A Pioneer of Ubiquitous Computing: Daqing Zhang
Daqing Zhang is a researcher and professor whose work focuses on Ubiquitous and Pervasive Computing. He has been a full professor in Telecom SudParis’ Networks and Mobile Multimedia Services Department since 2007, and has worked extensively under Peking University as well. He is widely recognized for his improvements in ubiquitous wireless sensing, a field to which he has contributed fundamental theoretical bases and effective application methods.
In 2021, Zhang won the ACM UbiComp Outstanding Paper Award of the Conference, for his research titled “Exploring LoRa for Long-Range Through-Wall Sensing.” The selected paper was chosen from a pool of over 170 UbiComp articles, for its “groundbreaking new perspective on the use of LoRa for wireless perception.” (Peking University) LoRa — short for long range — is a wireless platform for spread spectrum modulation, marked by its design for low data rate transmissions and low power requirement. A maintained open standard for network protocol in LoRaWAN joins with equally impressive scalable capacity, security standards, penetration characteristics and range to make LoRa a prevalent choice in IoT applications that demand continuous coverage over a wide area. The primary implication of Zhang’s exemplary contrivance was the unlocking of a new global maximum for LoRa receiver implementation, whereby “[his team’s] unique noise reduction algorithm…effectively eliminates the errors caused by baseband signals and desynchronization of transmission and reception,” while greatly improving perception range (Peking). This advanced method for improving connection between LoRa transceivers subsequently “realizes human respiration detection from 25 meters away with only a pair of…devices” (Peking). In the experiment, the same resolution is maintained from a distance of 15 meters when the signal is passed through two walls. Zhang’s algorithm has notably expanded the limits of the effective range in application of the popular LoRa IoT technology.
Zhang presented his proposal for CrowdRecruiter at the UbiComp ’14 conference, with the innovative idea of selecting participants for piggyback mobile crowdsensing to increase the efficiency of data collection thereby, with regard to the Piggyback Crowdsensing (PCS) task model’s coverage ratio requirement as well as the size of the set of integrated participants. (Zhang) He also received widespread recognition in 2015 for his efforts on bike-share station placement planning, which effectively leveraged heterogenous open urban data to improve placement (Telecom Institute). Further to renowned research about detecting taxi trajectories from GPS traces and predicting mobile phone user locations via behavioral patterns, Zhang’s contributions in the mid-2010s solidified his place as a trailblazer in the international UbiComp community.
Again in 2015, Zhang received the Best Paper Award from IEEE UIC for his team’s research titled “Recognizing Gait Pattern of Parkinson’s Disease Patients Based on Fine-Grained Movement Function Features” (Telecom Institute). The approach uses gait phase discrimination, feature extraction and selection, and pattern classification to distinguish gait patterns of targets with Parkinson’s Disease from those of healthy individuals. Plantar pressure data is assessed to determine amongst four gait phases, whereafter features from those phases are extracted and examined by a BP neural network for indicators of Parkinson’s Disease. The team’s procedure proved to “outperform the baseline approach by 32.7%…in terms of Precision [and] 42.2%…in terms of Recall.” (T. Wang et al.) The outcome of this research is an increased capability for discovering Parkinson’s Disease gait patterns.
More recently, Professor Zhang and his research group at Peking University have made significant headway into intelligent Wi-Fi and radar based sensing, by enhancing performance systems in real world deployments. They have published research papers about the Fresnel zone sensing model, the mapping relationships between Doppler velocity and speed, sensing boundaries in wireless perception, and perception models for mobile scenarios (Peking University). Ubiquitous wireless sensing allows for detection of targets in an environment via the use of wireless radio frequency signals, including Wi-Fi, radar, and RFID. Doppler velocity is a key aspect in wireless sensing as it helps account for change in wave identifiers, frequency and wavelength, as objects move around a wireless component. Zhang and his team addressed discontinuities previously unsolved for by analyzing the effects of a target’s distance from a transceiver, along with their motion direction, for Wi-Fi applications; They quantified these factors and “provided guiding principles for achieving accurate velocity estimation.” (Peking University) Gesture recognition and human trajectory tracking are the vital use-cases directly supported by the team’s results.
Throughout his career, Professor Daqing Zhang has made enormous contributions to Ubiquitous Computing through his theoretical ideation and advanced, innovative research. His participation in crucial studies concerning Mobile Sensing, Urban Computing, Smart Environments, and Context Awareness has been paramount in the development of effective new modes of UbiComp technology for application in all walks of life, as evidenced by his many citations and host of prestigious research awards.
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Works Cited
Prof. Daqing Zhang. Ambient Intelligence & Pervasive System Group, https://www-public.imtbs-tsp.eu/~zhang_da/DaqingZhang.html#:~:text=Longbiao%20Chen%2C%20Daqing%20Zhang%2C%20Gang,11%2C%202015%2C%20Osaka%2C%20Japan.
“Professor Zhang Daqing’s Research Team from the Department of Computer Science of Peking University Won the UbiComp/IMWUT Distinguished Paper Award.” Software Engineering Institute, Peking University, 29 Sept. 2021, https://www.sei.pku.edu.cn/info/1036/1394.htm.
The Research Group Led by Prof. ZHANG Daqing Makes Significant Progress in the Field of Ubiquitous Wireless Sensing. 9 Jan. 2023, https://www.sei.pku.edu.cn/info/1036/1384.htm.
Zhang, Daqing. “CrowdRecruiter: Selecting Participants for Piggyback Crowdsensing under Probabilistic Coverage Constraint.” UbiComp ’14: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Sept. 2014, https://dl.acm.org/doi/10.1145/2632048.2632059.
