Localization of Mobile Sensors and Actuators for Intervention in Low-Visibility Conditions: The ZigBee Fingerprinting Approach

Martí, José V.; Sales, Jorge Henrique; Marı́n, R.; Jiménez-Ruiz, Ernesto

doi:10.1155/2012/951213

Cited by 20 publications

(18 citation statements)

References 22 publications

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“…There is a large number of technologies to develop Indoor Positioning Systems (IPSs): Radio-Frequency Identification (RFID) (Jin et al, 2006;Montaser & Moselhi, 2014;Calderoni et al, 2015), Bluetooth (Feldmann et al, 2003;Li, 2014), Wireless Local Area Network (WLAN or Wi-Fi) (Bahl & Padmanabhan, 2000;Lau & Chung, 2007;del Corte-Valiente et al, 2009;Gansemer et al, 2010a;Segou et al, 2010;Machaj et al, 2011;Marques et al, 2012;Chen et al, 2013;Lan & Shih, 2013;Le et al, 2014), ZigBee (Martí et al, 2012), Ultrasound (Ijaz et al, 2013), Magnetic field variations (Chung et al, 2011;Guo et al, 2014), and even LED light (Kuo et al, 2014), among others. A combination of technologies has also been used (Martí & Marín, 2011;Baniukevic et al, 2013;Li et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Comprehensive analysis of distance and similarity measures for Wi-Fi fingerprinting indoor positioning systems

Torres-Sospedra

Montoliu

Trilles

et al. 2015

Expert Systems with Applications

239

150

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Recent advances in Indoor Positioning Systems led to a business interest in those applications and services where a precise localization is crucial. Wi-Fi fingerprinting based on Machine Learning and Expert Systems are commonly used in the literature. They compare a current fingerprint to a database of fingerprints, and then return the most similar one/ones according to: 1) a distance function, 2) a data representation method for Received Signal Strength values, and 3) a thresholding strategy. However, most of the previous works simply use the Euclidean distance with the raw unprocessed data.There is not any previous work that studies which is the best distance function, which is the best way of representing the data and which is the effect of applying thresholding.In this paper, we present a comprehensive study using 51 distance metrics, 4 alternatives to represent the raw data (2 of them proposed by us), a thresholding based on the RSS values and the public UJIIndoorLoc database. The results shown in this paper demonstrates that researchers and developers should take into account the conclusions arisen in this work in order to improve the accuracy of their systems. The IPSs based on k-NN are improved by just selecting the appropriate configuration (mainly distance function and data representation). In the best case, 13-NN with Sørensen distance and the powed data representation, the error in determining the place (building and floor) Preprint submitted to ElsevierNovember 23, 2015 has been reduced in more than a 50% and the positioning accuracy has been increased in 1.7 meters with respect to the 1-NN with Euclidean distance and raw data commonly used in the literature. Moreover, our experiments also demonstrates that thresholdingshould not be applied in multi-building and multi-floor environments

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Section: Introductionmentioning

confidence: 99%

Comprehensive analysis of distance and similarity measures for Wi-Fi fingerprinting indoor positioning systems

Torres-Sospedra

Montoliu

Trilles

et al. 2015

Expert Systems with Applications

239

150

View full text Add to dashboard Cite

show abstract

“…LED patterns have been previously used by the authors in the context of localization of mobile robots in low-visibility conditions [33,34]. The use of high intensity LEDs improve the detection of the markers using optical sensors like cameras, where visibility is not optimal, like in smoke-filled environments or underwater in presence of water turbidity.…”

Section: Visually-guided Algorithm To Control a Robotic Armmentioning

confidence: 99%

Visually-guided manipulation techniques for robotic autonomous underwater panel interventions

Peñalver

Pérez

Fernández

et al. 2015

Annual Reviews in Control

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The long term of this ongoing research has to do with increasing the autonomy levels for underwater intervention missions. Bearing in mind that the specific mission to face has been the intervention on a panel, in this paper some results in different development stages are presented by using the real mechatronics and the panel mockup. Furthermore, some details are highlighted describing two methodologies implemented for the required visually-guided manipulation algorithms, and also a roadmap explaining the different testbeds used for experimental validation, in increasing complexity order, are presented. It is worth mentioning that the aforementioned results would be impossible without previous generated know-how for both, the complete developed mechatronics for the autonomous underwater vehicle for intervention, and the required 3D simulation tool. In summary, thanks to the implemented approach, the intervention system is able to control the way in which the gripper approximates and manipulates the two panel devices (i.e. a valve and a connector) in autonomous manner and, results in different scenarios demonstrate the reliability and feasibility of this autonomous intervention system in water tank and pool conditions.

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“…In other words, this Zigbee is suitable for complex systems. Figure 1 depicts the network layers for Zigbee [7][8][9][10].…”

Section: Zigbeementioning

confidence: 99%

Ubiquitous Sensor Networks and Image Processing Based Environmental Monitoring System for Fire Safety

Lee¹,

Jung

Lee

2014

International Journal of Distributed Sensor Networks

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In recent years, since the tall buildings are getting increased and getting dense in the city area, those buildings can be more and more exposed to risks such as fire and natural disasters. In case if the high-rise building is on fire, it is not easy to put out the fire even with the modernization of the firefighting equipment. These risks can directly lead to human casualties so that it is necessary to quickly have an initial evacuation or initial suppression risks. In this paper, we propose the integrated method for reducing the fire risks through sensors such as temperature and humidity, ZigBee technology, camera control and image processing technologies, and real-time data transmission technology. Based on our proposed method, it is expected that our integrated system directly leads to the expansion of risk safety management system as well as the development of USN technologies.

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Localization of Mobile Sensors and Actuators for Intervention in Low-Visibility Conditions: The ZigBee Fingerprinting Approach

Cited by 20 publications

References 22 publications

Comprehensive analysis of distance and similarity measures for Wi-Fi fingerprinting indoor positioning systems

Comprehensive analysis of distance and similarity measures for Wi-Fi fingerprinting indoor positioning systems

Visually-guided manipulation techniques for robotic autonomous underwater panel interventions

Ubiquitous Sensor Networks and Image Processing Based Environmental Monitoring System for Fire Safety

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