Course Info
Instructor: Yu Yang
Office: Room 313, Building C, Mountaintop Campus
Office hours: 3:10 pm - 4:10 pm, Thursday
Email: yuyang@lehigh.edu
Lecture: :1:35 pm - 2:50 pm, Tuesday/Thursday
Location: Maginnes Hall 103 OR Zoom
Zoom link: See Course Site
Course Description
Empowered by rich data collected from various infrastructures in our cities and machine learning techniques, our cities are becoming “smarter”. In this course, we discuss how data science is used to innovate our cities. We cover topics such as urban sensing, data-driven modeling and analytics for smart city services, data-driven decision making, data visualization, and novel applications in various city phenomena. Students are expected to (i) read and present research papers drawn from top conferences, (ii) participate in discussions of the papers, and (iii) design, implement and present their ideas for the final class project.
Course Learning Objectives
By the end of this course, you will be able to
- understand the basic principle underlying data science for smart cities;
- explain the state-of-the-art research in this area;
- demonstrate ideas for smart cities;
- implement ideas based on real-world data using tools including but not limited to data analytics, machine learning, statistics, data visualization, etc.
Prerequisites
CSE 017 and (CSE 160 or CSE 326) OR other equivalent courses.
Required Texts
No books are required. All the materials will be online.
Grading
Participation: 10%
Reading summary: 20%
Topic presentations: 20%
Class projects: 50% (10% for Proposal Reports, 20% for Final Reports, 20% for Presentations)
Course Schedule (Tentative, Updated 08/28)
W1: Course Introduction & Motivation (08/24, 08/26)
W2: Urban Infrastructures (08/31, 09/02)
Reading:
- Mathur, Suhas, et al. "Parknet: drive-by sensing of road-side parking statistics." Proceedings of the 8th international conference on Mobile systems, applications, and services. 2010.
- Fang, Zhihan, et al. "CellRep: Usage Representativeness Modeling and Correction Based on Multiple City-Scale Cellular Networks." Proceedings of The Web Conference 2020. 2020.
- Nambi, Akshay Uttama, et al. "ALT: towards automating driver license testing using smartphones." Proceedings of the 17th Conference on Embedded Networked Sensor Systems. 2019.
- Jiang, Junchen, et al. "Chameleon: scalable adaptation of video analytics." Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication. 2018.
- Tong, Panrong, et al. "Large-scale vehicle trajectory reconstruction with camera sensing network." MobiCom. 2021.
- O’Keeffe, Kevin P., et al. "Quantifying the sensing power of vehicle fleets." Proceedings of the National Academy of Sciences 116.26 (2019): 12752-12757.
- Zhang, Kai, et al. "ChromaCode: A Fully Imperceptible Screen-Camera Communication System." Proceedings of the 24th Annual International Conference on Mobile Computing and Networking. 2018.
- Zhang, Li Lyna, et al. "nn-Meter: towards accurate latency prediction of deep-learning model inference on diverse edge devices." Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services. 2021.
W3: Data Management & Processing (09/07, 09/09)
Reading:
- Yuan, Nicholas Jing, et al. "Reconstructing individual mobility from smart card transactions: A space alignment approach." 2013 IEEE 13th International Conference on Data Mining. IEEE, 2013.
- Xue, Andy Yuan, et al. "Solving the data sparsity problem in destination prediction." The VLDB Journal 24.2 (2015): 219-243.
- Bao, Jie, et al. "Managing massive trajectories on the cloud." Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2016.
- Li, Shen, et al. "Pyro: A spatial-temporal big-data storage system." 2015 {USENIX} Annual Technical Conference ({USENIX}{ATC} 15). 2015.
- Ren, Huimin, et al. "MTrajRec: Map-Constrained Trajectory Recovery via Seq2Seq Multi-task Learning." Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 2021.
- Akatsuka, Hiroto, and Masayuki Terada. "Application of Kalman Filter to Large-Scale Geospatial Data: Modeling Population Dynamics." Proceedings of the 28th International Conference on Advances in Geographic Information Systems. 2020.
- Yao, Shuochao, et al. "Deepsense: A unified deep learning framework for time-series mobile sensing data processing." Proceedings of the 26th International Conference on World Wide Web. 2017.
- Zhou, Yao, et al. "Crowd Teaching with Imperfect Labels." Proceedings of The Web Conference 2020. 2020.
W4: Data-Driven Modeling: Sensing (09/14, 09/16)
Reading:
- Xie, Xiaoyang, et al. "coSense: Collaborative urban-scale vehicle sensing based on heterogeneous fleets." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2.4 (2018): 1-25.
- Qin, Zhou, et al. "EXIMIUS: A measurement framework for explicit and implicit urban traffic sensing." Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. 2018.
- Pappalardo, Luca, et al. "Returners and explorers dichotomy in human mobility." Nature communications 6.1 (2015): 1-8.
- Ganti, Raghu, et al. "Inferring human mobility patterns from taxicab location traces." Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. 2013.
- Liu, Ruilin, et al. "Your search path tells others where to park: Towards fine-grained parking availability crowdsourcing using parking decision models." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1.3 (2017): 1-27.
- Iyengar, Srinivasan, et al. "Watthome: A data-driven approach for energy efficiency analytics at city-scale." Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2018.
- Song, Yiwei, et al. "MIFF: Human Mobility Extractions with Cellular Signaling Data under Spatio-temporal Uncertainty." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4.4 (2020): 1-19.
- Huynh, Sinh, et al. "VitaMon: measuring heart rate variability using smartphone front camera." Proceedings of the 17th Conference on Embedded Networked Sensor Systems. 2019.
W5: Data-Driven Modeling: Prediction (09/21, 09/23)
Reading:
- Yang, Zidong, et al. "Mobility modeling and prediction in bike-sharing systems." Proceedings of the 14th annual international conference on mobile systems, applications, and services. 2016.
- Feng, Jie, et al. "Deepmove: Predicting human mobility with attentional recurrent networks." Proceedings of the 2018 world wide web conference. 2018.
- Pakdamanian, Erfan, et al. "Deeptake: Prediction of driver takeover behavior using multimodal data." Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 2021.
- Zhang, Yan, et al. "Route prediction for instant delivery." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3.3 (2019): 1-25.
- Qin, Zhou, et al. "CellPred: A behavior-aware scheme for cellular data usage prediction." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4.1 (2020): 1-24.
- Zhang, Junbo, Yu Zheng, and Dekang Qi. "Deep spatio-temporal residual networks for citywide crowd flows prediction." Thirty-first AAAI conference on artificial intelligence. 2017.
- Trirat, Patara, and Jae-Gil Lee. "DF-TAR: A Deep Fusion Network for Citywide Traffic Accident Risk Prediction with Dangerous Driving Behavior." Proceedings of the Web Conference 2021. 2021.
- Sun, Ke, et al. "Where to go next: Modeling long-and short-term user preferences for point-of-interest recommendation." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 34. No. 01. 2020.
W6: Data-Driven Modeling: Control (09/28, 09/30)
Reading:
- Ji, Shenggong, et al. "A deep reinforcement learning-enabled dynamic redeployment system for mobile ambulances." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3.1 (2019): 1-20.
- Wang, Guang, et al. "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.
- He, Sihong, et al. "Data-Driven Distributionally Robust Electric Vehicle Balancing for Mobility-on-Demand Systems under Demand and Supply Uncertainties." 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020.
- Xu, Zhe, et al. "Large-scale order dispatch in on-demand ride-hailing platforms: A learning and planning approach." Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2018.
- Vazifeh, Mohammad M., et al. "Addressing the minimum fleet problem in on-demand urban mobility." Nature 557.7706 (2018): 534-538.
- Wang, Shuai, et al. "Towards efficient sharing: A usage balancing mechanism for bike sharing systems." The World Wide Web Conference. 2019.
- Bao, Jie, et al. "Planning bike lanes based on sharing-bikes' trajectories." Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining. 2017.
- Xu, Zhe, et al. "When recommender systems meet fleet management: Practical study in online driver repositioning system." Proceedings of The Web Conference 2020. 2020.
W7: Data Visualization (10/05, 10/07)
Reading:
- Ferreira, Nivan, et al. "Visual exploration of big spatio-temporal urban data: A study of new york city taxi trips." IEEE transactions on visualization and computer graphics 19.12 (2013): 2149-2158.
- Liu, Dongyu, et al. "Smartadp: Visual analytics of large-scale taxi trajectories for selecting billboard locations." IEEE transactions on visualization and computer graphics 23.1 (2016): 1-10.
- Wu, Wenchao, et al. "Telcovis: Visual exploration of co-occurrence in urban human mobility based on telco data." IEEE transactions on visualization and computer graphics 22.1 (2015): 935-944.
- Guo, Diansheng, and Xi Zhu. "Origin-destination flow data smoothing and mapping." IEEE Transactions on Visualization and Computer Graphics 20.12 (2014): 2043-2052.
- Tominski, Christian, et al. "Stacking-based visualization of trajectory attribute data." IEEE Transactions on visualization and Computer Graphics 18.12 (2012): 2565-2574.
- Miranda, Fabio, et al. "Urban pulse: Capturing the rhythm of cities." IEEE transactions on visualization and computer graphics 23.1 (2016): 791-800.
- Raji, Mohammad, et al. "Dataless Sharing of Interactive Visualization." IEEE Transactions on Visualization and Computer Graphics (2020).
- Kwon, Bum Chul, et al. "DPVis: Visual analytics with hidden markov models for disease progression pathways." IEEE transactions on visualization and computer graphics (2020).
W8-1: Pacing Break and No Lecture (10/12)
W8-2: Proposal Presentation (10/14)
W9: Urban Phenomena (10/19, 10/21)
Reading:
- Zheng, Yu, Furui Liu, and Hsun-Ping Hsieh. "U-air: When urban air quality inference meets big data." Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. 2013.
- Yuan, Jing, Yu Zheng, and Xing Xie. "Discovering regions of different functions in a city using human mobility and POIs." Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. 2012.
- Zheng, Yu, et al. "Diagnosing New York city's noises with ubiquitous data." Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. 2014.
- Zhang, Huichu, Yu Zheng, and Yong Yu. "Detecting urban anomalies using multiple spatio-temporal data sources." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2.1 (2018): 1-18.
- Wei, Hua, et al. "Intellilight: A reinforcement learning approach for intelligent traffic light control." Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2018.
- Wang, Hongjian, et al. "Crime rate inference with big data." Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining. 2016.
- Balasingam, Arjun, et al. "Throughput-fairness tradeoffs in mobility platforms." Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services. 2021.
- Ren, Huimin, et al. "ST-SiameseNet: Spatio-Temporal Siamese Networks for Human Mobility Signature Identification." Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2020.
W10: Novel Services (10/26, 10/28)
Reading:
- Du, Bowen, et al. "Catch me if you can: Detecting pickpocket suspects from large-scale transit records." Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining. 2016.
- Meegahapola, Lakmal, et al. "Buscope: Fusing individual & aggregated mobility behavior for" live" smart city services." Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services. 2019.
- D'Silva, Krittika, et al. "The role of urban mobility in retail business survival." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2.3 (2018): 1-22.
- He, Tianfu, et al. "Detecting Vehicle Illegal Parking Events using Sharing Bikes' Trajectories." KDD. 2018.
- Arora, Neha, et al. "Hard to park? Estimating parking difficulty at scale." Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2019.
- Ruan, Sijie, et al. "Learning to generate maps from trajectories." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 34. No. 01. 2020.
- Vahedian, Amin, et al. "Predicting urban dispersal events: A two-stage framework through deep survival analysis on mobility data." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 33. No. 01. 2019.
- Pan, Menghai, et al. "Dissecting the learning curve of taxi drivers: A data-driven approach." Proceedings of the 2019 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2019.
W11: Conflict Management Guest Lecture (11/04)
Reading:
Ma, Meiyi, Sarah Masud Preum, and John A. Stankovic. "Cityguard: A watchdog for safety-aware conflict detection in smart cities." Proceedings of the Second International Conference on Internet-of-Things Design and Implementation. 2017.
Ma, Meiyi, John A. Stankovic, and Lu Feng. "Cityresolver: a decision support system for conflict resolution in smart cities." 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS). IEEE, 2018.
Yuan, Yukun, et al. "DeResolver: a decentralized negotiation and conflict resolution framework for smart city services." Proceedings of the ACM/IEEE 12th International Conference on Cyber-Physical Systems. 2021.
Liu, Renju, et al. "RemedioT: Remedial actions for internet-of-things conflicts." Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. 2019.
W12: Transferability (11/09, 11/11)
Reading:
- Wei, Ying, Yu Zheng, and Qiang Yang. "Transfer knowledge between cities." Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016.
- Wang, Leye, et al. "Cross-city Transfer Learning for Deep Spatio-temporal Prediction." IJCAI International Joint Conference on Artificial Intelligence. 2019.
- Ding, Jingtao, et al. "Learning from hometown and current city: Cross-city POI recommendation via interest drift and transfer learning." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3.4 (2019): 1-28.
- He, Tianfu, et al. "What is the human mobility in a new city: Transfer mobility knowledge across cities." Proceedings of The Web Conference 2020. 2020.
- Yao, Huaxiu, et al. "Learning from multiple cities: A meta-learning approach for spatial-temporal prediction." The World Wide Web Conference. 2019.
- Shao, Erzhuo, et al. "One-shot Transfer Learning for Population Mapping." arXiv preprint arXiv:2108.06228 (2021).
- Pang, Yanbo, et al. "Intercity Simulation of Human Mobility at Rare Events via Reinforcement Learning." Proceedings of the 28th International Conference on Advances in Geographic Information Systems. 2020.
- Li, Ruirui, et al. "Few-shot learning for new user recommendation in location-based social networks." Proceedings of The Web Conference 2020. 2020.
W13: Privacy and Security (11/16, 11/18)
Reading:
- De Montjoye, Yves-Alexandre, et al. "Unique in the crowd: The privacy bounds of human mobility." Scientific reports 3.1 (2013): 1-5.
- Wang, Gang, et al. "Defending against sybil devices in crowdsourced mapping services." Proceedings of the 14th annual international conference on mobile systems, applications, and services. 2016.
- Fang, Zhihan, et al. "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): 1-23.
- Pan, Zheyi, et al. "TrajGuard: A Comprehensive Trajectory Copyright Protection Scheme." Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2019.
- Xu, Fengli, et al. "Trajectory recovery from ash: User privacy is not preserved in aggregated mobility data." Proceedings of the 26th international conference on world wide web. 2017.
- Lentzsch, Christopher, et al. "Hey Alexa, is this Skill Safe?: Taking a Closer Look at the Alexa Skill Ecosystem." 28th Annual Network and Distributed System Security Symposium (NDSS 2021). The Internet Society. 2021.
- Zeng, Kexiong Curtis, et al. "All your {GPS} are belong to us: Towards stealthy manipulation of road navigation systems." 27th {USENIX} security symposium ({USENIX} security 18). 2018.
- Wang, Yue, Ke Wang, and Chunyan Miao. "Truth discovery against strategic sybil attack in crowdsourcing." Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2020.
W14: Human-in-the-loop (11/23)
Reading:
- Cho, Eunjoon, Seth A. Myers, and Jure Leskovec. "Friendship and mobility: user movement in location-based social networks." Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining. 2011.
- Shen, Zhihao, et al. "Deepapp: a deep reinforcement learning framework for mobile application usage prediction." IEEE Transactions on Mobile Computing (2021).
- Xu, Tong, et al. "Taxi driving behavior analysis in latent vehicle-to-vehicle networks: A social influence perspective." Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016.
- Pan, Menghai, et al. "Is reinforcement learning the choice of human learners? a case study of taxi drivers." Proceedings of the 28th International Conference on Advances in Geographic Information Systems. 2020.
- Wang, Pengyang, et al. "You are how you drive: Peer and temporal-aware representation learning for driving behavior analysis." Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2018.
- Qin, Zhou, et al. "MIMU: Mobile WiFi Usage Inference by Mining Diverse User Behaviors." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4.4 (2020): 1-22.
Project Presentation (11/30, 12/02)