Enhancing the Map Usage for Indoor Location-Aware Systems

Wang, Hui; Lenz, H.; Szabo, Andrei; Bamberger, Joachim; Hanebeck, Uwe D.

doi:10.1007/978-3-540-73107-8_17

Cited by 12 publications

(4 citation statements)

References 19 publications

(22 reference statements)

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“…We found that the original heat map shows a corner diversion due to the dominant path [40], whereas in our RSSI map estimation, only the direct path was used. To incorporate such effects and to retain a low calculation complexity, we add two triangular paths to avoid the direct path error to a certain extent, as shown in Figure 3d-(right).…”

Section: Proposed Approachmentioning

confidence: 99%

“…To improve the RSSI map generation accuracy using the procedure described above, we compare our map with a real RSSI heat map, calculated manually by site survey, while recording the RSSI information at each crossing point, 1 m in the horizontal and vertical direction of the grid, as depicted in Figure 3 d-(left). We found that the original heat map shows a corner diversion due to the dominant path [ 40 ], whereas in our RSSI map estimation, only the direct path was used. To incorporate such effects and to retain a low calculation complexity, we add two triangular paths to avoid the direct path error to a certain extent, as shown in Figure 3 d-(right).…”

Section: Proposed Approachmentioning

confidence: 99%

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LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning

Ali

Hur

Park

2017

Sensors

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Recent advancements in indoor positioning systems are based on infrastructure-free solutions, aimed at improving the location accuracy in complex indoor environments without the use of specialized resources. A popular infrastructure-free solution for indoor positioning is a calibration-based positioning, commonly known as fingerprinting. Fingerprinting solutions require extensive and error-free surveys of environments to build radio-map databases, which play a key role in position estimation. Fingerprinting also requires random updates of the database, when there are significant changes in the environment or a decrease in the accuracy. The calibration of the fingerprinting database is a time-consuming and laborious effort that prevents the extensive adoption of this technique. In this paper, we present a systematic LOCALIzation approach, “LOCALI”, for indoor positioning, which does not require a calibration database and extensive updates. The LOCALI exploits the floor plan/wall map of the environment to estimate the target position by generating radio maps by integrating path-losses over certain trajectories in complex indoor environments, where triangulation using time information or the received signal strength level is highly erroneous due to the fading effects caused by multi-path propagation or absorption by environmental elements or varying antenna alignment. Experimental results demonstrate that by using the map information and environmental parameters, a significant level of accuracy in indoor positioning can be achieved. Moreover, this process requires considerably lesser effort compared to the calibration-based techniques.

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Section: Proposed Approachmentioning

confidence: 99%

Section: Proposed Approachmentioning

confidence: 99%

LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning

Ali

Hur

Park

2017

Sensors

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“…In [11], [12] a particle filter is used: Each particle represents a possible position of the user. Topology information is used to discard particles that cross walls or other obstacles.…”

Section: Related Workmentioning

confidence: 99%

Towards ubiquitous indoor location based services and indoor navigation

Greßmann

Klimek

Turau

2010

2010 7th Workshop on Positioning, Navigation and Communication

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Abstract-Outdoor navigation services have become ubiquitously available due to small handheld devices such as GPS enabled mobile phones or dedicated mobile navigation systems. Two main drivers were necessary in order to provide widespread location based services: Acquiring positioning information with a certain degree of precision and widespread (mobile) access to computer networks to use the position information with a large information basis such as the Internet. Envisioned is a future, where indoor navigation and location based services are used as naturally as outdoor location based services are now. To achieve this long term vision where users seamlessly navigate for example from work desk to departure gate at the airport and use location based services on the way, various challenges have to be solved.In this paper, these challenges and open issues are discussed. The paper proposes an architecture which abstracts from different mobile devices and localization technologies. Additionally, it sketches the use of indoor topology information to increase the accuracy of indoor localization. These two presented concepts form a basis for a transition period until standards for ubiquitous indoor location based services have emerged.

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“…In addition to the sensor measurements, another key input for our system is the floormap of the indoor space of interest. Floormap information has been used to refine walking trajectory estimates by eliminating wall-crossings or unfeasible locations [ 12 , 13 , 14 ]. There has also been efforts to use the floormap to reduce the complexity of the tracking task by properly quantizing the indoor space [ 15 , 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

MapSentinel: Can the Knowledge of Space Use Improve Indoor Tracking Further?

Jia

Jin

Zou

et al. 2016

Sensors

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Estimating an occupant’s location is arguably the most fundamental sensing task in smart buildings. The applications for fine-grained, responsive building operations require the location sensing systems to provide location estimates in real time, also known as indoor tracking. Existing indoor tracking systems require occupants to carry specialized devices or install programs on their smartphone to collect inertial sensing data. In this paper, we propose MapSentinel, which performs non-intrusive location sensing based on WiFi access points and ultrasonic sensors. MapSentinel combines the noisy sensor readings with the floormap information to estimate locations. One key observation supporting our work is that occupants exhibit distinctive motion characteristics at different locations on the floormap, e.g., constrained motion along the corridor or in the cubicle zones, and free movement in the open space. While extensive research has been performed on using a floormap as a tool to obtain correct walking trajectories without wall-crossings, there have been few attempts to incorporate the knowledge of space use available from the floormap into the location estimation. This paper argues that the knowledge of space use as an additional information source presents new opportunities for indoor tracking. The fusion of heterogeneous information is theoretically formulated within the Factor Graph framework, and the Context-Augmented Particle Filtering algorithm is developed to efficiently solve real-time walking trajectories. Our evaluation in a large office space shows that the MapSentinel can achieve accuracy improvement of 31.3% compared with the purely WiFi-based tracking system.

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Enhancing the Map Usage for Indoor Location-Aware Systems

Cited by 12 publications

References 19 publications

LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning

LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning

Towards ubiquitous indoor location based services and indoor navigation

MapSentinel: Can the Knowledge of Space Use Improve Indoor Tracking Further?

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