Inter-Mobile-Device Distance Estimation using Network Localization Algorithms for Digital Contact Logging Applications
Mobile applications are being developed for automated logging of contacts via Bluetooth to help scale up digital contact tracing efforts in the context of the ongoing COVID-19 pandemic. A useful component of such applications is inter-device distance estimation, which can be formulated as a network localization problem. We survey several approaches and evaluate the performance of each on real and simulated Bluetooth Low Energy (BLE) measurement datasets with respect to both distance estimate accuracy and the proximity detection problem. We investigate the effects of obstructions like pockets, differences between device models, and the environment (i.e. indoors or outdoors) on performance. We conclude that while direct estimation can provide the best proximity detection when Received Signal Strength Indicator (RSSI) measurements are available, network localization algorithms like Isomap, Local Linear Embedding, and the spring model outperform direct estimation in the presence of missing or very noisy measurements. The spring model consistently achieves the best distance estimation accuracy.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Mobile Augmented Reality Framework with Fusional Localization and Pose Estimation
As a novel way of presenting information, augmented reality (AR) enables people to interact with the physical world in a direct and intuitive way. While there are some mobile AR products implemented with specific hardwar…
Pose EstimationRobust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset
Robust 6DoF pose estimation with mobile devices is the foundation for applications in robotics, augmented reality, and digital twin localization. In this paper, we extensively investigate the robustness of existing RGBD-…
3D Object Detection3D Object Tracking6D Pose Estimation6D Pose Estimation using RGBD+3Accurate Hand Keypoint Localization on Mobile Devices
We present a novel approach for 2D hand keypoint localization from regular color input. The proposed approach relies on an appropriately designed Convolutional Neural Network (CNN) that computes a set of heatmaps, one pe…
Computational EfficiencyHand Keypoint LocalizationKeypoint EstimationNeRC: Neural Ranging Correction through Differentiable Moving Horizon Location Estimation
GNSS localization using everyday mobile devices is challenging in urban environments, as ranging errors caused by the complex propagation of satellite signals and low-quality onboard GNSS hardware are blamed for undermin…
On-device Scalable Image-based Localization via Prioritized Cascade Search and Fast One-Many RANSAC
We present the design of an entire on-device system for large-scale urban localization using images. The proposed design integrates compact image retrieval and 2D-3D correspondence search to estimate the location in exte…
Image-Based LocalizationImage RetrievalPose EstimationRetrieval