Malguki: an RSSI based ad hoc location algorithm

Arias, Jagoba; Zuloaga, Aitzol; Lázaro, Jesús; Andreu, Jon; Astarloa, Armando

doi:10.1016/j.micpro.2004.03.001

Cited by 54 publications

(15 citation statements)

References 6 publications

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“…The software used localisation data from the DB, implementing a sensor fusion approach based on a Kalman Filter for estimating the user's position. The KF was implemented exploiting both range-free (Arias et al 2004) and range-based (Cavallo et al 2014a) localisation methods, according to Wang et al (Wang et al 2013). Presence sensors were also used to improve positioning accuracy and perform host detection.…”

Section: Application Layer the Cloud Platform Provided Saas Features mentioning

confidence: 99%

Enabling personalised medical support for chronic disease management through a hybrid robot-cloud approach

et al. 2016

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Information and Communication Technology and personal robots could play a fundamental role in efficiently managing chronic diseases and avoiding improper medications. They could support senior citizens with reminders, thus promoting their independent living and quality of life, especially in the presence of several chronic diseases (multimorbidity). In this context, this article proposes a service model for personalised medical support that is able to provide adequate healthcare service by means of a hybrid robot-cloud approach. This service was quantitatively and qualitatively tested to assess the technical feasibility and user acceptability level of the service. The service was tested with 23 older people (65-86 years) in the DomoCasa Lab (Italy). This study demonstrated the feasibility of the proposed hybrid cloud solution and the usability and acceptability were positively evaluated thus confirming the ability to utilise these innovative technologies for active and healthy ageing.

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Section: Application Layer the Cloud Platform Provided Saas Features mentioning

confidence: 99%

Enabling personalised medical support for chronic disease management through a hybrid robot-cloud approach

et al. 2016

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“…If the time of emission of signal is known, recording the time of arrival of signal at the receiver, the distance d can be calculated as in [10]. These weights determine the relative importance of each quantity on the average.…”

Section: A Principlementioning

confidence: 99%

An improved centroid localization algorithm based on weighted average in WSN

Cheng

Wang

Hua-kui

2011

2011 3rd International Conference on Electronics Computer Technology

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Location information of sensor node in wireless sensor networks is necessary for many WSNs' applications, the ability of sensor nodes to estimate their accurate position is crucial. In order to improve the location accuracy of centroid algorithm, we present an improved weighted centroid location algorithm (IWCA) with a time of arrival weight, which can weaken the negative effects of the density of beacon nodes and uniformity of deployment. By using weighted average of the received beacon nodes' coordinates instead of arithmetic mean as the estimation results, receivers can obtain optimum localization results. The performance analysis of both IWCA and centroid algorithm (CA) are presented. Simulation results show that IWCA can operate efficiently by using timeweighted centroid mechanisms.

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“…The adaptive gain should be carefully selected to improve the rate of convergence with reasonable mean square error. Some useful mathematical expressions are described below and can be found in detail in [7]. The cost function φ is defined by,…”

Section: Malguki Spring Model (Msm)mentioning

confidence: 99%

“…We have implemented various algorithms based on multilateration rather than triangulation. These selected algorithms are maximum likelihood estimation (MLE) [4,5], modified multidimensional scaling (MMDS) [6], Malguki spring model (MSM) [7] and weighted multidimensional scaling (WMDS) [8].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Performance of Various Localization Algorithms in Wireless and Sensor Networks

Desai

Tureli

2007

2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications

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In this paper, recent localization algorithms are analyzed under a common one hop network scenario. The performance of localization is affected by physical parameters in a real wireless environment such as anchor node location and quantity, and error in the measured distance. The numerical analysis presented in this paper can be used to choose among localization algorithms to satisfy practical constraints such as number of anchors, nodes, geometry of anchors and computational efficiency. I INTRODUCTIONLocalization performs a key role in higher level services in current wireless sensor, ad-hoc and cellular networks. Sensor network comprises small size, low power and low cost nodes with various sensors, e.g. temperature, audio, humidity, proximity and others. Typical applications are in surveillance, security applications and monitoring. Location awareness in such networks is crucial due to the position dependent data collection and to reduce overhead for routing data. GPS is not an appropriate solution for localization due to cost, power consumption and its limited application to outdoor environment [1].Popularity of wireless LAN and Bluetooth networks has created security issues and challenges for various location based attacks. Monitoring and tracking the location of wireless nodes reduce these security threats with providing location of attacker [2]. Furthermore, knowledge of location is greatly helpful in routing algorithms and in location critical applications, e.g. first responders and emergency calls.The essential part of localization is range measurement and can be performed by time of arrival (TOA), time difference of arrival (TDOA) or received signal strength indication (RSSI) measurements [3]. Since many devices already have the ability to measure RSSI, we consider ranging using RSSI measurements. A simple radio frequency propagation model is assumed for range measurement and all algorithms are analyzed under this model. We have implemented various algorithms based on multilateration rather than triangulation. These selected algorithms are maximum like- * The work of J. lihood estimation (MLE) [4, 5], modified multidimensional scaling (MMDS) [6], Malguki spring model (MSM) [7] and weighted multidimensional scaling (WMDS) [8].The rest of the paper is organized as follows. In section II the system model is proposed. Section III provides a brief summary of all algorithms to be analyzed. Section IV covers simulation results and discussion regarding the performance of each algorithm. Comparison table is presented in section V. Finally, we conclude with future work in section VI. II SYSTEM MODEL A Propagation ModelIn this paper, the performance of localization algorithms is evaluated under a common scenario. Instead of a very complicated indoor wireless channel model, a simple path loss model is assumed. The signal power in an actual environment decays with the distance [9]. The loss of power depends on various obstacles between transmitter and receiver. The overall effect results in lognormal distribution of...

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Malguki: an RSSI based ad hoc location algorithm

Cited by 54 publications

References 6 publications

Enabling personalised medical support for chronic disease management through a hybrid robot-cloud approach

Enabling personalised medical support for chronic disease management through a hybrid robot-cloud approach

An improved centroid localization algorithm based on weighted average in WSN

Evaluating Performance of Various Localization Algorithms in Wireless and Sensor Networks

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