Scalable and Energy-Efficient Multi-Building and Multi-Floor Indoor Localisation/Navigation based on Deep Neural Networks with a Multivariate Database
Table of Contents
Supervisors
Participants
- Mr Sihao Li (E-mail: Sihao.Li_at_liverpool.ac.uk; PhD Candidate; School of Advanced Technology, XJTLU)
Grants
- Xi'an Jiaotong-Liverpool University Research Development Fund with Three-Year PhD scholarship (under grant PRGS1912001).
Duration
- Jun./2020–May/2023 (3 years)
Related Projects
- KSF-E-25: Feasibility Study of XJTLU Campus-Wide Indoor Localisation System based on Deep Neural Networks
- XJTLU SURF-201830: Trajectory Estimation of Mobile Users/Devices based on Wi-Fi Fingerprinting and Deep Neural Networks
- XJTLU SURF-201739: Indoor Localisation Based on Wi-Fi Fingerprinting with Fuzzy Sets
- XJTLU RISGC-2017-4: Feasibility Assessment and Roadmap for XJTLU Campus Information and Visitor Service System as A Test Bed for Large-Scale Location-Aware Services in SIP
- RDF-16-02-39: Energy-Efficient Time Synchronisation and Data Bundling Schemes for Wireless Sensor Networks
References
- Kyeong Soo Kim, Sanghyuk Lee, and Kaizhu Huang, "A scalable deep neural network architecture for multi-building and multi-floor indoor localization based on Wi-Fi fingerprinting," Big Data Analytics, vol. 3, no. 4, pp. 1-17, Apr. 19, 2018.
- Kyeong Soo Kim et al., "Large-scale location-aware services in access: Hierarchical building/floor classification and location estimation using Wi-Fi fingerprinting based on deep neural networks," (Extended version of the FOAN 2017 paper), Fiber and Integrated Optics, vol. 37, no. 5, pp. 277-289, Apr. 27, 2018.
- Kyeong Soo Kim, "Hybrid building/floor classification and location coordinates regression using a single-input and multi-output deep neural network for large-scale indoor localisation based on Wi-Fi fingerprinting," Proc. 2018 CANDAR, Takayama, Japan, Nov. 27-30, 2018.
- Zhenghang Zhong et al., "XJTLUIndoorLoc: A new fingerprinting database for indoor localisation and trajectory estimation based on Wi-Fi RSS and geomagnetic field," Proc. 2018 CANDAR, Takayama, Japan, Nov. 27-30, 2018.
- Kyeong Soo Kim et al., "Large-scale location-aware services in access: Hierarchical building/floor classification and location estimation using Wi-Fi fingerprinting based on deep neural networks," Proc. FOAN 2017 Workshop, Munich, Germany, Nov. 7, 2017.