Indolocate is a Python package designed for indoor localization, leveraging Wi-Fi Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) to estimate precise indoor positions. Traditional GPS fails in indoor environments due to signal obstructions, making Wi-Fi-based localization a reliable alternative.
- Wi-Fi CSI-based Localization: Utilizes fine-grained CSI measurements for more accurate positioning compared to RSSI-based methods.
- RSSI-based Positioning: Implements fingerprinting and trilateration techniques using Wi-Fi signal strength.
- Multi-AP Fusion: Combines signals from multiple access points (APs) for improved localization accuracy.
- Signal Processing & Filtering: Supports smoothing techniques such as Kalman Filter and Particle Filter to reduce noise in CSI and RSSI data.
- Customizable API: Easy-to-use functions for training models and predicting indoor positions.
- Smart Buildings & Indoor Navigation: Assists in real-time navigation inside malls, airports, and offices.
- Asset Tracking: Helps locate objects, robots, and personnel in warehouses and factories.
- Activity Recognition & Sensing: Enhances human activity detection and environmental monitoring using Wi-Fi signals.
By integrating CSI and RSSI, indolocate provides a robust and scalable solution for Wi-Fi-based indoor localization, enabling researchers and developers to build efficient real-world positioning systems. 🚀