The Internet of Things
DOI: 10.1007/978-3-540-78731-0_21
|View full text |Cite
|
Sign up to set email alerts
|

Abstract: Abstract. We consider the problem of real-time sensing and tracking the location of a moving cart in an indoor environment. To this end, we propose to combine position information obtained from an inertial navigation system (INS) and a short-range wireless reference system that can be embedded into a future"network of things". The data produced by the INS lead to accurate short-term position estimates, but due to the drifts inherent to the system, these estimates perform loosely after some time. To solve this … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
8
0
1

Publication Types

Select...
5
3
1

Relationship

0
9

Authors

Journals

citations
Cited by 19 publications
(9 citation statements)
references
References 4 publications
0
8
0
1
Order By: Relevance
“…The Kalman filter can also be used as a tool to combine data of a different nature from different sources. This is used, for example, by Coronel et al [14], Lee et al [15], Chen et al [16], Chen et al [17], Yu et al [18], Liu et al [19] when dealing with a dynamic localization problem, they combine radio data and motion data from the respective mobile device sensors.…”
Section: Motivation For Using Kalman Filtersmentioning
confidence: 99%
See 1 more Smart Citation
“…The Kalman filter can also be used as a tool to combine data of a different nature from different sources. This is used, for example, by Coronel et al [14], Lee et al [15], Chen et al [16], Chen et al [17], Yu et al [18], Liu et al [19] when dealing with a dynamic localization problem, they combine radio data and motion data from the respective mobile device sensors.…”
Section: Motivation For Using Kalman Filtersmentioning
confidence: 99%
“…The described problem could be partially eliminated by using the PDR technique, which would replace the a priori estimation of the position according to the given state equation of the system model, see, for example, [14][15][16][17][18][19].…”
Section: Dynamic Localizationmentioning
confidence: 99%
“…Besides the coupling strategy itself, the fusion of heterogeneous data also requires the use of specific estimation tools and advanced filtering techniques, such as a particle filter in [14], a combination of a particle filter and an extended Kalman filter (EKF) in [15,18], or a backward/forward Kalman filter with a recording/smoothing unit in [31]. But another feature of navigation fusion filters concerns the way the IMU data are exploited.…”
Section: Hybrid Data Fusion Strategiesmentioning
confidence: 99%
“…In order to improve the localization accuracy, hybrid localization systems have been proposed, combining RSS localization with measurements provided by inertial sensors, such as accelerometers and gyroscopes [2], [3], [4], [5]. To this end, these devices are mounted on the object/person to be tracked to implement dead reckoning systems, which provide continuous estimates of the position, speed and orientation of the object.…”
Section: Introductionmentioning
confidence: 99%