research-article

Mobile Cyber-Physical Systems for Smart Cities

Author:

Desheng ZhangAuthors Info & Claims

WWW '20: Companion Proceedings of the Web Conference 2020

Pages 546 - 548

https://doi.org/10.1145/3366424.3382121

Published: 20 April 2020 Publication History

Abstract

Nowadays, rapid urbanization leads to severe urban challenges, e.g., congestion and energy consumption, related to human mobility. To address them, it is essential to (i) measure and predict human mobility based on data from urban infrastructure, and (ii) intervene and alter human mobility with novel services on urban infrastructure, i.e., a Cyber-Physical System approach. However, both existing mobility models and resultant services are built upon the interaction of residents with single infrastructure (e.g., taxis) or multiple infrastructures from single domains (e.g., transportation), which are limited by their homogeneous nature. Fortunately, cross-domain infrastructures and their data from the latest infrastructure expansion enable us to explore real-time interactions between residents and infrastructures across domains. In this talk, we will introduce some of our recent work under cross-domain interactions.

References

[1]

Zhihan Fang, Boyang Fu, Zhou Qin, Fan Zhang, and Desheng Zhang. 2020. PrivateBus: Privacy Identification and Protection in Large-Scale Bus WiFi Systems. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 1 (2020), 1–26.

Digital Library

[2]

Zhihan Fang, Shuai Wang, Guang Wang, Chaoji Zuo, Fan Zhang, and Desheng Zhang. 2020. CellRep: Usage Representativeness Modeling and Correction Based on Multiple City-Scale Cellular Networks. In The World Wide Web Conference. 1–11.

[3]

Zhihan Fang, Yu Yang, Shuai Wang, Boyang Fu, Zixing Song, Fan Zhang, and Desheng Zhang. 2019. MAC: Measuring the Impacts of Anomalies on Travel Time of Multiple Transportation Systems. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 2 (2019), 1–24.

Digital Library

[4]

Zhihan Fang, Fan Zhang, and Desheng Zhang. 2018. MultiCell: Urban Population Modeling based on Multiple Cellphone Networks. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (2018).

Digital Library

[5]

R. Jiang, Z. Feng, D. Zhang, S. Wang, Y. Zhu, F. Zhang, and T. He. 2017. Data-Driven Digital Advertising with Uncertain Demand Model in Metro Networks. IEEE Transactions on Big Data(2017). https://doi.org/10.1109/TBDATA.2017.2725913

[6]

Ruilin Liu, Yu Yang, Daehan Kwak, Desheng Zhang, Liviu Iftode, and Badri Nath. 2017. Your Search Path Tells Others Where to Park: Towards Fine-Grained Parking Availability Crowdsourcing Using Parking Decision Models. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 3 (Sept. 2017), 78:1–78:27. https://doi.org/10.1145/3130942

Digital Library

[7]

F. Miao, S. Lin, S. Munir, J. Stankovic, H. Huang ad Desheng Zhang, T. He, and G. J. Pappas. 2015. Taxi Dispatch with Real-Time Data in Metropolitan Areas. In ACM/IEEE International Conference on Cyber-Physical Systems.

[8]

Zhou Qin, Fang Cao, Yu Yang, shuai Wang, Yunhuai Liu, Chang Tan, and Desheng Zhang. 2020. CellPred: A Behavior-aided Scheme for Cellular Data Usage Prediction. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 1 (2020), 1–26.

Digital Library

[9]

Zhou Qin, Zhihan Fang, Yunhuai Liu, and Desheng Zhang. [n.d.]. EXIMIUS: A Measurement Framework for Explicit and Implicit Urban Traffic Sensing. In Tthe 16th ACM Conference on Embedded Networked Sensor Systems (SenSys’18).

[10]

Lai Tu, Shuai Wang, Desheng Zhang, Fan Zhang, and Tian He. 2019. ViFi-MobiScanner: Observe Human Mobility via Vehicular Internet Service. IEEE Transactions on Intelligent Transportation Systems (2019).

[11]

Guang Wang, Xiuyuan Chen, Fan Zhang, Yang Wang, and Desheng Zhang. [n.d.]. Experience: Understanding Long-Term Evolving Patterns of Shared Electric Vehicle Fleets. In The 25th ACM Conference on Mobile Computing and Networking (MobiCom’19).

[12]

Guang Wang, Wenzhong Li, Jun Zhang, Yingqiang Ge, Zuohui Fu, Fan Zhang, Yang Wang, and Desheng Zhang. 2019. sharedCharging: Data-Driven Shared Charging for Large-Scale Heterogeneous Electric Vehicle Fleets. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 3 (2019), 1–25.

Digital Library

[13]

Guang Wang, Xiaoyang Xie, Fan Zhang, Yunhuai Liu, and Desheng Zhang. 2018. bCharge: Data-Driven Real-Time Charging Scheduling for Large-Scale Electric Bus Fleets. In IEEE Real-Time Systems Symposium. IEEE.

[14]

Guang Wang, Yongfeng Zhang, Zhihan Fang, Fan Zhang, and Desheng Zhang. 2020. FairCharge: Data-Driven Fairness-Aware Charging Recommendation for Electric Taxi Fleets. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 1 (2020).

[15]

Shuai Wang, Tian He, Desheng Zhang, Yunhuai Liu, and Sang H. Son. 2019. Towards efficient sharing: A usage balancing mechanism for bike sharing systems. In The World Wide Web Conference. 2011–2021.

[16]

Shuai Wang, Tian He, Desheng Zhang, Yuanchao Shu, Yunhuai Liu, Yu Gu, Cong Liu, Haengju Lee, and Sang H. Son. [n.d.]. BRAVO: Improving the Rebalancing Operation in Bike Sharing with Rebalancing Range Prediction. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2018 ([n. d.]).

[17]

Xiaoyang Xie, Yu Yang, Zhihan Fang, Guang Wang, Fan Zhang, Fan Zhang, Yunhuai Liu, and Desheng Zhang. 2018. coSense: Collaborative Urban-Scale Vehicle Sensing Based on Heterogeneous Fleets. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 4 (2018), 1–25.

Digital Library

[18]

Xiaoyang Xie, Fan Zhang, and Desheng Zhang. 2018. PrivateHunt: Multi-Source Data-Driven Dispatching in For-Hire Vehicle Systems. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 1 (March 2018), 45:1–45:26. https://doi.org/10.1145/3191777

Digital Library

[19]

Yu Yang, Xiaoyang Xie, Zhihan Fang, Fan Zhang, Yang Wang, and Desheng Zhang. [n.d.]. VeMo: Enabling Vehicular Mobility Modeling at Individual Levels with Full Penetration. In The 25th ACM Conference on Mobile Computing and Networking (MobiCom’19).

[20]

Yu Yang, Fan Zhang, and Desheng Zhang. 2018. SharedEdge: GPS-Free Fine-Grained Travel Time Estimation in State-Level Highway Systems. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 1 (March 2018), 48:1–48:26. https://doi.org/10.1145/3191780

Digital Library

[21]

Yukun Yuan, Desheng Zhang, Fei Miao, Jimin Chen, Tian He, and Shan Lin. 2019. p2303 2Charging: Proactive Partial Charging for Electric Taxi Systems. In 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS). IEEE, 688–699.

[22]

Yukun Yuan, Desheng Zhang, Fei Miao, John A Stankovic, Tian He, George Pappas, and Shan Lin. [n.d.]. In ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS’18).

[23]

Desheng Zhang and Tian He. [n.d.]. Online Cruising Mile Reduction for Large-Scale Taxicab Networks. In IEEE Transactions on Parallel and Distributed Systems (TPDS’15).

[24]

Desheng Zhang and Tian He. [n.d.]. pCruise: Reducing Cruising Miles for Taxicab Networks. In the 33rd IEEE Real-time Systems Symposium (RTSS’12).

[25]

Desheng Zhang, Tian He, Shan Lin, Sirajum Munir, and John A. Stankovic. [n.d.]. Dmodel: Online Taxicab Passenger Demand Model from Large Roving Sensor Networks. In the 3rd IEEE International Congress on Big Data (BIGDATA’14).

[26]

Desheng Zhang, Tian He, Shan Lin, Sirajum Munir, and John A. Stankovic.[n.d.]. Taxi Passenger Demand Modeling from a Roving Sensor Network. In IEEE Transactions on Big Data (IEEE TBD).

[27]

Desheng Zhang, Tian He, Yunhuai Liu, and John A. Stankovic. [n.d.]. A Unified Recommendation System for Carpooling and Regular Taxicab Services. In IEEE Transactions on Emerging Topics in Computing (IEEE TETC 2014).

[28]

Desheng Zhang, Tian He, Yunhuai Liu, and John A. Stankovic. [n.d.]. CallCab: A Unified Recommendation System for Carpooling and Regular Taxicab Services. In the IEEE International Conference on Big Data (BIGDATA’13).

[29]

Desheng Zhang, Tian He, and Fan Zhang. 2017. Real-Time Human Mobility Modeling with Multi-View Learning. ACM Trans. Intell. Syst. Technol. 9, 3 (Dec. 2017), 22:1–22:25. https://doi.org/10.1145/3092692

[30]

Desheng Zhang, Tian He, and Fan Zhang. 2019. National-scale traffic model calibration in real time with multi-source incomplete data. ACM Transactions on Cyber-Physical Systems 3, 2 (2019), 1–26.

Digital Library

[31]

D. Zhang, T. He, F. Zhang, and C. Xu. 2018. Urban-Scale Human Mobility Modeling With Multi-Source Urban Network Data. IEEE/ACM Transactions on Networking 26, 2 (April 2018), 671–684. https://doi.org/10.1109/TNET.2018.2801598

Digital Library

[32]

Desheng Zhang, Tian He, Fan Zhang, and Chengzhong Xu. 2018. Urban-Scale Human Mobility Modeling With Multi-Source Urban Network Data. IEEE/ACM Transactions on Networking 26, 2 (2018), 671–684.

Digital Library

[33]

Desheng Zhang, Jun Huang, Ye Li, Fan Zhang, Chengzhong Xu, and Tian He. [n.d.]. Exploring Human Mobility with Multi-Source Data at Extremely Large Metropolitan Scales. In 20th ACM Conference on Mobile Computing and Networking (MobiCom’14).

[34]

Desheng Zhang, Ruobing Jiang, Shuai Wang, Yanming Zhu, Bo Yang, Jian Cao, Fan Zhang, and Tian He. [n.d.]. Everyone Counts: Fine-Grained Digital Media Advertising in Metro Systems. In the IEEE International Conference on Big Data (BIGDATA’15).

[35]

Desheng Zhang, Ye Li, Fan Zhang, Mingming Lu, Yunhuai Liu, and Tian He. [n.d.]. coRide: Carpool Service with a Win-Win Fare Model for Taxicab Networks. In the 11th ACM Conference on Embedded Networked Sensor Systems (SenSys’13).

[36]

Desheng Zhang, Fan Zhang, and Tian He. [n.d.]. MultiCalib:National-Scale Traffic Model Calibration with Multi-source Incomplete Data. In The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL’16).

[37]

Desheng Zhang, Fan Zhang, Ming Lu, Yunhuai Liu, and Tian He. [n.d.]. Carpool Service for Large-Scale Taxicab Networks. In ACM Transactions on Sensor Networks (ACM TOSN’ 16).

[38]

Desheng Zhang, Juanjuan Zhao, Fan Zhang, and Tian He. [n.d.]. In ACM/IEEE Sixth International Conference on Cyber-Physical Systems ICCPS’15.

[39]

Desheng Zhang, Juanjuan Zhao, Fan Zhang, and Tian He. [n.d.]. coMobile: Real-time Human Mobility Modeling at Urban Scale by Multi-View Learning. In ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL’15).

[40]

Desheng Zhang, Juanjuan Zhao, Fan Zhang, Tian He, Haengju Lee, and Sang H Son. 2016. Heterogeneous model integration for multi-source urban infrastructure data. ACM Transactions on Cyber-Physical Systems 1, 1 (2016), 1–26.

Digital Library

[41]

Desheng Zhang, Juanjuan Zhao, Fan Zhang, Ruobing Jiang, and Tian He. [n.d.]. Feeder: Supporting Last-Mile Transit with Extreme-Scale Infrastructure Data. In the 14th ACM Conference on Information Processing in Sensor Networks (IPSN ’15).

[42]

Desheng Zhang, Juanjuan Zhao, Fan Zhang, Ruobing Jiang, and Tian He. [n.d.]. Last-Mile Transit Service with Urban Infrastructure Data. In ACM Transactions on Cyber Physical Systems (ACM TCPS’ 16).

[43]

Yan Zhang, Yunhuai Liu, Genjian Li, Yi Ding, Ning Chen, Hao Zhang, Tian He, and Desheng Zhang. 2019. Route Prediction for Instant Delivery. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 3 (Sept. 2019). https://doi.org/10.1145/3351282

Digital Library

[44]

Yi Zhao, Xu Wang, Jianbo Li, Desheng Zhang, and Zheng Yang. [n.d.]. CellTrans: Private Car or Public Transportation? Infer Users’ Main Transportation Modes at Urban Scale with Cellular Data. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2019 ([n. d.]).

Cited By

Sachan AChauhan NKumar N(2023)Congestion Minimization using Fog-deployed DRL-Agent Feedback enabled Traffic Light Cooperative Framework2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)10.1109/CCGrid57682.2023.00058(557-567)Online publication date: May-2023
https://doi.org/10.1109/CCGrid57682.2023.00058
Lu HLyu FRen JYu JWu FZhang YShen X(2022)CODE: Compact IoT Data Collection with Precise Matrix Sampling and Efficient Inference2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS54860.2022.00077(743-753)Online publication date: Jul-2022
https://doi.org/10.1109/ICDCS54860.2022.00077

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Mobile Cyber-Physical Systems for Smart Cities

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cover image ACM Conferences

WWW '20: Companion Proceedings of the Web Conference 2020

April 2020

854 pages

ISBN:9781450370240

DOI:10.1145/3366424

Editors:
Amal El Fallah Seghrouchni
Sorbonne University, France
,
Gita Sukthankar
University of Central Florida, United States
,
Tie-Yan Liu
Microsoft Research Asia, China
,
Maarten van Steen
University of Twente, Netherlands

Copyright © 2020 ACM.

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Published: 20 April 2020

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WWW '20: The Web Conference 2020

April 20 - 24, 2020

Taipei, Taiwan

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Cited By

Sachan AChauhan NKumar N(2023)Congestion Minimization using Fog-deployed DRL-Agent Feedback enabled Traffic Light Cooperative Framework2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)10.1109/CCGrid57682.2023.00058(557-567)Online publication date: May-2023
https://doi.org/10.1109/CCGrid57682.2023.00058
Lu HLyu FRen JYu JWu FZhang YShen X(2022)CODE: Compact IoT Data Collection with Precise Matrix Sampling and Efficient Inference2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS54860.2022.00077(743-753)Online publication date: Jul-2022
https://doi.org/10.1109/ICDCS54860.2022.00077

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