Real-time prediction program for change in occupants in large exhibition hall based on deep learning
US12112262B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 9, 2020 |
| Grant date | Oct 8, 2024 |
| Priority date | — |
| Expiry date | Jun 12, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/52
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.