survey

Spatial Data Quality in the Internet of Things: Management, Exploitation, and Prospects

Authors:

Christian S. Jensen,

Muhammad Aamir CheemaAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 55, Issue 3

Article No.: 57, Pages 1 - 41

https://doi.org/10.1145/3498338

Published: 03 February 2022 Publication History

Abstract

With the continued deployment of the Internet of Things (IoT), increasing volumes of devices are being deployed that emit massive spatially referenced data. Due in part to the dynamic, decentralized, and heterogeneous architecture of the IoT, the varying and often low quality of spatial IoT data (SID) presents challenges to applications built on top of this data. This survey aims to provide unique insight to practitioners who intend to develop IoT-enabled applications and to researchers who wish to conduct research that relates to data quality in the IoT setting. The survey offers an inventory analysis of major data quality dimensions in SID and covers significant data characteristics and associated quality considerations. The survey summarizes data quality related technologies from both task and technique perspectives. Organizing the technologies from the task perspective, it covers recent progress in SID quality management, encompassing location refinement, uncertainty elimination, outlier removal, fault correction, data integration, and data reduction; and it covers low-quality SID exploitation, encompassing querying, analysis, and decision-making techniques. Finally, the survey covers emerging trends and open issues concerning the quality of SID.

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References

[1]

2016. General Data Protection Regulation (GDPR). https://gdpr-info.eu/.

[2]

2017. IDC FutureScape: Worldwide Internet of Things 2018 predictions. Retrieved Nov 2021 fromhttps://www.idc.com/research/viewtoc.jsp?containerId=US43161517.

[3]

2017. Location-based services for the Internet of Things. Retrieved Nov 2021 fromhttps://internetofthingsagenda.techtarget.com/blog/IoT-Agenda/Location-based-services-for-the-internet-of-things.

[4]

2018. California Consumer Privacy Act (CCPA). https://oag.ca.gov/privacy/ccpa.

[5]

2019. Growing opportunities in the Internet of Things. Retrieved Nov 2021 fromhttps://www.mckinsey.com/industries/private-equity-and-principal-investors/our-insights/growing-opportunities-in-the-internet-of-things.

[6]

2019. IDC forecasts connected IoT devices to generate 79.4ZB of data in 2025. Retrieved Nov 2021 fromhttps://futureiot.tech/idc-forecasts-connected-iot-devices-to-generate-79-4zb-of-data-in-2025/.

[7]

2020. 5G and the enablement of IoT edge processing. Retrieved Nov 2021 fromhttps://hazelcast.com/resources/5g-and-the-enablement-of-iot-edge-processing/.

[8]

2021. The dangers of driverless cars. Retrieved Nov 2021 fromhttps://www.natlawreview.com/article/dangers-driverless-cars.

[9]

Alsharif Abuadbba, Ibrahim Khalil, and Xinghuo Yu. 2017. Gaussian approximation-based lossless compression of smart meter readings. IEEE Transactions on Smart Grid 9, 5 (2017), 5047–5056.

[10]

Charu C. Aggarwal. 2015. Outlier analysis. In Data Mining. 237–263.

Digital Library

[11]

Mamta Agiwal, Navrati Saxena, and Abhishek Roy. 2019. Towards connected living: 5G enabled Internet of Things (IoT). IETE Technical Review 36, 2 (2019), 190–202.

[12]

Isam Mashhour Al Jawarneh, Paolo Bellavista, Antonio Corradi, Luca Foschini, and Rebecca Montanari. 2020. Big spatial data management for the Internet of Things: A survey. Journal of Network and Systems Management 28, 4 (2020), 990–1035.

Digital Library

[13]

Haidar Al-Khalidi, David Taniar, John Betts, and Sultan Alamri. 2014. Monitoring moving queries inside a safe region. The Scientific World Journal 2014 (2014).

[14]

Furqan Alam, Rashid Mehmood, Iyad Katib, Nasser N. Albogami, and Aiiad Albeshri. 2017. Data fusion and IoT for smart ubiquitous environments: A survey. IEEE Access 5 (2017), 9533–9554.

[15]

Alessia Albanese, Sankar K. Pal, and Alfredo Petrosino. 2012. Rough sets, kernel set, and spatiotemporal outlier detection. IEEE Transactions on Knowledge and Data Engineering 26, 1 (2012), 194–207.

Digital Library

[16]

Fernandes Nicole Ann and Rupali Wagh. 2019. Quality assurance in big data analytics: An IoT perspective. Telfor Journal 11, 2 (2019), 114–118.

[17]

Annalisa Appice, Anna Ciampi, Donato Malerba, and Pietro Guccione. 2013. Using trend clusters for spatiotemporal interpolation of missing data in a sensor network. Journal of Spatial Information Science 2013, 6 (2013), 119–153.

[18]

Javed Aslam, Zack Butler, Florin Constantin, Valentino Crespi, George Cybenko, and Daniela Rus. 2003. Tracking a moving object with a binary sensor network. In SenSys. 150–161.

Digital Library

[19]

Asif Iqbal Baba, Manfred Jaeger, Hua Lu, Torben Bach Pedersen, Wei-Shinn Ku, and Xike Xie. 2016. Learning-based cleansing for indoor RFID data. In SIGMOD. 925–936.

Digital Library

[20]

Asif Iqbal Baba, Hua Lu, Torben Bach Pedersen, and Xike Xie. 2014. Handling false negatives in indoor RFID data. In MDM, Vol. 1. 117–126.

Digital Library

[21]

Asif Iqbal Baba, Hua Lu, Xike Xie, and Torben Bach Pedersen. 2013. Spatiotemporal data cleansing for indoor RFID tracking data. In MDM, Vol. 1. 187–196.

Digital Library

[22]

Elarbi Badidi and Muthucumaru Maheswaran. 2018. Towards a platform for urban data management, integration and processing. In IoTBDS. 299–306.

[23]

Garvita Bajaj, Rachit Agarwal, Pushpendra Singh, Nikolaos Georgantas, and Valérie Issarny. 2018. 4W1H in IoT semantics. IEEE Access 6 (2018), 65488–65506.

[24]

Tanvi Banerjee and Amit Sheth. 2017. IoT quality control for data and application needs. IEEE Intelligent Systems 32, 2 (2017), 68–73.

Digital Library

[25]

Payam Barnaghi, Wei Wang, Lijun Dong, and Chonggang Wang. 2013. A linked-data model for semantic sensor streams. In IEEE GreenCom/iThings/CPScom. 468–475.

Digital Library

[26]

Thomas Bernecker, Tobias Emrich, Hans-Peter Kriegel, Nikos Mamoulis, Matthias Renz, and Andreas Züfle. 2011. A novel probabilistic pruning approach to speed up similarity queries in uncertain databases. In ICDE. 339–350.

Digital Library

[27]

Thomas Bernecker, Tobias Emrich, Hans-Peter Kriegel, Matthias Renz, Stefan Zankl, and Andreas Züfle. 2011. Efficient probabilistic reverse nearest neighbor query processing on uncertain data. Proceedings of the VLDB Endowment 4, 10 (2011), 669–680.

Digital Library

[28]

George Beskales, Mohamed A. Soliman, and Ihab F. Ilyas. 2008. Efficient search for the top-k probable nearest neighbors in uncertain databases. Proceedings of the VLDB Endowment 1, 1 (2008), 326–339.

Digital Library

[29]

Derya Birant and Alp Kut. 2007. ST-DBSCAN: An algorithm for clustering spatial–temporal data. Data & Knowledge Engineering 60, 1 (2007), 208–221.

Digital Library

[30]

Ane Blázquez-García, Angel Conde, Usue Mori, and Jose A. Lozano. 2021. A review on outlier/anomaly detection in time series data. Comput. Surveys 54, 3 (2021), 1–33.

Digital Library

[31]

Robert Goodell Brown. 2004. Smoothing, forecasting and prediction of discrete time series. Courier Corporation.

[32]

Yingyi Bu, Lei Chen, Ada Wai-Chee Fu, and Dawei Liu. 2009. Efficient anomaly monitoring over moving object trajectory streams. In KDD. 159–168.

Digital Library

[33]

Hu Cao, Ouri Wolfson, and Goce Trajcevski. 2006. Spatio-temporal data reduction with deterministic error bounds. The VLDB Journal 15, 3 (2006), 211–228.

Digital Library

[34]

Carlos Carvalho, Danielo G. Gomes, Nazim Agoulmine, and José Neuman De Souza. 2011. Improving prediction accuracy for WSN data reduction by applying multivariate spatio-temporal correlation. Sensors 11, 11 (2011), 10010–10037.

[35]

Roberto Casado-Vara, Fernando de la Prieta, Javier Prieto, and Juan M. Corchado. 2018. Blockchain framework for IoT data quality via edge computing. In SenSys BlockSys Workshop. 19–24.

Digital Library

[36]

Dakshak Keerthi Chandra, Pengyang Wang, Jennifer Leopold, and Yanjie Fu. 2019. Collective representation learning on spatiotemporal heterogeneous information networks. In SIGSPATIAL. 319–328.

Digital Library

[37]

Tung-Chun Chang, Georgios Bouloukakis, Chia-Ying Hsieh, Cheng-Hsin Hsu, and Nalini Venkatasubramanian. 2021. SmartParcels: Cross-layer IoT planning for smart communities. In IoTDI. 1–13.

Digital Library

[38]

Muhammad Aamir Cheema, Ljiljana Brankovic, Xuemin Lin, Wenjie Zhang, and Wei Wang. 2010. Multi-guarded safe zone: An effective technique to monitor moving circular range queries. In ICDE. 189–200.

[39]

Muhammad Aamir Cheema, Xuemin Lin, Wei Wang, Wenjie Zhang, and Jian Pei. 2009. Probabilistic reverse nearest neighbor queries on uncertain data. IEEE Transactions on Knowledge and Data Engineering 22, 4 (2009), 550–564.

Digital Library

[40]

Chaoxiong Chen, Chao Chen, Chaocan Xiang, Songtao Guo, Zhu Wang, and Bin Guo. 2020. ToiletBuilder: A PU learning based model for selecting new public toilet locations. IEEE Internet of Things Journal (2020).

[41]

Chao Chen, Yan Ding, Xuefeng Xie, Shu Zhang, Zhu Wang, and Liang Feng. 2019. TrajCompressor: An online map-matching-based trajectory compression framework leveraging vehicle heading direction and change. IEEE Transactions on Intelligent Transportation Systems 21, 5 (2019), 2012–2028.

[42]

Chao Chen, Daqing Zhang, Pablo Samuel Castro, Nan Li, Lin Sun, and Shijian Li. 2011. Real-time detection of anomalous taxi trajectories from GPS traces. In Mobiquitous. 63–74.

[43]

Haiquan Chen, Wei-Shinn Ku, Haixun Wang, and Min-Te Sun. 2010. Leveraging spatio-temporal redundancy for RFID data cleansing. In SIGMOD. 51–62.

Digital Library

[44]

Jingyu Chen, Ping Chen, Qiuyan Huo, and Xuezhou Xu. 2011. Clustering network-constrained uncertain trajectories. In FSKD, Vol. 3. 1657–1662.

[45]

Jian Chen, Gang Ou, Ao Peng, Lingxiang Zheng, and Jianghong Shi. 2018. An INS/WiFi indoor localization system based on the weighted least squares. Sensors 18, 5 (2018), 1458.

[46]

Ling Chen, Yaya Cai, Yifang Ding, Mingqi Lv, Cuili Yuan, and Gencai Chen. 2016. Spatially fine-grained urban air quality estimation using ensemble semi-supervised learning and pruning. In UbiComp. 1076–1087.

Digital Library

[47]

Liang Chen, Sarang Thombre, Kimmo Järvinen, Elena Simona Lohan, Anette Alén-Savikko, Helena Leppäkoski, M. Zahidul H. Bhuiyan, Shakila Bu-Pasha, Giorgia Nunzia Ferrara, Salomon Honkala, et al. 2017. Robustness, security and privacy in location-based services for future IoT: A survey. IEEE Access 5 (2017), 8956–8977.

[48]

Xinyu Chen, Jiajie Xu, Rui Zhou, Wei Chen, Junhua Fang, and Chengfei Liu. 2021. TrajVAE: A Variational AutoEncoder model for trajectory generation. Neurocomputing 428 (2021), 332–339.

[49]

Xiao Chen and Shengnan Zou. 2017. Improved Wi-Fi indoor positioning based on particle swarm optimization. IEEE Sensors Journal 17, 21 (2017), 7143–7148.

[50]

Zhida Chen, Gao Cong, Zhenjie Zhang, Tom ZJ Fuz, and Lisi Chen. 2017. Distributed publish/subscribe query processing on the spatio-textual data stream. In ICDE. 1095–1106.

[51]

Qing Cheng, Huiqing Liu, Huanfeng Shen, Penghai Wu, and Liangpei Zhang. 2017. A spatial and temporal nonlocal filter-based data fusion method. IEEE Transactions on Geoscience and Remote Sensing 55, 8 (2017), 4476–4488.

[52]

Reynold Cheng, Jinchuan Chen, Mohamed Mokbel, and Chi-Yin Chow. 2008. Probabilistic verifiers: Evaluating constrained nearest-neighbor queries over uncertain data. In ICDE. 973–982.

Digital Library

[53]

Reynold Cheng, Tobias Emrich, Hans-Peter Kriegel, Nikos Mamoulis, Matthias Renz, Goce Trajcevski, and Andreas Züfle. 2014. Managing uncertainty in spatial and spatio-temporal data. In ICDE. 1302–1305.

[54]

Reynold Cheng, Dmitri V. Kalashnikov, and Sunil Prabhakar. 2004. Querying imprecise data in moving object environments. IEEE Transactions on Knowledge and Data Engineering 16, 9 (2004), 1112–1127.

Digital Library

[55]

Peng Dai, Yuan Yang, Manyi Wang, and Ruqiang Yan. 2019. Combination of DNN and improved KNN for indoor location fingerprinting. Wireless Communications and Mobile Computing 2019 (2019).

Digital Library

[56]

Xiangyuan Dai, Man Lung Yiu, Nikos Mamoulis, Yufei Tao, and Michail Vaitis. 2005. Probabilistic spatial queries on existentially uncertain data. In SSTD. 400–417.

Digital Library

[57]

Julio Cesar Stacchini de Souza, Tatiana Mariano Lessa Assis, and Bikash Chandra Pal. 2015. Data compression in smart distribution systems via singular value decomposition. IEEE Transactions on Smart Grid 8, 1 (2015), 275–284.

[58]

Rodolphe Devillers, Alfred Stein, Yvan Bédard, Nicholas Chrisman, Peter Fisher, and Wenzhong Shi. 2010. Thirty years of research on spatial data quality: Achievements, failures, and opportunities. Transactions in GIS 14, 4 (2010), 387–400.

[59]

Xin Ding, Lu Chen, Yunjun Gao, Christian S. Jensen, and Hujun Bao. 2018. UlTraMan: A unified platform for big trajectory data management and analytics. Proceedings of the VLDB Endowment 11, 7 (2018), 787–799.

Digital Library

[60]

Frederike Dümbgen, Cynthia Oeschger, Mihailo Kolundžija, Adam Scholefield, Emmanuel Girardin, Johan Leuenberger, and Serge Ayer. 2019. Multi-modal probabilistic indoor localization on a smartphone. In IPIN. 1–8.

[61]

Tobias Emrich, Hans-Peter Kriegel, Nikos Mamoulis, Johannes Niedermayer, Matthias Renz, and Andreas Züfle. 2014. Reverse-nearest neighbor queries on uncertain moving object trajectories. In DASFAA. 92–107.

[62]

Tobias Emrich, Hans-Peter Kriegel, Nikos Mamoulis, Matthias Renz, and Andreas Zufle. 2012. Querying uncertain spatio-temporal data. In ICDE. 354–365.

Digital Library

[63]

Xuming Fang, Zonghua Jiang, Lei Nan, and Lijun Chen. 2018. Optimal weighted K-nearest neighbour algorithm for wireless sensor network fingerprint localisation in noisy environment. IET Communications 12, 10 (2018), 1171–1177.

Digital Library

[64]

Bettina Fazzinga, Sergio Flesca, Filippo Furfaro, and Francesco Parisi. 2016. Exploiting integrity constraints for cleaning trajectories of RFID-monitored objects. ACM Transactions on Database Systems 41, 4 (2016), 1–52.

Digital Library

[65]

Kaiyu Feng, Tao Guo, Gao Cong, Sourav S. Bhowmick, and Shuai Ma. 2019. SURGE: Continuous detection of bursty regions over a stream of spatial objects. IEEE Transactions on Knowledge and Data Engineering 32, 11 (2019), 2254–2268.

[66]

Massimo Ficco, Christian Esposito, and Aniello Napolitano. 2013. Calibrating indoor positioning systems with low efforts. IEEE Transactions on Mobile Computing 13, 4 (2013), 737–751.

Digital Library

[67]

Yuyang Gao and Liang Zhao. 2018. Incomplete label multi-task ordinal regression for spatial event scale forecasting. In AAAI. 2999–3006.

Digital Library

[68]

Arthur Gatouillat, Youakim Badr, Bertrand Massot, and Ervin Sejdić. 2018. Internet of Medical Things: A review of recent contributions dealing with cyber-physical systems in medicine. IEEE Internet of Things Journal 5, 5 (2018), 3810–3822.

[69]

Davide Giovanelli, Elisabetta Farella, Daniele Fontanelli, and David Macii. 2018. Bluetooth-based indoor positioning through ToF and RSSI data fusion. In IPIN. 1–8.

[70]

Michael F. Goodchild. 1998. Uncertainty: The Achilles heel of GIS. Geo Info Systems 8, 11 (1998), 50–52.

[71]

Michael F. Goodchild. 2013. The quality of big (geo) data. Dialogues in Human Geography 3, 3 (2013), 280–284.

[72]

Chenjuan Guo, Bin Yang, Jilin Hu, and Christian S. Jensen. 2018. Learning to route with sparse trajectory sets. In ICDE. 1073–1084.

[73]

Cheng Guo, Ruhan Zhuang, Chunhua Su, Charles Zhechao Liu, and Kim-Kwang Raymond Choo. 2019. Secure and efficient k nearest neighbor query over encrypted uncertain data in cloud-IoT ecosystem. IEEE Internet of Things Journal 6, 6 (2019), 9868–9879.

[74]

Long Guo, Dongxiang Zhang, Guoliang Li, Kian-Lee Tan, and Zhifeng Bao. 2015. Location-aware pub/sub system: When continuous moving queries meet dynamic event streams. In SIGMOD. 843–857.

Digital Library

[75]

Manish Gupta, Jing Gao, Charu C. Aggarwal, and Jiawei Han. 2013. Outlier detection for temporal data: A survey. IEEE Transactions on Knowledge and Data Engineering 26, 9 (2013), 2250–2267.

Digital Library

[76]

Stephen C. Guptill and Joel L. Morrison. 2013. Elements of Spatial Data Quality. Elsevier.

[77]

Torsten Hägerstraand. 1970. What about people in regional science?Papers in Regional Science 24, 1 (1970), 7–24.

[78]

Yunheng Han, Weiwei Sun, and Baihua Zheng. 2017. COMPRESS: A comprehensive framework of trajectory compression in road networks. ACM Transactions on Database Systems 42, 2 (2017), 1–49.

Digital Library

[79]

Arif Hidayat, Muhammad Aamir Cheema, Xuemin Lin, Wenjie Zhang, and Ying Zhang. 2021. Continuous monitoring of moving skyline and top-k queries. The VLDB Journal (2021).

[80]

Minh Tu Hoang, Brosnan Yuen, Xiaodai Dong, Tao Lu, Robert Westendorp, and Kishore Reddy. 2019. Recurrent neural networks for accurate RSSI indoor localization. IEEE Internet of Things Journal 6, 6 (2019), 10639–10651.

[81]

Kathleen Hornsby and Max J. Egenhofer. 2002. Modeling moving objects over multiple granularities. Annals of Mathematics and Artificial Intelligence 36, 1 (2002), 177–194.

Digital Library

[82]

Saeid Hosseini, Hongzhi Yin, Xiaofang Zhou, Shazia Sadiq, Mohammad Reza Kangavari, and Ngai-Man Cheung. 2019. Leveraging multi-aspect time-related influence in location recommendation. World Wide Web Journal 22, 3 (2019), 1001–1028.

Digital Library

[83]

Chunchun Hu, Xionghua Kang, Nianxue Luo, and Qiansheng Zhao. 2015. Parallel clustering of big data of spatio-temporal trajectory. In ICNC. 769–774.

[84]

Ming Hua, Jian Pei, Wenjie Zhang, and Xuemin Lin. 2008. Ranking queries on uncertain data: A probabilistic threshold approach. In SIGMOD. 673–686.

Digital Library

[85]

Hailong Huang and Andrey V. Savkin. 2018. Towards the Internet of Flying Robots: A survey. Sensors 18, 11 (2018), 4038.

[86]

Yuan-Ko Huang, Chao-Chun Chen, and Chiang Lee. 2009. Continuous k-nearest neighbor query for moving objects with uncertain velocity. GeoInformatica 13, 1 (2009), 1–25.

Digital Library

[87]

George Rosario Jagadeesh and Thambipillai Srikanthan. 2014. Robust real-time route inference from sparse vehicle position data. In ITSC. 296–301.

[88]

Shawn R. Jeffery, Minos Garofalakis, and Michael J. Franklin. 2006. Adaptive cleaning for RFID data streams. Proceedings of the VLDB Endowment 6, 163–174.

Digital Library

[89]

Porter Jenkins, Ahmad Farag, Suhang Wang, and Zhenhui Li. 2019. Unsupervised representation learning of spatial data via multimodal embedding. In CIKM. 1993–2002.

Digital Library

[90]

Hoyoung Jeung, Hua Lu, Saket Sathe, and Man Lung Yiu. 2013. Managing evolving uncertainty in trajectory databases. IEEE Transactions on Knowledge and Data Engineering 26, 7 (2013), 1692–1705.

[91]

Yuanzhen Ji, Hongjin Zhou, Zbigniew Jerzak, Anisoara Nica, Gregor Hackenbroich, and Christof Fetzer. 2015. Quality-driven continuous query execution over out-of-order data streams. In SIGMOD. 889–894.

Digital Library

[92]

Zhe Jiang. 2018. A survey on spatial prediction methods. IEEE Transactions on Knowledge and Data Engineering 31, 9 (2018), 1645–1664.

Digital Library

[93]

Fengmei Jin, Wen Hua, Thomas Zhou, Jiajie Xu, Matteo Francia, Maria Orowska, and Xiaofang Zhou. 2020. Trajectory-based spatiotemporal entity linking. IEEE Transactions on Knowledge and Data Engineering (2020).

[94]

Ibrahim Kamel, Ayesha M. Talha, and Zaher Al Aghbari. 2017. Dynamic spatial index for efficient query processing on the cloud. Journal of Cloud Computing 6, 1 (2017), 1–16.

Digital Library

[95]

Aimad Karkouch, Hajar Mousannif, Hassan Al Moatassime, and Thomas Noel. 2016. Data quality in Internet of Things: A state-of-the-art survey. Journal of Network and Computer Applications 73 (2016), 57–81.

Digital Library

[96]

Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, and Pascal Poupart. 2020. Representation learning for dynamic graphs: A survey. Journal of Machine Learning Research 21, 70 (2020), 1–73.

[97]

Satoshi Koide, Yukihiro Tadokoro, Chuan Xiao, and Yoshiharu Ishikawa. 2018. CiNCT: Compression and retrieval for massive vehicular trajectories via relative movement labeling. In ICDE. 1097–1108.

[98]

Daniel Kuemper, Thorben Iggena, Ralf Toenjes, and Elke Pulvermueller. 2018. Valid.IoT: A framework for sensor data quality analysis and interpolation. In MMSys. 294–303.

Digital Library

[99]

Bart Kuijpers, Rafael Grimson, and Walied Othman. 2011. An analytic solution to the alibi query in the space–time prisms model for moving object data. International Journal of Geographical Information Science 25, 2 (2011), 293–322.

Digital Library

[100]

Bart Kuijpers, Harvey J. Miller, and Walied Othman. 2011. Kinetic space-time prisms. In SIGSPATIAL/GIS. 162–170.

Digital Library

[101]

Rajesh Kumar, Abdullah Aman Khan, Jay Kumar, A. Zakria, Noorbakhsh Amiri Golilarz, Simin Zhang, Yang Ting, Chengyu Zheng, and WenYong Wang. 2021. Blockchain-federated-learning and deep learning models for COVID-19 detection using CT imaging. IEEE Sensors Journal (2021).

[102]

Arnab Kumar Laha and Sayan Putatunda. 2018. Real time location prediction with taxi-GPS data streams. Transportation Research Part C: Emerging Technologies 92 (2018), 298–322.

[103]

Ralph Lange, Frank Dürr, and Kurt Rothermel. 2011. Efficient real-time trajectory tracking. The VLDB Journal 20, 5 (2011), 671–694.

Digital Library

[104]

Truc Viet Le, Siyuan Liu, and Hoong Chuin Lau. 2016. Reinforcement learning framework for modeling spatial sequential decisions under uncertainty. In AAMAS. 1449–1450.

Digital Library

[105]

Anliang Li, Shuang Wang, Wenzhu Li, Shengnan Liu, and Siyuan Zhang. 2020. Predicting human mobility with federated learning. In SIGSPATIAL. 441–444.

Digital Library

[106]

Bo Li, Omid Sarbishei, Hosein Nourani, and Tristan Glatard. 2018. A multi-dimensional extension of the lightweight temporal compression method. In IEEE Big Data. 2918–2923.

[107]

Chuanwen Li, Yu Gu, Jianzhong Qi, Ge Yu, Rui Zhang, and Wang Yi. 2014. Processing moving k NN queries using influential neighbor sets. Proceedings of the VLDB Endowment 8, 2 (2014), 113–124.

Digital Library

[108]

Deren Li, Jingxiong Zhang, and Huayi Wu. 2012. Spatial data quality and beyond. International Journal of Geographical Information Science 26, 12 (2012), 2277–2290.

Digital Library

[109]

Huan Li, Hua Lu, Muhammad Aamir Cheema, Lidan Shou, and Gang Chen. 2020. Indoor mobility semantics annotation using coupled conditional Markov networks. In ICDE. 1441–1452.

[110]

Huan Li, Hua Lu, Gang Chen, Ke Chen, Qinkuang Chen, and Lidan Shou. 2020. Toward translating raw indoor positioning data into mobility semantics. ACM/IMS Transactions on Data Science 1, 4 (2020), 1–37.

Digital Library

[111]

Huan Li, Hua Lu, Lidan Shou, Gang Chen, and Ke Chen. 2018. Finding most popular indoor semantic locations using uncertain mobility data. IEEE Transactions on Knowledge and Data Engineering 31, 11 (2018), 2108–2123.

[112]

Huan Li, Hua Lu, Lidan Shou, Gang Chen, and Ke Chen. 2018. In search of indoor dense regions: An approach using indoor positioning data. IEEE Transactions on Knowledge and Data Engineering 30, 8 (2018), 1481–1495.

[113]

Jiayu Li, Haoran Li, Yehan Ma, Yang Wang, Ahmed A. Abokifa, Chenyang Lu, and Pratim Biswas. 2018. Spatiotemporal distribution of indoor particulate matter concentration with a low-cost sensor network. Building and Environment 127 (2018), 138–147.

[114]

Lingxiao Li, Muhammad Aamir Cheema, Mohammed Eunus Ali, Hua Lu, and David Taniar. 2020. Continuously monitoring alternative shortest paths on road networks. Proceedings of the VLDB Endowment 13, 12 (2020), 2243–2255.

Digital Library

[115]

Lun Li, Xiaohang Chen, Qizhi Liu, and Zhifeng Bao. 2020. A data-driven approach for GPS trajectory data cleaning. In DASFAA. 3–19.

[116]

Lixin Li, Xingyou Zhang, James B. Holt, Jie Tian, and Reinhard Piltner. 2011. Spatiotemporal interpolation methods for air pollution exposure. In SARA.

[117]

Songnian Li, Suzana Dragicevic, Francesc Antón Castro, Monika Sester, Stephan Winter, Arzu Coltekin, Christopher Pettit, Bin Jiang, James Haworth, Alfred Stein, et al. 2016. Geospatial big data handling theory and methods: A review and research challenges. ISPRS Journal of Photogrammetry and Remote Sensing 115 (2016), 119–133.

[118]

Tianyi Li, Lu Chen, Christian S. Jensen, and Torben Bach Pedersen. 2021. TRACE: Real-time compression of streaming trajectories in road networks. Proceedings of the VLDB Endowment 14, 7 (2021), 1175–1187.

Digital Library

[119]

Tianyi Li, Ruikai Huang, Lu Chen, Christian S. Jensen, and Torben Bach Pedersen. 2020. Compression of uncertain trajectories in road networks. Proceedings of the VLDB Endowment 13, 7 (2020), 1050–1063.

Digital Library

[120]

Yuxuan Li, James Bailey, Lars Kulik, and Jian Pei. 2013. Mining probabilistic frequent spatio-temporal sequential patterns with gap constraints from uncertain databases. In ICDM. 448–457.

[121]

Yang Li, Yangyan Li, Dimitrios Gunopulos, and Leonidas Guibas. 2016. Knowledge-based trajectory completion from sparse GPS samples. In SIGSPATIAL. 1–10.

Digital Library

[122]

You Li, Yuan Zhuang, Xin Hu, Zhouzheng Gao, Jia Hu, Long Chen, Zhe He, Ling Pei, Kejie Chen, Maosong Wang, et al. 2020. Location-Enabled IoT (LE-IoT): A survey of positioning techniques, error sources, and mitigation. arXiv preprint arXiv:2004.03738 (2020).

[123]

Zhenhui Li and Jiawei Han. 2014. Mining periodicity from dynamic and incomplete spatiotemporal data. In Data Mining and Knowledge Discovery for Big Data. 41–81.

[124]

Xiang Lian and Lei Chen. 2009. Efficient processing of probabilistic reverse nearest neighbor queries over uncertain data. The VLDB Journal 18, 3 (2009), 787–808.

Digital Library

[125]

Lin Liao, Dieter Fox, and Henry Kautz. 2007. Extracting places and activities from GPS traces using hierarchical conditional random fields. The International Journal of Robotics Research 26, 1 (2007), 119–134.

Digital Library

[126]

Lin Liao, Donald J. Patterson, Dieter Fox, and Henry Kautz. 2007. Learning and inferring transportation routines. Artificial Intelligence 171, 5-6 (2007), 311–331.

Digital Library

[127]

Lu Lin, Jianxin Li, Feng Chen, Jieping Ye, and Jinpeng Huai. 2017. Road traffic speed prediction: A probabilistic model fusing multi-source data. IEEE Transactions on Knowledge and Data Engineering 30, 7 (2017), 1310–1323.

[128]

Xuelian Lin, Jiahao Jiang, Shuai Ma, Yimeng Zuo, and Chunming Hu. 2019. One-pass trajectory simplification using the synchronous Euclidean distance. The VLDB Journal 28, 6 (2019), 897–921.

[129]

Xuelian Lin, Shuai Ma, Jiahao Jiang, Yanchen Hou, and Tianyu Wo. 2021. Error bounded line simplification algorithms for trajectory compression: An experimental evaluation. ACM Transactions on Database Systems 46, 3 (2021), 1–44.

Digital Library

[130]

Yijun Lin, Yao-Yi Chiang, Fan Pan, Dimitrios Stripelis, José Luis Ambite, Sandrah P. Eckel, and Rima Habre. 2017. Mining public datasets for modeling intra-city PM2.5 concentrations at a fine spatial resolution. In SIGSPATIAL. 1–10.

Digital Library

[131]

Caihua Liu, Patrick Nitschke, Susan P. Williams, and Didar Zowghi. 2020. Data quality and the Internet of Things. Computing 102, 2 (2020), 573–599.

Digital Library

[132]

Chuanren Liu, Hui Xiong, Yong Ge, Wei Geng, and Matt Perkins. 2012. A stochastic model for context-aware anomaly detection in indoor location traces. In ICDE. 449–458.

Digital Library

[133]

Hui Liu, Houshang Darabi, Pat Banerjee, and Jing Liu. 2007. Survey of wireless indoor positioning techniques and systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 37, 6 (2007), 1067–1080.

Digital Library

[134]

Jingbin Liu, Ruizhi Chen, Ling Pei, Robert Guinness, and Heidi Kuusniemi. 2012. A hybrid smartphone indoor positioning solution for mobile LBS. Sensors 12, 12 (2012), 17208–17233.

[135]

Jia Liu, Tianrui Li, Peng Xie, Shengdong Du, Fei Teng, and Xin Yang. 2020. Urban big data fusion based on deep learning: An overview. Information Fusion 53 (2020), 123–133.

Digital Library

[136]

Jiajun Liu, Kun Zhao, Philipp Sommer, Shuo Shang, Brano Kusy, and Raja Jurdak. 2015. Bounded quadrant system: Error-bounded trajectory compression on the go. In ICDE. 987–998.

[137]

Jiajun Liu, Kun Zhao, Philipp Sommer, Shuo Shang, Brano Kusy, Jae-Gil Lee, and Raja Jurdak. 2016. A novel framework for online amnesic trajectory compression in resource-constrained environments. IEEE Transactions on Knowledge and Data Engineering 28, 11 (2016), 2827–2841.

Digital Library

[138]

Mo Liu, Ming Li, Denis Golovnya, Elke A. Rundensteiner, and Kajal Claypool. 2009. Sequence pattern query processing over out-of-order event streams. In ICDE. 784–795.

Digital Library

[139]

Qiyu Liu, Xiang Lian, and Lei Chen. 2019. Probabilistic maximum range-sum queries on spatial database. In SIGSPATIAL. 159–168.

Digital Library

[140]

Siyuan Liu and Shuhui Wang. 2016. Trajectory community discovery and recommendation by multi-source diffusion modeling. IEEE Transactions on Knowledge and Data Engineering 29, 4 (2016), 898–911.

Digital Library

[141]

Yi Liu, J. Q. James, Jiawen Kang, Dusit Niyato, and Shuyu Zhang. 2020. Privacy-preserving traffic flow prediction: A federated learning approach. IEEE Internet of Things Journal 7, 8 (2020), 7751–7763.

[142]

Yiding Liu, Kaiqi Zhao, Gao Cong, and Zhifeng Bao. 2020. Online anomalous trajectory detection with deep generative sequence modeling. In ICDE. 949–960.

[143]

Stuart Lloyd. 1982. Least squares quantization in PCM. IEEE Transactions on Information Theory 28, 2 (1982), 129–137.

Digital Library

[144]

Cheng Long, Raymond Chi-Wing Wong, and H. V. Jagadish. 2014. Trajectory simplification: On minimizing the direction-based error. Proceedings of the VLDB Endowment 8, 1 (2014), 49–60.

Digital Library

[145]

Hua Lu, Chenjuan Guo, Bin Yang, and Christian S. Jensen. 2016. Finding frequently visited indoor POIs using symbolic indoor tracking data. In EDBT. 449–460.

[146]

Hua Lu, Bin Yang, and Christian S. Jensen. 2011. Spatio-temporal joins on symbolic indoor tracking data. In ICDE. 816–827.

Digital Library

[147]

Haidong Luo, Hongming Cai, Han Yu, Yan Sun, Zhuming Bi, and Lihong Jiang. 2019. A short-term energy prediction system based on edge computing for smart city. Future Generation Computer Systems 101 (2019), 444–457.

Digital Library

[148]

Chunyang Ma, Hua Lu, Lidan Shou, and Gang Chen. 2012. KSQ: Top-k similarity query on uncertain trajectories. IEEE Transactions on Knowledge and Data Engineering 25, 9 (2012), 2049–2062.

Digital Library

[149]

Altti Ilari Maarala, Xiang Su, and Jukka Riekki. 2016. Semantic reasoning for context-aware Internet of Things applications. IEEE Internet of Things Journal 4, 2 (2016), 461–473.

[150]

Pavel Mach and Zdenek Becvar. 2017. Mobile edge computing: A survey on architecture and computation offloading. IEEE Communications Surveys & Tutorials 19, 3 (2017), 1628–1656.

Digital Library

[151]

Michele Magno, Xiaying Wang, Manuel Eggimann, Lukas Cavigelli, and Luca Benini. 2020. InfiniWolf: Energy efficient smart bracelet for edge computing with dual source energy harvesting. In DATE. 342–345.

Digital Library

[152]

Mohammad Saeid Mahdavinejad, Mohammadreza Rezvan, Mohammadamin Barekatain, Peyman Adibi, Payam Barnaghi, and Amit P. Sheth. 2018. Machine learning for Internet of Things data analysis: A survey. Digital Communications and Networks 4, 3 (2018), 161–175.

[153]

Ahmed R. Mahmood, Ahmed M. Aly, Thamir Qadah, El Kindi Rezig, Anas Daghistani, Amgad Madkour, Ahmed S. Abdelhamid, Mohamed S. Hassan, Walid G. Aref, and Saleh Basalamah. 2015. Tornado: A distributed spatio-textual stream processing system. Proceedings of the VLDB Endowment 8, 12 (2015), 2020–2023.

Digital Library

[154]

Jiali Mao, Jiaye Liu, Cheqing Jin, and Aoying Zhou. 2021. Feature grouping–based trajectory outlier detection over distributed streams. ACM Transactions on Intelligent Systems and Technology 12, 2 (2021), 1–23.

Digital Library

[155]

Shunmei Meng, Lianyong Qi, Qianmu Li, Wenmin Lin, Xiaolong Xu, and Shaohua Wan. 2019. Privacy-preserving and sparsity-aware location-based prediction method for collaborative recommender systems. Future Generation Computer Systems 96 (2019), 324–335.

Digital Library

[156]

Weixiao Meng, Ying He, Zhian Deng, and Cheng Li. 2012. Optimized access points deployment for WLAN indoor positioning system. In WCNC. 2457–2461.

[157]

Mostafa Milani, Zheng Zheng, and Fei Chiang. 2019. CurrentClean: Spatio-temporal cleaning of stale data. In ICDE. 172–183.

[158]

Mehdi Mohammadi, Ala Al-Fuqaha, Sameh Sorour, and Mohsen Guizani. 2018. Deep learning for IoT big data and streaming analytics: A survey. IEEE Communications Surveys & Tutorials 20, 4 (2018), 2923–2960.

Digital Library

[159]

Jonathan Muckell, Jeong-Hyon Hwang, Vikram Patil, Catherine T. Lawson, Fan Ping, and S. S. Ravi. 2011. SQUISH: An online approach for GPS trajectory compression. In COM.Geo. 1–8.

Digital Library

[160]

Jonathan Muckell, Paul W. Olsen, Jeong-Hyon Hwang, Catherine T. Lawson, and S. S. Ravi. 2014. Compression of trajectory data: A comprehensive evaluation and new approach. GeoInformatica 18, 3 (2014), 435–460.

Digital Library

[161]

Raül Muñoz, Ricard Vilalta, Noboru Yoshikane, Ramon Casellas, Ricardo Martínez, Takehiro Tsuritani, and Itsuro Morita. 2018. Integration of IoT, transport SDN, and edge/cloud computing for dynamic distribution of IoT analytics and efficient use of network resources. IEEE Journal of Lightwave Technology 36, 7 (2018), 1420–1428.

[162]

Christopher Mutschler and Michael Philippsen. 2013. Distributed low-latency out-of-order event processing for high data rate sensor streams. In IPDPS. 1133–1144.

Digital Library

[163]

Kapileswar Nellore and Gerhard P. Hancke. 2016. A survey on urban traffic management system using wireless sensor networks. Sensors 16, 2 (2016), 157.

[164]

Long H. Nguyen, Jiazhen Zhu, Zhe Lin, Hanxiang Du, Zhou Yang, Wenxuan Guo, and Fang Jin. 2019. Spatial-temporal multi-task learning for within-field cotton yield prediction. In PAKDD. 343–354.

[165]

Dragoş Niculescu and Badri Nath. 2003. DV based positioning in ad hoc networks. Telecommunication Systems 22, 1 (2003), 267–280.

Digital Library

[166]

Johannes Niedermayer, Andreas Züfle, Tobias Emrich, Matthias Renz, Nikos Mamoulis, Lei Chen, and Hans-Peter Kriegel. 2013. Probabilistic nearest neighbor queries on uncertain moving object trajectories. Proceedings of the VLDB Endowment 7, 3 (2013), 205–216.

Digital Library

[167]

Tales P. Nogueira, Reinaldo B. Braga, Carina T. de Oliveira, and Hervé Martin. 2018. FrameSTEP: A framework for annotating semantic trajectories based on episodes. Expert Systems with Applications 92 (2018), 533–545.

Digital Library

[168]

Sarana Nutanong, Rui Zhang, Egemen Tanin, and Lars Kulik. 2010. Analysis and evaluation of v*-k nn: An efficient algorithm for moving k nn queries. The VLDB Journal 19, 3 (2010), 307–332.

Digital Library

[169]

Nwamaka U. Okafor, Yahia Alghorani, and Declan T. Delaney. 2020. Improving data quality of low-cost IoT sensors in environmental monitoring networks using data fusion and machine learning approach. ICT Express 6, 3 (2020), 220–228.

[170]

Robin Wentao Ouyang, Mani Srivastava, Alice Toniolo, and Timothy J. Norman. 2015. Truth discovery in crowdsourced detection of spatial events. IEEE Transactions on Knowledge and Data Engineering 28, 4 (2015), 1047–1060.

Digital Library

[171]

Vikram Patil, Priyanka Singh, Shivam Parikh, and Pradeep K. Atrey. 2018. Geosclean: Secure cleaning of GPS trajectory data using anomaly detection. In MIPR. 166–169.

[172]

Jian Pei, Bin Jiang, Xuemin Lin, and Yidong Yuan. 2007. Probabilistic skylines on uncertain data. In VLDB. 15–26.

Digital Library

[173]

Douglas Alves Peixoto, Xiaofang Zhou, Nguyen Quoc Viet Hung, Dan He, and Bela Stantic. 2018. A system for spatial-temporal trajectory data integration and representation. In DASFAA. 807–812.

[174]

Nikos Pelekis, Ioannis Kopanakis, Evangelos E Kotsifakos, Elias Frentzos, and Yannis Theodoridis. 2011. Clustering uncertain trajectories. Knowledge and Information Systems 28, 1 (2011), 117–147.

Digital Library

[175]

Ricardo Perez-Castillo, Ana G. Carretero, Moises Rodriguez, Ismael Caballero, Mario Piattini, Alejandro Mate, Sunho Kim, and Dongwoo Lee. 2018. Data quality best practices in IoT environments. In QUATIC. 272–275.

[176]

Dieter Pfoser and Christian S. Jensen. 1999. Capturing the uncertainty of moving-object representations. In SSD. 111–131.

Digital Library

[177]

Iulian Sandu Popa, Karine Zeitouni, Vincent Oria, and Ahmed Kharrat. 2015. Spatio-temporal compression of trajectories in road networks. GeoInformatica 19, 1 (2015), 117–145.

Digital Library

[178]

Sitthapon Pumpichet, Niki Pissinou, Xinyu Jin, and Deng Pan. 2012. Belief-based cleaning in trajectory sensor streams. In ICC. 208–212.

[179]

Apostolos Pyrgelis, Emiliano De Cristofaro, and Gordon J. Ross. 2016. Privacy-friendly mobility analytics using aggregate location data. In SIGSPATIAL. 1–10.

Digital Library

[180]

Jianzhong Qi, Rui Zhang, Christian S. Jensen, Kotagiri Ramamohanarao, and Jiayuan He. 2018. Continuous spatial query processing: A survey of safe region based techniques. Comput. Surveys 51, 3 (2018), 1–39.

Digital Library

[181]

Shaojie Qiao, Changjie Tang, Huidong Jin, Teng Long, Shucheng Dai, Yungchang Ku, and Michael Chau. 2010. PutMode: Prediction of uncertain trajectories in moving objects databases. Applied Intelligence 33, 3 (2010), 370–386.

Digital Library

[182]

M. Mazhar Rathore, Awais Ahmad, Anand Paul, and Seungmin Rho. 2016. Urban planning and building smart cities based on the Internet of Things using big data analytics. Computer Networks 101 (2016), 63–80.

Digital Library

[183]

Suprio Ray, Bogdan Simion, Angela Demke Brown, and Ryan Johnson. 2013. A parallel spatial data analysis infrastructure for the cloud. In SIGSPATIAL. 284–293.

Digital Library

[184]

Fabio Sartori, Riccardo Melen, and Fabio Giudici. 2019. IoT data validation using spatial and temporal correlations. In MTSR. 77–89.

[185]

Omer Berat Sezer, Erdogan Dogdu, and Ahmet Murat Ozbayoglu. 2017. Context-aware computing, learning, and big data in Internet of Things: A survey. IEEE Internet of Things Journal 5, 1 (2017), 1–27.

[186]

Rathin Chandra Shit, Suraj Sharma, Deepak Puthal, and Albert Y. Zomaya. 2018. Location of Things (LoT): A review and taxonomy of sensors localization in IoT infrastructure. IEEE Communications Surveys & Tutorials 20, 3 (2018), 2028–2061.

[187]

Eugene Siow, Thanassis Tiropanis, and Wendy Hall. 2018. Analytics for the Internet of Things: A survey. Comput. Surveys 51, 4 (2018), 1–36.

Digital Library

[188]

Shaoxu Song, Ruihong Huang, Yue Cao, and Jianmin Wang. 2021. Cleaning timestamps with temporal constraints. The VLDB Journal (2021), 1–22.

[189]

Shaoxu Song and Aoqian Zhang. 2020. IoT data quality. In CIKM. 3517–3518.

Digital Library

[190]

Xiaozhao Song, Jiajie Xu, Rui Zhou, Chengfei Liu, Kai Zheng, Pengpeng Zhao, and Nickolas Falkner. 2020. Collective spatial keyword search on activity trajectories. GeoInformatica 24, 1 (2020), 61–84.

Digital Library

[191]

Han Su, Kai Zheng, Haozhou Wang, Jiamin Huang, and Xiaofang Zhou. 2013. Calibrating trajectory data for similarity-based analysis. In SIGMOD. 833–844.

Digital Library

[192]

Lijun Sun, Xiaojie Yu, Jiachen Guo, Yang Yan, and Xu Yu. 2021. Deep reinforcement learning for task assignment in spatial crowdsourcing and sensing. IEEE Sensors Journal (2021).

[193]

Lu Sun, Wei Zhou, Baichen Jiang, and Jian Guan. 2017. A real-time similarity measure model for multi-source trajectories. In CIIS. 257–262.

[194]

Zi-Yun Sun, Ming-Che Tsai, and Hsiao-Ping Tsai. 2014. Mining uncertain sequence data on Hadoop platform. In PAKDD. 204–215.

[195]

Ferry Susanto, Paulo De Souza, and Jing He. 2016. Spatiotemporal interpolation for environmental modelling. Sensors 16, 8 (2016), 1245.

[196]

Romana Talat, Mohammad S. Obaidat, Muhammad Muzammal, Ali Hassan Sodhro, Zongwei Luo, and Sandeep Pirbhulal. 2020. A decentralised approach to privacy preserving trajectory mining. Future Generation Computer Systems 102 (2020), 382–392.

Digital Library

[197]

Liansheng Tan and Mou Wu. 2015. Data reduction in wireless sensor networks: A hierarchical LMS prediction approach. IEEE Sensors Journal 16, 6 (2015), 1708–1715.

[198]

Luliang Tang, Xue Yang, Zihan Kan, and Qingquan Li. 2015. Lane-level road information mining from vehicle GPS trajectories based on Naïve Bayesian classification. ISPRS International Journal of Geo-Information 4, 4 (2015), 2660–2680.

[199]

Xianfeng Tang, Boqing Gong, Yanwei Yu, Huaxiu Yao, Yandong Li, Haiyong Xie, and Xiaoyu Wang. 2019. Joint modeling of dense and incomplete trajectories for citywide traffic volume inference. In WWW. 1806–1817.

Digital Library

[200]

Yufei Tao, Xiaokui Xiao, and Reynold Cheng. 2007. Range search on multidimensional uncertain data. ACM Transactions on Database Systems 32, 3 (2007), 15–es.

Digital Library

[201]

Joseph Euzebe Tate. 2015. Preprocessing and Golomb-Rice encoding for lossless compression of phasor angle data. IEEE Transactions on Smart Grid 7, 2 (2015), 718–729.

[202]

Christopher Taylor, Ali Rahimi, Jonathan Bachrach, Howard Shrobe, and Anthony Grue. 2006. Simultaneous localization, calibration, and tracking in an ad hoc sensor network. In IPSN. 27–33.

Digital Library

[203]

Shan-Yun Teng, Wei-Shinn Ku, and Kun-Ta Chuang. 2017. Toward mining stop-by behaviors in indoor space. ACM Transactions on Spatial Algorithms and Systems 3, 2 (2017), 1–38.

Digital Library

[204]

Waldo R. Tobler. 1970. A computer movie simulating urban growth in the Detroit region. Economic geography 46, sup1 (1970), 234–240.

[205]

Goce Trajcevski, Alok Choudhary, Ouri Wolfson, Li Ye, and Gang Li. 2010. Uncertain range queries for necklaces. In MDM. 199–208.

Digital Library

[206]

Goce Trajcevski, Roberto Tamassia, Hui Ding, Peter Scheuermann, and Isabel F. Cruz. 2009. Continuous probabilistic nearest-neighbor queries for uncertain trajectories. In EDBT. 874–885.

Digital Library

[207]

Sharda Tripathi and Swades De. 2018. An efficient data characterization and reduction scheme for smart metering infrastructure. IEEE Transactions on Industrial Informatics 14, 10 (2018), 4300–4308.

[208]

Chun-Wei Tsai, Chin-Feng Lai, Ming-Chao Chiang, and Laurence T. Yang. 2013. Data mining for Internet of Things: A survey. IEEE Communications Surveys & Tutorials 16, 1 (2013), 77–97.

[209]

M. Jeroen Van Der Donckt, Danny Weyns, M. Usman Iftikhar, and Ritesh Kumar Singh. 2018. Cost-benefit analysis at runtime for self-adaptive systems applied to an Internet of Things application. In ENASE. 478–490.

Digital Library

[210]

Hoang Vo, Ablimit Aji, and Fusheng Wang. 2014. SATO: A spatial data partitioning framework for scalable query processing. In SIGSPATIAL. 545–548.

Digital Library

[211]

Khuong Vu and Rong Zheng. 2013. Efficient algorithms for spatial skyline query with uncertainty. In SIGSPATIAL. 412–415.

Digital Library

[212]

Jiangtao Wang, Yasha Wang, Daqing Zhang, Feng Wang, Haoyi Xiong, Chao Chen, Qin Lv, and Zhaopeng Qiu. 2018. Multi-task allocation in mobile crowd sensing with individual task quality assurance. IEEE Transactions on Mobile Computing 17, 9 (2018), 2101–2113.

Digital Library

[213]

Lizhen Wang, Pinping Wu, and Hongmei Chen. 2011. Finding probabilistic prevalent colocations in spatially uncertain data sets. IEEE Transactions on Knowledge and Data Engineering 25, 4 (2011), 790–804.

Digital Library

[214]

Peixiao Wang, Fei Gao, Yuhui Zhao, Ming Li, and Xinyan Zhu. 2020. Detection of indoor high-density crowds via Wi-Fi tracking data. Sensors 20, 18 (2020), 5078.

[215]

Pu Wang, Jiyu Lai, Zhiren Huang, Qian Tan, and Tao Lin. 2020. Estimating traffic flow in large road networks based on multi-source traffic data. IEEE Transactions on Intelligent Transportation Systems (2020).

[216]

Sheng Wang, Zhifeng Bao, J. Shane Culpepper, Timos Sellis, and Xiaolin Qin. 2019. Fast large-scale trajectory clustering. Proceedings of the VLDB Endowment 13, 1 (2019), 29–42.

Digital Library

[217]

Wei Wang, Feng Xia, Hansong Nie, Zhikui Chen, Zhiguo Gong, Xiangjie Kong, and Wei Wei. 2020. Vehicle trajectory clustering based on dynamic representation learning of Internet of Vehicles. IEEE Transactions on Intelligent Transportation Systems (2020).

[218]

Zheng Wang, Cheng Long, and Gao Cong. 2021. Trajectory simplification with reinforcement learning. In ICDE.

[219]

Zhanquan Wang, Bowen Lu, Fangli Ying, Man Kong, and Minwei Tang. 2017. Research of mining algorithms for uncertain spatio-temporal co-occurrence pattern. In KST. 12–17.

[220]

Zhi-Jie Wang, Dong-Hua Wang, Bin Yao, and Minyi Guo. 2014. Probabilistic range query over uncertain moving objects in constrained two-dimensional space. IEEE Transactions on Knowledge and Data Engineering 27, 3 (2014), 866–879.

Digital Library

[221]

Ling-Yin Wei, Ya-Ting Hsu, Wen-Chih Peng, and Wang-Chien Lee. 2014. Indexing spatial data in cloud data managements. Pervasive and Mobile Computing 15 (2014), 48–61.

Digital Library

[222]

Ling-Yin Wei, Yu Zheng, and Wen-Chih Peng. 2012. Constructing popular routes from uncertain trajectories. In KDD. 195–203.

Digital Library

[223]

Robert Weibel. 1996. Generalization of spatial data: Principles and selected algorithms. In Algorithmic Foundations of Geographic Information Systems. 99–152.

Digital Library

[224]

Fei Wu and Zhenhui Li. 2016. Where did you go: Personalized annotation of mobility records. In CIKM. 589–598.

Digital Library

[225]

Fei Wu, Zhenhui Li, Wang-Chien Lee, Hongjian Wang, and Zhuojie Huang. 2015. Semantic annotation of mobility data using social media. In WWW. 1253–1263.

Digital Library

[226]

Hao Wu, Jiangyun Mao, Weiwei Sun, Baihua Zheng, Hanyuan Zhang, Ziyang Chen, and Wei Wang. 2016. Probabilistic robust route recovery with spatio-temporal dynamics. In KDD. 1915–1924.

Digital Library

[227]

Hao Wu, Weiwei Sun, and Baihua Zheng. 2017. A fast trajectory outlier detection approach via driving behavior modeling. In CIKM. 837–846.

Digital Library

[228]

Yanbo Wu, Hong Shen, and Quan Z. Sheng. 2014. A cloud-friendly RFID trajectory clustering algorithm in uncertain environments. IEEE Transactions on Parallel and Distributed Systems 26, 8 (2014), 2075–2088.

Digital Library

[229]

Zheng Wu, Esrafil Jedari, Roberto Muscedere, and Rashid Rashidzadeh. 2016. Improved particle filter based on WLAN RSSI fingerprinting and smart sensors for indoor localization. Computer Communications 83 (2016), 64–71.

Digital Library

[230]

Zhenyu Wu, Yuan Xu, Yunong Yang, Chunhong Zhang, Xinning Zhu, and Yang Ji. 2017. Towards a semantic Web of Things: A hybrid semantic annotation, extraction, and reasoning framework for cyber-physical system. Sensors 17, 2 (2017), 403.

[231]

Dong Xie, Feifei Li, and Jeff M. Phillips. 2017. Distributed trajectory similarity search. Proceedings of the VLDB Endowment 10, 11 (2017), 1478–1489.

Digital Library

[232]

Xike Xie, Hua Lu, and Torben Bach Pedersen. 2013. Efficient distance-aware query evaluation on indoor moving objects. In ICDE. 434–445.

Digital Library

[233]

Xike Xie, Hua Lu, and Torben Bach Pedersen. 2014. Distance-aware join for indoor moving objects. IEEE Transactions on Knowledge and Data Engineering 27, 2 (2014), 428–442.

[234]

Jianqiu Xu and Ralf Hartmut Güting. 2013. A generic data model for moving objects. GeoInformatica 17, 1 (2013), 125–172.

Digital Library

[235]

Wenchao Xu, Haibo Zhou, Nan Cheng, Feng Lyu, Weisen Shi, Jiayin Chen, and Xuemin Shen. 2017. Internet of Vehicles in big data era. IEEE/CAA Journal of Automatica Sinica 5, 1 (2017), 19–35.

[236]

Yongyang Xu, Zhanlong Chen, Zhong Xie, and Liang Wu. 2017. Quality assessment of building footprint data using a deep autoencoder network. International Journal of Geographical Information Science 31, 10 (2017), 1929–1951.

Digital Library

[237]

Ying Xu, Dongxiang Zhang, Meihui Zhang, Dongsheng Li, Xiaoling Wang, and Heng Tao Shen. 2018. Continuous proximity detection via predictive safe region construction. In ICDE. 629–640.

[238]

Da Yan, Zhou Zhao, Wilfred Ng, and Steven Liu. 2014. Probabilistic convex hull queries over uncertain data. IEEE Transactions on Knowledge and Data Engineering 27, 3 (2014), 852–865.

Digital Library

[239]

Zhixian Yan, Dipanjan Chakraborty, Christine Parent, Stefano Spaccapietra, and Karl Aberer. 2013. Semantic trajectories: Mobility data computation and annotation. ACM Transactions on Intelligent Systems and Technology 4, 3 (2013), 1–38.

Digital Library

[240]

Bin Yang, Hua Lu, and Christian S. Jensen. 2009. Scalable continuous range monitoring of moving objects in symbolic indoor space. In CIKM. 671–680.

Digital Library

[241]

Bin Yang, Hua Lu, and Christian S. Jensen. 2010. Probabilistic threshold k nearest neighbor queries over moving objects in symbolic indoor space. In EDBT. 335–346.

Digital Library

[242]

Dingyu Yang, Dongxiang Zhang, Kian-Lee Tan, Jian Cao, and Frédéric Le Mouël. 2014. CANDS: Continuous optimal navigation via distributed stream processing. Proceedings of the VLDB Endowment 8, 2 (2014), 137–148.

Digital Library

[243]

Xiaochun Yang, Bin Wang, Kai Yang, Chengfei Liu, and Baihua Zheng. 2017. A novel representation and compression for queries on trajectories in road networks. IEEE Transactions on Knowledge and Data Engineering 30, 4 (2017), 613–629.

[244]

Yuqing Yang, Jianghui Cai, Haifeng Yang, Jifu Zhang, and Xujun Zhao. 2020. TAD: A trajectory clustering algorithm based on spatial-temporal density analysis. Expert Systems with Applications 139 (2020), 112846.

Digital Library

[245]

Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, and Zhenhui Li. 2019. Learning from multiple cities: A meta-learning approach for spatial-temporal prediction. In WWW. 2181–2191.

Digital Library

[246]

Ibrar Yaqoob, Ejaz Ahmed, Ibrahim Abaker Targio Hashem, Abdelmuttlib Ibrahim Abdalla Ahmed, Abdullah Gani, Muhammad Imran, and Mohsen Guizani. 2017. Internet of Things architecture: Recent advances, taxonomy, requirements, and open challenges. IEEE Wireless Communications 24, 3 (2017), 10–16.

Digital Library

[247]

Jaegeol Yim, Chansik Park, Jaehun Joo, and Seunghwan Jeong. 2008. Extended Kalman filter for wireless LAN based indoor positioning. Decision Support Systems 45, 4 (2008), 960–971.

Digital Library

[248]

Yihang Yin, Fengzheng Liu, Xiang Zhou, and Quanzhong Li. 2015. An efficient data compression model based on spatial clustering and principal component analysis in wireless sensor networks. Sensors 15, 8 (2015), 19443–19465.

[249]

Man Lung Yiu, Gabriel Ghinita, Christian S. Jensen, and Panos Kalnis. 2010. Enabling search services on outsourced private spatial data. The VLDB Journal 19, 3 (2010), 363–384.

Digital Library

[250]

Simin You, Jianting Zhang, and Le Gruenwald. 2015. Large-scale spatial join query processing in cloud. In ICDE Workshops. 34–41.

[251]

Jiao Yu, Wei-Shinn Ku, Min-Te Sun, and Hua Lu. 2013. An RFID and particle filter-based indoor spatial query evaluation system. In EDBT. 263–274.

Digital Library

[252]

Haitao Yuan and Guoliang Li. 2019. Distributed in-memory trajectory similarity search and join on road network. In ICDE. 1262–1273.

[253]

Shuai Yuan, Jiayu Zhou, Pang-Ning Tan, Emi Fergus, Tyler Wagner, and Patricia Soranno. 2017. Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data. In ICDM. 1153–1158.

[254]

Liming Zhan, Ying Zhang, Wenjie Zhang, and Xuemin Lin. 2015. Finding top k most influential spatial facilities over uncertain objects. IEEE Transactions on Knowledge and Data Engineering 27, 12 (2015), 3289–3303.

Digital Library

[255]

Aoqian Zhang, Shaoxu Song, and Jianmin Wang. 2016. Sequential data cleaning: A statistical approach. In SIGMOD. 909–924.

Digital Library

[256]

Aoqian Zhang, Shaoxu Song, Jianmin Wang, and Philip S. Yu. 2017. Time series data cleaning: From anomaly detection to anomaly repairing. Proceedings of the VLDB Endowment 10, 10 (2017), 1046–1057.

Digital Library

[257]

Bing Zhang, Goce Trajcevski, and Liu Liu. 2016. Towards fusing uncertain location data from heterogeneous sources. GeoInformatica 20, 2 (2016), 179–212.

Digital Library

[258]

Chao Zhang, Yu Zheng, Xiuli Ma, and Jiawei Han. 2015. Assembler: Efficient discovery of spatial co-evolving patterns in massive geo-sensory data. In KDD. 1415–1424.

Digital Library

[259]

Dongxiang Zhang, Zhihao Chang, Sai Wu, Ye Yuan, Kian-Lee Tan, and Gang Chen. 2020. Continuous trajectory similarity search for online outlier detection. IEEE Transactions on Knowledge and Data Engineering (2020).

[260]

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

[261]

Desheng Zhang, Jun Huang, Ye Li, Fan Zhang, Chengzhong Xu, and Tian He. 2014. Exploring human mobility with multi-source data at extremely large metropolitan scales. In MobiCom. 201–212.

Digital Library

[262]

Desheng Zhang, Juanjuan Zhao, Fan Zhang, and Tian He. 2015. coMobile: Real-time human mobility modeling at urban scale using multi-view learning. In SIGSPATIAL. 1–10.

Digital Library

[263]

Guolong Zhang, Ping Wang, Haibing Chen, and Lan Zhang. 2019. Wireless indoor localization using convolutional neural network and Gaussian process regression. Sensors 19, 11 (2019), 2508.

[264]

Lu Zhang, Zhu Sun, Jie Zhang, Horst Kloeden, and Felix Klanner. 2020. Modeling hierarchical category transition for next POI recommendation with uncertain check-ins. Information Sciences 515 (2020), 169–190.

Digital Library

[265]

Meihui Zhang, Su Chen, Christian S. Jensen, Beng Chin Ooi, and Zhenjie Zhang. 2009. Effectively indexing uncertain moving objects for predictive queries. Proceedings of the VLDB Endowment 2, 1 (2009), 1198–1209.

Digital Library

[266]

Wenjie Zhang, Xuemin Lin, Ying Zhang, Muhammad Aamir Cheema, and Qing Zhang. 2012. Stochastic skylines. ACM Transactions on Database Systems 37, 2 (2012), 1–34.

Digital Library

[267]

Xiaopu Zhang, Jun Lin, Zubin Chen, Feng Sun, Xi Zhu, and Gengfa Fang. 2018. An efficient neural-network-based microseismic monitoring platform for hydraulic fracture on an edge computing architecture. Sensors 18, 6 (2018), 1828.

[268]

Xichen Zhang, Suprio Ray, Farzaneh Shoeleh, and Rongxing Lu. 2021. Efficient contact similarity query over uncertain trajectories. In EDBT. 403–408.

[269]

Yatao Zhang, Qingquan Li, Wei Tu, Ke Mai, Yao Yao, and Yiyong Chen. 2019. Functional urban land use recognition integrating multi-source geospatial data and cross-correlations. Computers, Environment and Urban Systems 78 (2019), 101374.

[270]

Ying Zhang, Xuemin Lin, Yufei Tao, Wenjie Zhang, and Haixun Wang. 2011. Efficient computation of range aggregates against uncertain location-based queries. IEEE Transactions on Knowledge and Data Engineering 24, 7 (2011), 1244–1258.

Digital Library

[271]

Yueyue Zhang, Song Xing, Yaping Zhu, Feng Yan, and Lianfeng Shen. 2017. RSS-based localization in WSNs using Gaussian mixture model via semidefinite relaxation. IEEE Communications Letters 21, 6 (2017), 1329–1332.

[272]

Guoshuai Zhao, Tianlei Liu, Xueming Qian, Tao Hou, Huan Wang, Xingsong Hou, and Zhetao Li. 2017. Location recommendation for enterprises by multi-source urban big data analysis. IEEE Transactions on Services Computing (2017).

[273]

Pengpeng Zhao, Anjing Luo, Yanchi Liu, Fuzhen Zhuang, Jiajie Xu, Zhixu Li, Victor S. Sheng, and Xiaofang Zhou. 2020. Where to go next: A spatio-temporal gated network for next POI recommendation. IEEE Transactions on Knowledge and Data Engineering (2020).

[274]

Wenfeng Zhao, Biao Sun, Tong Wu, and Zhi Yang. 2018. On-chip neural data compression based on compressed sensing with sparse sensing matrices. IEEE Transactions on Biomedical Circuits and Systems 12, 1 (2018), 242–254.

[275]

Yan Zhao, Shuo Shang, Yu Wang, Bolong Zheng, Quoc Viet Hung Nguyen, and Kai Zheng. 2018. REST: A reference-based framework for spatio-temporal trajectory compression. In KDD. 2797–2806.

Digital Library

[276]

Zhou Zhao, Da Yan, and Wilfred Ng. 2012. Mining probabilistically frequent sequential patterns in uncertain databases. In EDBT. 74–85.

Digital Library

[277]

Guanjie Zheng, Susan L. Brantley, Thomas Lauvaux, and Zhenhui Li. 2017. Contextual spatial outlier detection with metric learning. In KDD. 2161–2170.

Digital Library

[278]

Kai Zheng, Shuo Shang, Nicholas Jing Yuan, and Yi Yang. 2013. Towards efficient search for activity trajectories. In ICDE. 230–241.

Digital Library

[279]

Kai Zheng and Han Su. 2015. Go beyond raw trajectory data: Quality and semantics. IEEE Data Engineering Bulletin 38, 2 (2015), 27–34.

[280]

Kai Zheng, Goce Trajcevski, Xiaofang Zhou, and Peter Scheuermann. 2011. Probabilistic range queries for uncertain trajectories on road networks. In EDBT. 283–294.

Digital Library

[281]

Kai Zheng, Yu Zheng, Xing Xie, and Xiaofang Zhou. 2012. Reducing uncertainty of low-sampling-rate trajectories. In ICDE. 1144–1155.

Digital Library

[282]

Yu Zheng. 2015. Trajectory data mining: An overview. ACM Transactions on Intelligent Systems and Technology 6, 3 (2015), 1–41.

Digital Library

[283]

Xiaolin Zhu, Fangyi Cai, Jiaqi Tian, and Trecia Kay-Ann Williams. 2018. Spatiotemporal fusion of multisource remote sensing data: Literature survey, taxonomy, principles, applications, and future directions. Remote Sensing 10, 4 (2018), 527.

[284]

Andreas Züfle. 2020. Uncertain spatial data management: An overview. arXiv preprint arXiv:2009.01121 (2020).

[285]

Andreas Züfle, Goce Trajcevski, Dieter Pfoser, Matthias Renz, Matthew T. Rice, Timothy Leslie, Paul Delamater, and Tobias Emrich. 2017. Handling uncertainty in geo-spatial data. In ICDE. 1467–1470.

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Index Terms

Spatial Data Quality in the Internet of Things: Management, Exploitation, and Prospects
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Geographic information systems
      2. Sensor networks

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 55, Issue 3

March 2023

772 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3514180

Editor:
Albert Zomaya
University of Sydney, Australia

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Publication History

Published: 03 February 2022

Accepted: 01 November 2021

Revised: 01 September 2021

Received: 01 June 2021

Published in CSUR Volume 55, Issue 3

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