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International positioning architecture
Introduction
An indoor positioning system (in English indoor positioning system, abbreviated IPS) is a network of devices used to wirelessly locate objects or people within a building and that can also be used for navigation within the building.[1] Sometimes, products offered under this term do not comply with the international standard ISO/IEC[2] 24730 on real-time location systems") (RTLS).
Instead of using satellites, an IPS relies on nearby anchors (nodes with a known position), which either actively locate tags or provide environmental context to sensor devices.[3] The localized nature of an IPS has led to design fragmentation, with systems making use of various technologies: optical,[4] radio,[5][6][7][8][9] or even acoustic.[10].
In the design of the systems, it must be taken into account that the unambiguous location service requires at least three independent measurements per destination. To smooth out and compensate for stochastic errors, there must be an excess of mathematical determination that allows the error budget to be reduced. Otherwise, the system must include information from other systems to address physical ambiguity and to enable error compensation.
Uses
The main user benefit of indoor positioning is the expansion of indoor mobile computing location recognition. As mobile devices become ubiquitous, contextual awareness for applications has become a priority for developers. Most apps rely on GPS, however, and don't work well indoors. Applications that benefit from indoor location include:
References
[1] ↑ Kevin Curran, Eoghan Furey, Tom Lunney, Jose Santos, Derek Woods and Aiden Mc Caughey (2011) An Evaluation of Indoor Location Determination Technologies. Journal of Location Based Services Vol. 5, No. 2, pp: 61-78, June 2011, ISSN 1748-9725, DOI:10.1080/17489725.2011.562927, Taylor & Francis.: https://es.wikipedia.org//portal.issn.org/resource/ISSN/1748-9725
[2] ↑ ISO/IEC JTC1 (en inglés).
[3] ↑ Eoghan Furey, Kevin Curran and Paul Mc Kevitt (2012) HABITS: A Bayesian Filter Approach to Indoor Tracking and Location. International Journal of Bio-Inspired Computation (IJBIC) Vol. 4, No. 2, pp: 79-88, ISSN 1758-0366, DOI: 10.1504/IJBIC.2012.047178, InderScience.: https://es.wikipedia.org//portal.issn.org/resource/ISSN/1758-0366
[4] ↑ Liu X, Makino H, Mase K. 2010. Improved indoor location estimation using fluorescent light communication system with a nine-channel receiver. IEICE Transactions on Communications E93-B(11):2936-44.
[5] ↑ Chang N, Rashidzadeh R, Ahmadi M. 2010. Robust indoor positioning using differential Wi-Fi access points. IEEE Transactions on Consumer Electronics 56(3):1860-7.
[6] ↑ Chiou Y, Wang C, Yeh S. 2010. An adaptive location estimator using tracking algorithms for indoor WLANs. Wireless Networks 16(7):1987-2012.
[7] ↑ Lim H, Kung L, Hou JC, Luo Haiyun. 2010. Zero-configuration indoor localization over IEEE 802.11 wireless infrastructure. Wireless Networks 16(2):405-20.
[8] ↑ Reza AW, Geok TK. 2009. Investigation of indoor location sensing via RFID reader network utilizing grid covering algorithm. Wireless Personal Communications 49(1):67-80.
[9] ↑ Zhou Y, Law CL, Guan YL, Chin F. 2011. Indoor elliptical localization based on asynchronous UWB range measurement. IEEE Transactions on Instrumentation and Measurement 60(1):248-57.
International positioning architecture
Introduction
An indoor positioning system (in English indoor positioning system, abbreviated IPS) is a network of devices used to wirelessly locate objects or people within a building and that can also be used for navigation within the building.[1] Sometimes, products offered under this term do not comply with the international standard ISO/IEC[2] 24730 on real-time location systems") (RTLS).
Instead of using satellites, an IPS relies on nearby anchors (nodes with a known position), which either actively locate tags or provide environmental context to sensor devices.[3] The localized nature of an IPS has led to design fragmentation, with systems making use of various technologies: optical,[4] radio,[5][6][7][8][9] or even acoustic.[10].
In the design of the systems, it must be taken into account that the unambiguous location service requires at least three independent measurements per destination. To smooth out and compensate for stochastic errors, there must be an excess of mathematical determination that allows the error budget to be reduced. Otherwise, the system must include information from other systems to address physical ambiguity and to enable error compensation.
Uses
The main user benefit of indoor positioning is the expansion of indoor mobile computing location recognition. As mobile devices become ubiquitous, contextual awareness for applications has become a priority for developers. Most apps rely on GPS, however, and don't work well indoors. Applications that benefit from indoor location include:
References
[1] ↑ Kevin Curran, Eoghan Furey, Tom Lunney, Jose Santos, Derek Woods and Aiden Mc Caughey (2011) An Evaluation of Indoor Location Determination Technologies. Journal of Location Based Services Vol. 5, No. 2, pp: 61-78, June 2011, ISSN 1748-9725, DOI:10.1080/17489725.2011.562927, Taylor & Francis.
[10] ↑ Schweinzer H, Kaniak G. 2010. Ultrasonic device localization and its potential for wireless sensor network security. Control Engineering Practice 18(8):852-62.
[3] ↑ Eoghan Furey, Kevin Curran and Paul Mc Kevitt (2012) HABITS: A Bayesian Filter Approach to Indoor Tracking and Location. International Journal of Bio-Inspired Computation (IJBIC) Vol. 4, No. 2, pp: 79-88, ISSN 1758-0366, DOI: 10.1504/IJBIC.2012.047178, InderScience.: https://es.wikipedia.org//portal.issn.org/resource/ISSN/1758-0366
[4] ↑ Liu X, Makino H, Mase K. 2010. Improved indoor location estimation using fluorescent light communication system with a nine-channel receiver. IEICE Transactions on Communications E93-B(11):2936-44.
[5] ↑ Chang N, Rashidzadeh R, Ahmadi M. 2010. Robust indoor positioning using differential Wi-Fi access points. IEEE Transactions on Consumer Electronics 56(3):1860-7.
[6] ↑ Chiou Y, Wang C, Yeh S. 2010. An adaptive location estimator using tracking algorithms for indoor WLANs. Wireless Networks 16(7):1987-2012.
[7] ↑ Lim H, Kung L, Hou JC, Luo Haiyun. 2010. Zero-configuration indoor localization over IEEE 802.11 wireless infrastructure. Wireless Networks 16(2):405-20.
[8] ↑ Reza AW, Geok TK. 2009. Investigation of indoor location sensing via RFID reader network utilizing grid covering algorithm. Wireless Personal Communications 49(1):67-80.
[9] ↑ Zhou Y, Law CL, Guan YL, Chin F. 2011. Indoor elliptical localization based on asynchronous UWB range measurement. IEEE Transactions on Instrumentation and Measurement 60(1):248-57.
[10] ↑ Schweinzer H, Kaniak G. 2010. Ultrasonic device localization and its potential for wireless sensor network security. Control Engineering Practice 18(8):852-62.