i Kartografii, Politechnika Warszawska. Gotlib, D. & Marciniak, J. (2012). Cartographical aspects in the design of indoornavigation systems. Annual of Navigation no 19/2012, Polish Navigation Forum Isikdag, U., Zlatanova, S. & Underwood, J. (2013). A BIM-Oriented Model for supporting indoornavigation requirements, Computers, Environment and Urban Systems, Volume 4, September 2013, pp. 112-123. Lee, J. & Zlatanova, S. (2008). A 3D data model and topological analyses for emergency response in urban areas. In Zlatanova, Li (Eds.), Geospatial information
References  Giorgetti G., Farley R., Chikkappa K., Ellis J., Kaleas T., Cortina: Collaborative Indoor Positioning Using Low-Power Sensor Networks, International Conference on Indoor Positioning and IndoorNavigation, Guimarăes, Portugal, 2011.  Gotlib D., Methodology of cartographic presentation in mobile positioning and navigation systems (in Polish), Prace Naukowe Politechniki Warszawskiej, Geodezja, 2011, No. 48.  Gotlib D., Development of cartographic presentation methods in mobile systems, including indoor positioning systems (in Polish), the report
: 10.1080/17489720802345386 Fellner I., Huang H., Gartner G., 2017, “ Turn left after the WC, and use the lift to go to the 2nd floor ” − generation of landmark-based route instructions for indoornavigation . “ISPRS International. Journal Geo-Information” Vol. 6, 183; DOI:10.3390/ijgi6060183 Gartner G., 2000, TeleKartographie. “GeoBIT” Vol. 4, pp. 21−24. Gartner G., 2009, Ubiquitous cartography . “American Congress of Surveying and Mapping (ACSM) Bulletin”, pp. 22−24. Gartner G., Bennett D.A., Morita T., 2007, Towards ubiquitous cartography . “Cartography and
Tracking using Smartphone Sensors, Step Detection and Map Matching Algorithm. Geodetski list, Vol. 70 (93), No. 1, pp. 1-24. Jain, M. - Rahul, R. C. P. - Tolety, S. B. (2013) A study on indoornavigation techniques using smartphones. Advances in Computing, Communications and Informatics (ICACCI): IEEE Conference Publications, IEEE, Jaipur, India, pp. 1113-1118 DOI: 10.1109/ICACCI.2013.6637333 Jeon, J. - Kong, Y. - Kangbin, Y. - Nam, Y. - Yim, K. (2015) An Indoor Positioning System using Bluetooth RSSI with an Accelerometer and a Barometer on a Smartphone. 2015 10th
Indoor Positioning and IndoorNavigation, 2011, pp. 1-7.  Retscher G., Fu Q., Continuos IndoorNavigation with RFID and INS, Position Location and Navigation Symposium (PLANS), 2010, pp. 102-112.  Song Y., Yu H., A RSS Based Indoor Tracking Algorithm via Particle Filter and Probability Distribution. 4th International Conference on Wireless Communications, Networking and Mobile Computing, 2008, pp. 1-4.
This paper presents a proof of the concept cloud based patient monitoring and self-care platform, powered by measurements provided from various smartphone sensors. The Cloud platform provides the infrastructure and computational capacity for calculation of the navigation and motion tracking system, fall detection monitoring, as well as emergency notifications. The navigation system uses the pedometer and fusion of the accelerometer, gyroscope and magnetometer sensors. It aims to estimate precisely the patient’s movement and location. While both navigation and tracking systems can independently determine the incremental movement and indoor localization of the patients, they are fused in order to provide more accurate estimations. The fall detection monitoring is enabled by processing the raw data collected from the smartphone’s accelerometer and gyroscope. Furthermore, the cloud system provides various statistics for the physical activity of the patients, based on measurements from the pedometer. Consequently, this paper proposes a proof of the concept cloud based platform that is scalable and highly responsive, used for real-time monitoring and tracking a large number of patients. It also provides indoor navigation and other self-care features.
This paper presents ambiguity resolution in the range-based ZigBee positioning system. The system is using the phase shift measurements to determine the distances between user and anchors. In this paper, the ambiguity is defined as the number of full reps of a certain distance added to the measurement result. The way of resolving ambiguities in the positioning system is described and an experiment results are presented. Featured algorithm is successful in finding ambiguities and correct location of the user.
References  S. Albers,H. Bals, Dynamic TCP acknowledgement: Penalizing long delays, SIAM J. Discrete Math. 19, 4 (2005) 938-951. →7  M. Brugger, T. Christ, F. Kemeth, S. Nagy, M. Schaefer, M. M. Pietrzyk, The FMCW technology-based indoor localization system, Proc. Ubiquitous Positioning IndoorNavigation and Location Based Service (UPINLBS), Helsinki, Finnland, 2010, pp. 1-6. →6  M. Brugger, F. Kemeth, Locating rate adaptation by evaluating movement specific parameters, Proc. 2010 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), Anaheim, USA
”, Sensors (Basel), 12, pp. 10536-10549.  Grejner-Brzezinska D. A., Toth C. K., Moafipoor S., Hyoun Kwon J., 2017, “Design and calibration of a neural network-based adaptive knowledge system for multi-sensor personal navigation”, from: http://www.isprs.org/proceedings/XXXVI/5-C55/papers/dorota_brzezinska.pdf .  Nilsson J. O., Skog I., Handel P., 2012, “A note on the limitations of ZUPTs and the implications on sensor error modeling”, 2012 International Conference on Indoor Positioning and IndoorNavigation.  Szymanowski J., Grzelak J., Popowski S., 2003
References  S. Albers, H. Bals, Dynamic TCP acknowledgment: Penalizing long delays, SIAM J. Discrete Math. 19, 4 (2005) 938-951. ⇒165  A. Borodin, R. El-Yaniv, Online Computation and Competitive Analysis, Cambridge University Press, 1998. ⇒164  M. Brugger, T. Christ, F. Kemeth, S. Nagy, M. Schaefer, M. M.Pietrzyk, The FMCW technology-based indoor localization system, in: Ubiquitous Positioning IndoorNavigation and Location Based Services, 2010, pp. 1-6. ⇒164  M. Brugger, F. Kemeth, Locating rate adaptation by evaluating movement specific parameters