WiCount

The description is generated by Grok3.

Dataset Structure

Data Instances

Each instance is a .csv file representing a 60-second sample with the following columns:

• seq: Row number of the entry.
• timestamp: UTC+8 time of data collection.
• local_timestamp: ESP32 local time.
• rssi: Received Signal Strength Indicator.
• data: CSI data with 104 numbers representing 52 subcarriers, where each subcarrier's complex CSI value is computed as a[2i] + a[2i+1]j.
• Other columns: Additional ESP32 device information (e.g., MAC, MCS details).

Data Fields

Field Name	Description
seq	Row number of the entry
timestamp	UTC+8 time of data collection
local_timestamp	ESP32 local time
rssi	Received Signal Strength Indicator
data	CSI data (104 numbers, representing 52 subcarriers as complex values)
Other columns	Additional ESP32 metadata (e.g., MAC address, MCS details)

Data Splits

The dataset is organized by the number of people (0–3), with each folder containing .csv files corresponding to the number of people present in the environment:

• Folders: 0, 1, 2, 3 (representing the number of people).

Dataset Creation

Curation Rationale

The dataset was created to facilitate research on WiFi-based people number estimation using low-cost ESP32-S3 devices, enabling applications in smart environments, occupancy monitoring, and crowd management.

Source Data

• Initial Data Collection:

  Data was collected in an indoor meeting room with a single transmitter and multiple receivers using ESP32-S3 devices. The setup included:

  • Frequency Band: 2.4 GHz
  • Bandwidth: 20 MHz (52 subcarriers)
  • Protocol: 802.11n
  • Waveform: OFDM
  • Sampling Rate: ~100 Hz
  • Antenna Configuration: 1 antenna per device
  • Environment: Indoor with walls and a soft pad to prevent volunteer injuries.

• Who are the source data producers? The data was collected by researchers, with volunteers present in a controlled meeting room environment.

Annotations

• Annotation Process: Each .csv file is stored in a folder labeled with the number of people present (0–3). No additional manual annotations were provided.
• Who are the annotators? The dataset creators labeled the data based on the experimental setup.

Personal and Sensitive Information

The dataset does not contain personally identifiable information, as it focuses on the number of people (0–3) without associating specific identities or biometric data beyond CSI patterns.

Citation

@article{zhao2024mining,
  title={CSI-BERT2: A BERT-inspired Framework for Efficient CSI Prediction and Classification in Wireless Communication and Sensing},
  author={Zhao, Zijian and Meng, Fanyi and Lyu, Zhonghao and Li, Hang and Li, Xiaoyang and Zhu, Guangxu},
  journal={arXiv preprint arXiv:2412.06861},
  year={2024}
}