Kunpeng Huang, Yasha Iravantchi, Dongyao Chen, and Alanson Sample

This paper introduces MagDesk, an interactive tabletop workspace capable of real-time 3D tracking of passive magnets embedded in objects.

Jike Wang, Yasha Iravantchi, Alanson Sample, Kang G. Shin, Xinbing Wang, Dongyao Chen

Fiducial tags are essential for robots. They provide crucial supports such as pose calibration, contextual perception, and navigation. In Polaris, we build the world first invisible fiducial tag with magnetic sensing.

Dongyao Chen, Qing Luo, Xiaomeng Chen, Xinbing Wang, Chenghu Zhou

Tracking the angular movement of body joints has been a critical enabler for various applications, such as virtual and augmented reality, sports monitoring, and medical rehabilitation. MagDot is the first wearable system that achieves drift-free joint tracking. Experiment results indicate MagDot can achieve tracking accuracy of 2.72◦, 4.14◦, and 4.61◦ for elbow, knee, and shoulder, respectively.

Zhenyu Chen, Jike Wang, and Dongyao Chen

We demonstrate the deployment of magnetic tracking techniques on commodity smartphones. Our implementation is benchmarked on a Commercial Off-The-Shelf (COTS) Android smartphone. Empirical studies indicate that our implementation on mobile platforms is both energy-efficient and highly effective.

Jike Wang, Shanmu Wang, Yasha Iravantchi, Mingke Wang, Alanson Sample, Kang G. Shin, Xinbing Wang, Chenghu Zhou, Dongyao Chen

Allowing cars to "see" road markings is crucial for traffic safety. However, road markings, e.g., lanes and pedestrian crossings, can be easily occluded by bad weather. METRO proposed a novel magnetic sensing approach to encode rich information with passive magnets. METRO is tested and verified on REAL-WORLD ROADS!

Dongyao Chen, Mert D. Pesé, and Kang G. Shin

We leveraged the widely available smartphone data to infer the vehicle type information.

Mingke Wang*, Qing Luo*, Yasha Iravantchi, Xiaomeng Chen, Alanson Sample, Kang G. Shin, Xiaohua Tian, Xinbing Wang, Dongyao Chen

We proposed MAGIC, a systematic framework to automatically calibrate both soft- and hard-iron disturbances for a MEMS magnetometer array.

Fengyuan Zhu, Mingwei Ouyang, Luwei Feng, Yaoyu Liu, Xiaohua Tian, Meng Jin, Dongyao Chen, Xinbing Wang

In this work, we for the first time show how to enable softwaredefined PHY (SD-PHY) to achieve agile reprogrammability in wireless backscatter networks. This can facilitate innovations in this field by relieving researchers from unnecessary engineering work.

Mert D. Pesé, Dongyao Chen, C. Andrés Campos, Alice Ying, Troy Stacer, Kang G. Shin

DETROIT is an open-source vehicle-agnostic end- to-end framework for vehicular data collection, translation and sharing that facilitates the rapid development of automotive apps.

Dongyao Chen, Mingke Wang, Chenxi He, Qing Luo, Yasha Iravantchi, Alanson Sample, Kang G. Shin, Xinbing Wang

We proposed MagX, the first untethered and mobile magnetic tracking platform for fine-grained hand tracking. Exemplary applications includes AR/VR interaction and face-touching detection.

Liang He, Yuanchao Shu, Youngmoon Lee, Dongyao Chen, Kang G. Shin

This work presented B-Auth, a vehicle battery-based driver authentication platform. We discovered the connection between battery voltage with the driver's behavior, e.g., braking, acceleration, using wipers, etc.

Mert D. Pesé, Troy Stacer, C. Andrés Campos, Eric Newberry, Dongyao Chen, Kang G. Shin

LibreCAN can be used for automated translation of in-vehicle data, thus making the data flow in cars "transparent" to developers. In the future, we may be able to build apps on cars as easy as developing apps on smartphones!

Dongyao Chen, Kang G. Shin

This work presents TurnsMap, an IoT + AI framework for automatically detecting if a left turn is safe, e.g., whether it has protection for left-turning cars. Democratizing this information can help assure traffic safety for various transportation applications, e.g., navigation and ride-sharing apps.

Dongyao Chen, Kyong-Tak Cho, Kang G. Shin

This work presents Dri-Fi, a solution that enables automotive apps to identify the person behind-the-wheel by only using mobile sensors. The capability of identifying driver is essential for personalized service/assistance for the driver and his/her designated parties, thus benefiting various automotive apps

Dongyao Chen, Yurong Jiang, Kyu-Han Kim, Kang G. Shin

LocBLE is able to locate specific location of any surrounding Bluetooth low energy (BLE) beacons by justing using your smartphone. Comparing to existing coarse-grained BLE ranging applications, LocBLE is capable of enabling various use cases in Internet-of-Things. This is a collaborative work with Hewlett Packard Labs during my internship.

Dongyao Chen, Kyong-Tak Cho, Sihui Han, Zhizhuo Jin, Kang G. Shin

This work introduced a vehicle steering detection middleware called V-Sense which can run on commodity smartphones without additional sensors or infrastructure support.

Yu-Chih Tung, Sihui Han, Dongyao Chen, Kang G. Shin

This work investigated vulnerability in MU-MIMO. Focusing on the plaintext feedback of estimated channel state information (CSI) from clients to the APs, we found that a malicious user could employ a sniff attack or a power attack by exploiting the vulnerability in the existing CSI feed scheme.