University of Twente Student Theses
Room occupancy analysis using Wi-Fi channel state information
Vintea, N.C. (2024) Room occupancy analysis using Wi-Fi channel state information.
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| Abstract: | This research shows that using the Wi-Fi CSI for occupancy analysis purposes proves that it can accurately be used to estimate the occupied rooms after gaining training data from the environment. This is done by training an FNN model to recognize different scenarios of room occupancy by collecting channel state information from all the possible occupancy combinations. Additionally, the paper highlights and analyses the parameters that influence the accuracy of the scanning like room count, and people count, and proves that distance does not have a big impact on the efficiency of the model. Even though the approach requires extended research with the implication of more people and the usage of bigger spaces, the system proved accurate enough to be used as an alternative to current detection methods. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/101206 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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