Support Vector Machine (SVM) is a supervised machine learning classifier that finds an optimal hyperplane to separate data points belonging to different classes by maximizing the margin between class boundaries, often employing kernel functions to handle nonlinearly separable data. In CSI-based Wi-Fi sensing, SVM is widely used for tasks such as activity recognition, occupancy detection, and passenger counting because it performs reliably on relatively small, high-dimensional feature sets extracted from channel state information without requiring large training datasets. Key variants relevant to the field include linear SVM for simpler separable problems, kernel-based SVM with radial basis function or polynomial kernels for complex nonlinear sensing scenarios, and multi-class extensions such as one-vs-one or one-vs-rest strategies to handle multiple activity or occupancy classes.
Source Papers
- A Survey on Green Wireless Sensing: Energy-Efficient Sensing via WiFi CSI and Lightweight Learning ↗ — A Survey on Green Wireless Sensing: Energy-Efficient Sensing
- A Survey on Human Behavior Recognition Using Channel State Information ↗ — A Survey on Human Behavior Recognition Using Channel State I
- A Survey on Wireless Device-free Human Sensing: Application Scenarios, Current Solutions, and Open Issues ↗ — A Survey on Wireless Device-free Human Sensing: Application
- A survey on CSI-based Wi-Fi sensing datasets and models with a focus on reproducibility ↗ — A survey on CSI-based Wi-Fi sensing datasets and models with
- BLE Can See: A Reinforcement Learning Approach for RF-based Indoor Occupancy Detection ↗ — BLE Can See: A Reinforcement Learning Approach for RF-based
- CSI-Based NTC Using Ambient WiFi: Channel Selection, Topology Control and Traffic Interference ↗ — CSI-Based NTC Using Ambient WiFi: Channel Selection, Topolog
- CSI-Chain: A Complete End-to-End Framework for WiFi CSI Sensing ↗ — CSI-Chain: A Complete End-to-End Framework for WiFi CSI Sens
- CSI-based Passenger Counting on Public Transport Vehicles with Multiple Transceivers ↗ — CSI-based Passenger Counting on Public Transport Vehicles wi
- Channel State Information from Pure Communication to Sense and Track Human Motion: A Survey ↗ — Channel State Information from Pure Communication to Sense a
- CrossSense: Towards Cross-Site and Large-Scale WiFi Sensing ↗ — CrossSense: Towards Cross-Site and Large-Scale WiFi Sensing
- Device-Free Passive Identity Identification via WiFi Signals ↗ — Device-Free Passive Identity Identification via WiFi Signals
- Device-Free Wireless Sensing for Gesture Recognition Based on Complementary CSI Amplitude and Phase ↗ — Device-Free Wireless Sensing for Gesture Recognition Based o
- Device-free occupancy detection and crowd counting in smart buildings with WiFi-enabled IoT ↗ — Device-free occupancy detection and crowd counting in smart
- Guiding Wi-Fi Sensor Placement for Enhanced CSI-Based Sensing in Stationary Crowd Counting ↗ — Guiding Wi-Fi Sensor Placement for Enhanced CSI-Based Sensin
- Human Activity Recognition via Wi-Fi and Inertial Sensors With Machine Learning ↗ — Human Activity Recognition via Wi-Fi and Inertial Sensors Wi
- Implementing Wi-Fi CSI-based room-level occupancy Estimation: an experimental study in multi-zone residential environments ↗ — Implementing Wi-Fi CSI-based room-level occupancy Estimation
- Occupancy Prediction in IoT-Enabled Smart Buildings: Technologies, Methods, and Future Directions ↗ — Occupancy Prediction in IoT-Enabled Smart Buildings: Technol
- Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review ↗ — Sensing Technologies for Crowd Management, Adaptation, and I
- WiFi Sensing with Channel State Information ↗ — WiFi Sensing with Channel State Information
- WiFi-Based Human Sensing With Deep Learning: Recent Advances, Challenges, and Opportunities ↗ — WiFi-Based Human Sensing With Deep Learning: Recent Advances