![Hidden Markov Models for Vehicle Tracking with Bluetooth](https://writelatex.s3.amazonaws.com/published_ver/137.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240831T231313Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240831/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=67ba0a9bcbd7ebd51b75edcf873d5b554e1b1aa93ca72eed181f4b95456fd0d3)
Hidden Markov Models for Vehicle Tracking with Bluetooth
Author
John D. Lees-Miller, R. Eddie Wilson, Simon Box
Last Updated
před 11 lety
License
Other (as stated in the work)
Abstract
Bluetooth is a short range communication protocol. Bluetooth-enabled devices can be detected using road-side equipment, and each detected device reports a unique identifier. These unique identifiers can be used to track vehicles through road networks over time. The focus of this paper is on reconstructing the paths of vehicles through a road network using Bluetooth detection data. A method is proposed that uses Hidden Markov Models, which are a well-known tool for statistical pattern recognition. The proposed method is evaluated on a mixture of real and synthetic Bluetooth data with GPS ground truth, and it outperforms a simple deterministic strategy by a large margin (30%-50%) in this case.
![Hidden Markov Models for Vehicle Tracking with Bluetooth](https://writelatex.s3.amazonaws.com/published_ver/137.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240831T231313Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240831/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=67ba0a9bcbd7ebd51b75edcf873d5b554e1b1aa93ca72eed181f4b95456fd0d3)