Learning indoor movement habits for predictive control

Furey, Eoghan; Curran, Kevin; Kevitt, Paul Mc

doi:10.1504/ijssc.2011.043503

Cited by 12 publications

(3 citation statements)

References 9 publications

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“…This is normally the minimum required for accurate localisation. The highest frequency rate of position updates from the Ekahau RTLS has been found to be 5 s [16,17,18]. These updates are often up to 15 seconds apart.…”

Section: Habits Modellingmentioning

confidence: 99%

HABITS: a Bayesian filter approach to indoor tracking and location

Furey

Curran

McKevitt

2012

IJBIC

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Abstract. Knowledge of the location of people and things has always been a valuable commodity. The explosion of new devices and techniques has brought people and item tracking out of the experimental stage and into the wider world. Using Wi-Fi signals is an attractive and reasonably affordable option to deal with the currently unsolved problem of widespread tracking in an indoor environment. HABITS (History Aware Based Indoor Tracking System) models human movement patterns by applying a discrete Bayesian filter to predict the areas that will, or will not, be visited in the future. We outline here the operation of the HABITS Real-Time Location System (RTLS) and discuss the implementation in relation to indoor Wi-Fi tracking with a large wireless network. Testing of HABITS shows that it gives comparable levels of accuracy to those achieved by doubling the number of access points. These probabilistic predictions may be used as an additional input into building automation systems for intelligent control of heating and lighting. It is twice as accurate as existing systems in dealing with signal black spots and it can predict the final destination of a person within the test environment almost 80% of the time.

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Section: Habits Modellingmentioning

confidence: 99%

HABITS: a Bayesian filter approach to indoor tracking and location

Furey

Curran

McKevitt

2012

IJBIC

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“…How to obtain the handset's approximate position is a challenge. Other techniques such as WiFi positioning (Li et al 2005, Furey, Curran & Mc Kevitt 2008) or mobile network positioning (Drane, Macnaughtan & Scott 1998) may be utilized. Otherwise the base station or access point that the handset is connected to may have coordinates defined that can be used.…”

Section: A-gps Protocolsmentioning

confidence: 99%

Open Source GNSS Reference Server for Assisted-Global Navigation Satellite Systems

Zhang

Dempster

et al. 2010

J. Navigation

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Assisted-Global Navigation Satellite Systems (A-GNSS), or Assisted-Global Positioning Systems (A-GPS) in particular, are now commonly accepted as an effective way to reduce the time-to-first-fix (TTFF) in GNSS-unfriendly environments, e.g. in areas of weak GNSS signals. Today's location-based service (LBS) devices such as GPS-enabled mobile phones and personal digital assistants (PDA) rely on A-GPS; however, such commercial devices are equipped with an integrated A-GPS chip that makes customisation very difficult. The Open Source GNSS Reference Server (OSGRS) provided by the University of New South Wales is an open source Java application that can generate the necessary data for A-GPS clients. The GNSS Reference Interface Protocol (GRIP), based on extensible mark-up language (XML), is employed as the OSGRS interface protocol. This paper describes the current status of OSGRS: a client simulator is available open-source; client software which supports four different types of A-GPS-enabled receivers has been developed and used to test OSGRS. The performance of the OSGRS is analysed based on intensive tests. The challenges for OSGRS and future work are also discussed.

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“…WMNs are based on mesh topology, in which every node (representing a server) is connected through wireless links to one or more nodes, enabling thus the information transmission in more than one path [2]. The path redundancy is a robust feature of mesh topology.…”

Section: Introductionmentioning

confidence: 99%

Analysis of WMN-SA andWMN-GA Simulation Results: A Comparison Performance for Wireless Mesh Networks

Ikeda

Oda

Sakamoto

et al. 2014

2014 17th International Conference on Network-Based Information Systems

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Wireless Mesh Networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In our previous work, we evaluated WMN-SA and WMN-GA systems which are based respectively on Simulated Annealing (SA) and Genetic Algorithms (GAs) to find an optimal location assignment for mesh routers. In this paper, we evaluate the performance of optimal distribution of router nodes for two different algorithms. As evaluation metrics, we used packet delivery ratio, end-to-end delay, beacon received and packet dropped. For simulations, we used QualNet and Hybrid Wireless Mesh Protocol (HWMP). We compare the performance of the optimized network topologies for event site environment of mesh clients by sending multiple constant bit rate flows in the network. The simulation results show that for GA scenario, the average PDR is higher than the results of SA. Comparing the results of WMN-SA and WMN-GA scenario, the number of packets dropped due to retransmission of WMN-GA is smaller than WMN-SA.

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Learning indoor movement habits for predictive control

Cited by 12 publications

References 9 publications

HABITS: a Bayesian filter approach to indoor tracking and location

HABITS: a Bayesian filter approach to indoor tracking and location

Open Source GNSS Reference Server for Assisted-Global Navigation Satellite Systems

Analysis of WMN-SA andWMN-GA Simulation Results: A Comparison Performance for Wireless Mesh Networks

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