An intelligent multi-floor indoor positioning system for cloud-based environment

[1]  Yong K. Cho,et al.  Case Study of BIM and Cloud–Enabled Real-Time RFID Indoor Localization for Construction Management Applications , 2016 .

[2]  Yunhao Liu,et al.  Mobility Increases Localizability , 2015, ACM Comput. Surv..

[3]  Rosdiadee Nordin,et al.  Accurate Wireless Sensor Localization Technique Based on Hybrid PSO-ANN Algorithm for Indoor and Outdoor Track Cycling , 2016, IEEE Sensors Journal.

[4]  Shahrokh Valaee,et al.  Received-Signal-Strength-Based Indoor Positioning Using Compressive Sensing , 2012, IEEE Transactions on Mobile Computing.

[5]  Gianfranco Manes,et al.  A Distributed Positioning System Based on a Predictive Fingerprinting Method Enabling Sub-Metric Precision in IEEE 802.11 Networks , 2015, IEEE Transactions on Microwave Theory and Techniques.

[6]  Hongming Zhou,et al.  Optimization method based extreme learning machine for classification , 2010, Neurocomputing.

[7]  Thorsten Joachims,et al.  Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.

[8]  Hubert Roth,et al.  WSNs and on-Board Visual Fuzzy Servoing on Blimp Robot for Tracking Purposes , 2016 .

[9]  Erol Gelenbe,et al.  A Cooperative Emergency Navigation Framework Using Mobile Cloud Computing , 2014, ISCIS.

[10]  Massimiliano Pontil,et al.  Support Vector Machines for 3D Object Recognition , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Antoni Morell,et al.  Indoor Pedestrian Tracking by On-Body Multiple Receivers , 2016, IEEE Sensors Journal.

[12]  Shiwen Mao,et al.  CSI-Based Fingerprinting for Indoor Localization: A Deep Learning Approach , 2016, IEEE Transactions on Vehicular Technology.

[13]  Yuwei Chen,et al.  Using LS-SVM Based Motion Recognition for Smartphone Indoor Wireless Positioning , 2012, Sensors.

[14]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[15]  Hao Jiang,et al.  A Fast and Precise Indoor Localization Algorithm Based on an Online Sequential Extreme Learning Machine † , 2015, Sensors.

[16]  Lin Ma,et al.  A Spatial Division Clustering Method and Low Dimensional Feature Extraction Technique Based Indoor Positioning System , 2014, Sensors.

[17]  Hongming Zhou,et al.  Extreme Learning Machine for Regression and Multiclass Classification , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[18]  Luca De Nardis,et al.  A Mixed Approach to Similarity Metric Selection in Affinity Propagation-Based WiFi Fingerprinting Indoor Positioning , 2015, Sensors.

[19]  Hyun Myung,et al.  A Probabilistic Feature Map-Based Localization System Using a Monocular Camera , 2015, Sensors.

[20]  Maode Ma,et al.  Markovian model based indoor location tracking for Internet of Things (IoT) applications , 2017, Cluster Computing.

[21]  Sun I. Kim,et al.  Nonlinear Support Vector Machine Visualization for Risk Factor Analysis Using Nomograms and Localized Radial Basis Function Kernels , 2008, IEEE Transactions on Information Technology in Biomedicine.

[22]  Shang-Yuan Chen,et al.  A Review of Smart Living Space Development in a Cloud Computing Network Environment , 2009 .

[23]  Guang-Bin Huang,et al.  Convex incremental extreme learning machine , 2007, Neurocomputing.

[24]  Joseph Kee-Yin Ng,et al.  Location Estimation via Support Vector Regression , 2007, IEEE Transactions on Mobile Computing.

[25]  Yiqiang Chen,et al.  SELM: Semi-supervised ELM with application in sparse calibrated location estimation , 2011, Neurocomputing.

[26]  Kai Zhao,et al.  An Improved Algorithm to Generate a Wi-Fi Fingerprint Database for Indoor Positioning , 2013, Sensors.

[27]  Junhai Luo,et al.  Indoor Positioning Systems Based on Visible Light Communication: State of the Art , 2017, IEEE Communications Surveys & Tutorials.

[28]  Lei Chen,et al.  Enhanced random search based incremental extreme learning machine , 2008, Neurocomputing.

[29]  Shahrokh Valaee,et al.  Indoor Tracking and Navigation Using Received Signal Strength and Compressive Sensing on a Mobile Device , 2013, IEEE Transactions on Mobile Computing.