Abstract
The proliferation of mobile computing has prompted navigation to be one of the most attractive and promising applications. Conventional designs of navigation systems mainly focus on either indoor or outdoor navigation. However, people have a strong need for navigation from a large open indoor environment to an outdoor destination in real life. This article presents IONavi, a joint navigation solution, which can enable passengers to easily deploy indoor-outdoor navigation service for subway transportation systems in a crowdsourcing way. Any self-motivated passenger records and shares individual walking traces from a location inside a subway station to an uncertain outdoor destination within a given range, such as one kilometer. IONavi further extracts navigation traces from shared individual traces, each of which is not necessary to be accurate. A subsequent following user achieves indoor-outdoor navigation services by tracking a recommended navigation trace. Extensive experiments are conducted on a subway transportation system. The experimental results indicate that IONavi exhibits outstanding navigation performance from an uncertain location inside a subway station to an outdoor destination. Although IONavi is to enable indoor-outdoor navigation for subway transportation systems, the basic idea can naturally be extended to joint navigation from other open indoor environments to outdoor environments.
- Moustafa Alzantot and Moustafa Youssef. 2012. Crowdinside: Automatic construction of indoor floorplans. In Proc. of SIGSPATIAL. Google ScholarDigital Library
- Paramvir Bahl and Venkata N. Padmanabhan. 2000. RADAR: An in-building RF-based user location and tracking system. In Proc. of IEEE Infocom.Google Scholar
- Si Chen, Muyuan Li, Kui Ren, and Chunming Qiao. 2015. CrowdMap: Accurate reconstruction of indoor floor plans from crowdsourced sensor-rich videos. In Proc. of IEEE ICDCS.Google Scholar
- Tao Chen, Deke Guo, Yuan He, Honghui Chen, Xue Liu, and Xueshan Luo. 2013. A bloom filters based dissemination protocol in wireless sensor networks. Ad Hoc Networks 11, 4 (2013), 1359--1371. Google ScholarDigital Library
- Tao Chen, Zheng Yang, Yunhao Liu, Deke Guo, and Xueshan Luo. 2011. Localization in non-localizable sensor and ad-hoc networks: A localizability-aided approach. In Proc. of IEEE Infocom. Google ScholarCross Ref
- Jiang Dong, Yu Xiao, Marius Noreikis, Zhonghong Ou, and Antti Yla-Jaaski. 2015. iMoon: Using smartphones for image-based indoor navigation. In Proc. of ACM SenSys. Google ScholarDigital Library
- Dan Feldman, Cynthia R. Sung, Andrew Sugaya, and Daniela Rus. 2015. iDiary: From GPS signals to a text-searchable diary. ACM Transactions on Sensor Networks. 11, 4 (2015), 60. Google ScholarDigital Library
- Nivan Ferreira, James T. Klosowski, Carlos Eduardo Scheidegger, and Cláudio T. Silva. 2013. Vector field k-means: Clustering trajectories by fitting multiple vector fields. Eurographics Conference on Visualization. 32, 3 (2013), 201--210.Google Scholar
- Dieter Fox, Jeffrey Hightower, Lin Liao, Dirk Schulz, and Gaetano Borriello. 2003. Bayesian filtering for location estimation. IEEE Pervasive Computing. 2, 3 (2003), 24--33. Google ScholarDigital Library
- Ruipeng Gao, Yang Tian, Fan Ye, Luo Guojie, Kaigui Bian, Yizhou Wang, Tao Wang, and Xiaoming Li. 2014a. Sextant: Towards ubiquitous indoor localization service by photo-taking of the environment. IEEE Transactions on Mobile Computing. 13, 9 (2014), 1--14.Google Scholar
- Ruipeng Gao, Mingmin Zhao, Tao Ye, Fan Ye, Yizhou Wang, Kaigui Bian, Tao Wang, and Xiaoming Li. 2014b. Jigsaw: Indoor floor plan reconstruction via mobile crowdsensing. In Proc. of ACM MobiCom. Google ScholarDigital Library
- Gerald Glanzer and Ulrich Walder. 2010. Self-contained indoor pedestrian navigation by means of human motion analysis and magnetic field mapping. In Proc. of IEEE WPNC. Google ScholarCross Ref
- Robert Harle. 2013. A survey of indoor inertial positioning systems for pedestrians. IEEE Communications Surveys. 15, 3 (2013), 1281--1293. Google ScholarCross Ref
- Yiqing Hu, Yan Xiong, Wenchao Huang, Xiangyang Li, Yanan Zhang, Xufei Mao, and Caimei Wang. 2015. Lightitude: Indoor positioning using ubiquitous visible lights and COTS devices. In Proc. of IEEE ICDCS. Google ScholarCross Ref
- Lee Inje, Giwan Yoon, and Dongsoo Han. 2011. Nerimi: WiFi-based subway navigation system. In Intelligent Radio for Future Personal Terminals.Google Scholar
- Yifei Jiang, Xiang Yun, Xin Pan, Kun Li, Qin Lv, Robert P. Dick, Li Shang, and Michael Hannigan. 2013. Hallway based automatic indoor floorplan construction using room fingerprints. In Proc. of ACM UbiComp. Google ScholarDigital Library
- Daniel Keysers, Thomas Deselaers, and Hermann Ney. 2004. Pixel-to-pixel matching for image recognition using Hungarian graph matching. DAGM-Symposium (2004), 154--162.Google Scholar
- Ye-Sheng Kuo, Pat Pannuto, Ko-Jen Hsiao, and Prabal Dutta. 2014. Luxapose: Indoor positioning with mobile phones and visible light. In Proc. of ACM MobiCom. Google ScholarDigital Library
- Jae-Gil Lee, Jiawei Han, Xiaolei Li, and Hector Gonzalez. 2008. TraClass: Trajectory classification using hierarchical region-based and trajectory-based clustering. In Proc. of ACM PVLDB. Google ScholarDigital Library
- Jae-Gil Lee, Jiawei Han, and Kyu-Young Whang. 2007. Trajectory clustering: A partition-and-group framework. In Proc. of ACM SIGMOD. Google ScholarDigital Library
- Fan Li, Chunshui Zhao, Guanzhong Ding, Jian Gong, Chenxing Liu, and Feng Zhao. 2012. A reliable and accurate indoor localization method using phone inertial sensors. In Proc. of ACM UbiComp. Google ScholarDigital Library
- Haochao Li, Kaishun Wu, Qian Zhang, and Lionel M. Ni. 2014c. CUTS: Improving channel utilization in both time and spatial domain in WLANs. IEEE Transactions on Parallel and Distributed Systems 25, 6 (2014), 1413--1423. Google ScholarDigital Library
- Liqun Li, Pan Hu, Chunyi Peng, Guobin Shen, and Feng Zhao. 2014a. Epsilon: A visible light based positioning system. In Proc. of USENIX NSDI. Seattle, WA.Google ScholarDigital Library
- Liqun Li, Guobin Shen, Chunshui Zhao, Thomas Moscibroda, Jyh-Han Lin, and Feng Zhao. 2014b. Experiencing and handling the diversity in data density and environmental locality in an indoor positioning service. In Proc. of ACM MobiCom. Google ScholarDigital Library
- Mo Li, Pengfei Zhou, Yuanqing Zheng, Zhenjiang Li, and Guobin Shen. 2015. IODetector: A generic service for indoor/outdoor detection. ACM Transactions on Sensor Networks. 11, 21 (2015), 28.Google ScholarDigital Library
- Hongbo Liu, Yu Gan, Jie Yang, Simon Sidhom, Yan Wang, Yingying Chen, and Fan Ye. 2012. Push the limit of Wi-Fi based localization for smartphones. In Proc. of ACM MobiCom.Google Scholar
- Tie Luo, Salil S. Kanhere, Hwee-Pink Tan, Fan Wu, and Hongyi Wu. 2015. Crowdsourcing with tullock contests: A new perspective. In Proc. of IEEE INFOCOM. Google ScholarCross Ref
- Alessandro Mulloni, Daniel Wagner, István Barakonyi, and Dieter Schmalstieg. 2009. Indoor positioning and navigation with camera phones. IEEE Pervasive Computing. 8, 2 (2009), 22--31. Google ScholarDigital Library
- Christos H. Papadimitriou and Kenneth Steiglitz. 1998. Combinatorial optimization: Algorithms and complexity. Dover Publications.Google Scholar
- Damian Philipp, Patrick Baier, Christoph Dibak, Frank Dürr, Kurt Rothermel, Susanne Becker, Michael Peter, and Dieter Fritsch. 2014. Mapgenie: Grammar-enhanced indoor map construction from crowd-sourced data. In Proc. of IEEE PerCom. Google ScholarCross Ref
- Jothi V. Prakash and Dr LM Nithya. 2014. A survey on semi-supervised learning techniques. In arXiv preprint arXiv:1402.4645.Google Scholar
- Valentin Radu, Panagiota Katsikouli, Rik Sarkar, and Mahesh K. Marina. 2014. A semi-supervised learning approach for robust indoor-outdoor detection with smartphones. In Proc. of ACM Sensys. Google ScholarDigital Library
- Anshul Rai, Krishna Kant Chintalapudi, Venkata N. Padmanabhan, and Rijurekha Sen. 2012. Zee: Zero-effort crowdsourcing for indoor localization. In Proc. of ACM MobiCom. Google ScholarDigital Library
- Alex Rodriguez and Alessandro Laio. 2014. Clustering by fast search and find of density peaks. Science 344, 6191 (2014), 1492--1496. Google ScholarCross Ref
- Sarta Sahni and Teofilo Gonzalez. 1976. P-complete approximation problems. J. ACM. 23, 3 (1976), 555--565. Google ScholarDigital Library
- Muhammad N. Sakib, Junaed Bin Halim, and Chin-Tser Huang. 2014. Determining location and movement pattern using anonymized WiFi access point BSSID. In Proc. of IEEE SecTech. Google ScholarDigital Library
- Guobin Shen, Zhuo Chen, Peichao Zhang, Thomas Moscibroda, and Yongguang Zhang. 2013. Walkie-Markie: Indoor pathway mapping made easy. In Proc. of USENIX NSDI.Google Scholar
- Yuanchao Shu, Kang G. Shin, Tian He, and Jiming Chen. 2015. Last-Mile navigation using smartphones. In Proc. of ACM MobiCom. Google ScholarDigital Library
- S. Skiena. 1990. Dijkstra’s algorithm. In Implementing Discrete Mathematics: Combinatorics and Graph Theory with Mathematica. Addison-Wesley, Reading, MA, 225--227.Google ScholarDigital Library
- Chun-Jung Sun, Hong-Yi Kuo, and Chin E. Lin. 2010. A sensor based indoor mobile localization and navigation using unscented kalman filter. In Proc. of IEEE LPLANS. I Google ScholarCross Ref
- Jorma Tarhio and Esko Ukkonen. 1993. Approximate Boyer-Moore string matching. Society for Industrial and Applied Mathematics. 22, 2 (1993), 243--260.Google Scholar
- Xiaoqiang Teng, Deke Guo, Xiaolei Zhou, and Zhong Liu. 2015. Poster: An indoor-outdoor navigation service for subway transportation systems. In Proc. of ACM SenSys. Google ScholarDigital Library
- Guanhua Wang, Shanfeng Zhang, Kaishun Wu, Qian Zhang, and Lionel M. Ni. 2016. Tim: Fine-grained rate adaptation in WLANs. IEEE Transactions on Mobile Computing 15, 3 (2016), 748--761. Google ScholarDigital Library
- He Wang, Souvik Sen, Ahmed Elgohary, Moustafa Farid, Moustafa Youssef, and Romit Roy Choudhury. 2012. No need to war-drive: Unsupervised indoor localization. In Proc. of ACM MobiSys. Google ScholarDigital Library
- Shenlong Wang, Sanja Fidler, and Raquel Urtasun. 2015. Lost shopping! Monocular localization in large indoor spaces. In Proc. of IEEE ICCV. Google ScholarDigital Library
- Kaishun Wu, Haochao Li, Lu Wang, Youwen Yi, Yunhuai Liu, Dihu Chen, Xiaonan Luo, Qian Zhang, and Lionel M. Ni. 2013. hJam: Attachment transmission in WLANs. IEEE Transactions on Mobile Computing 12, 12 (2013), 2334--2345. Google ScholarDigital Library
- Bo Xie, Guang Tan, and Tian He. 2015. Spinlight: A high accuracy and robust light positioning system for indoor applications. In Proc. of ACM SenSys. Seoul, Korea. Google ScholarDigital Library
- Dejun Yang, Guoliang Xue, Xi Fang, and Jian Tang. 2012b. Crowdsourcing to smartphones: Incentive mechanism design for mobile phone sensing. In Proc. of ACM MobiCom. Google ScholarDigital Library
- Zheng Yang, Chenshu Wu, and Yunhao Liu. 2012a. Locating in fingerprint space: Wireless indoor localization with little human intervention. In Proc. of ACM MobiCom. Google ScholarDigital Library
- Xiang Zhang, Guoliang Xue, Ruozhou Yu, Dejun Yang, and Jian Tang. 2015. Truthful incentive mechanisms for crowdsourcing. In Proc. of IEEE INFOCOM. Google ScholarCross Ref
- Yuanqing Zheng, Guobin Shen, Liqun Li, Chunshui Zhao, Mo Li, and Feng Zhao. 2014. Travi-Navi: Self-deployable indoor navigation system. In Proc. of ACM MobiCom. Google ScholarDigital Library
Index Terms
- IONavi: An Indoor-Outdoor Navigation Service via Mobile Crowdsensing
Recommendations
Poster: An Indoor-Outdoor Navigation Service for Subway Transportation Systems
SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor SystemsThe proliferation of mobile computing has prompted navigation to be one of the most attractive and promising applications. Conventional designs of navigation systems mainly focus either indoor or outdoor navigation. However, people have a strong need ...
A Polygonal Method for Ranging-Based Localization in an Indoor Wireless Sensor Network
In this paper, we propose an indoor localization method in a wireless sensor network based on IEEE 802.15.4 specification. The proposed method follows a ranging-based approach using not only the measurements of received signal strength (RSS) but also ...
SALMA: UWB-based Single-Anchor Localization System using Multipath Assistance
SenSys '18: Proceedings of the 16th ACM Conference on Embedded Networked Sensor SystemsSetting up indoor localization systems is often excessively time-consuming and labor-intensive, because of the high amount of anchors to be carefully deployed or the burdensome collection of fingerprints. In this paper, we present SALMA, a novel low-...
Comments