants in each divided zone using the generated time-series data, and predicting the number of occupants within the space by inputting, to the trained model, the data related to a number of occupants within the space collected in real time through socket communication with a server.
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