An environment adaptive ZigBee-based indoor positioning algorithm
Morelab, DeustoTech, Bilbao, Spain
DOI: 10.1109/IPIN.2010.5647828 Conference: Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on
Lately, there has been significant progress in the field of wireless communications and networking. Furthermore, the number of applications that require context information as the user's location will increase in the coming years. However, this issue still has not been solved indoors due to the RF (Radio Frequency) signals' behaviour in this kind of scenarios. In this paper, we present a robust, easy to deploy and flexible indoor localization system based on ZigBee Wireless Sensor Networks. It is important to mention that our localization system is based on RSSI (Received Signal Strength Indicator) level measurements since this information can be obtained directly from the messages exchanged between nodes, so no extra hardware is required. Our localization system consists of two phases: calibration and localization. Anytime a blind node needs to be located, our system performs calibration using a matrices system, so that the environment can be characterized, taking into account possible changes on it since the last request. Then, in the localization phase, the central server processes all the information and calculates the blind node's position with the new iterative algorithm we present. With this indoor positioning algorithm we can estimate the blind node's position with a good resolution (3 m average error), so we can say that this ZigBee localization algorithm provides very promising results.
Available from: Maissa Ben Jamâa
- "In addition, heavy loaded computations are complex and memory greedy which inhibit the possibility of their implementation in resources constrained sensor nodes. It turns out that although several works, such as       have reduced the deployment phase complexity, they are still difficult to implement and too heavy to operate on sensor node with limited resources. In particular, authors in  have considered practical issues in their design, but their approach was simply validated using MATLAB simulations and offline empirical data analysis where no implementation was reported. "
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ABSTRACT: Localization based on Received Signal Strength (RSS) is a key method for locating objects in Wireless Sensor Networks (WSNs). However, current RSS-based methods are ineffective at both deployment and operation design levels since they (i.) usually require a labor-intensive pre-deployment profiling operations to map the RSS to either locations or distances and (ii.) rely on heavy processing operations. These two designs problems limit the possibility of implementing the localization technique on resources constrained sensor nodes and also restrict its scalability and practical use. In this paper, we tackle the challenge of devising a self-organizing and practical RSS-based localization technique that improves on previous approaches in terms of ease of deployment, ease of implementation while still providing a reasonable accuracy. To this end, we come up with a new solution, EasyLoc, a plug-and-play and distributed RSS-based localization method that requires zero pre-deployment configuration. The idea consists in exploiting the available distance information between anchors to derive an online and anchor-specific RSS-to-distance mapping. We show that, in addition to its simplicity, EasyLoc provides location errors of 90% less than 1m and an average error of 0.48m in small environment and 1.8m in large environment. (C) 2012 Published by Elsevier Ltd.
Procedia Computer Science 12/2012; 10:1127-1133. DOI:10.1016/j.procs.2012.06.160
Available from: Rohana Mahmud
- "proposed the indoor positioning systems that estimate the position of the objects by analyzing the received signal strengths in which the service area is divided into zones and sub-zones. In , the authors proposed the algorithm based on the decent gradient iteration to define the object position. In , the RSS-based techniques were used to estimate the distance between the object and the referencing nodes and the triangulation techniques were used to define the object position. "
Available from: Christian Ibars
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ABSTRACT: The ability of a sensor node to determine its position is a fundamental requirement for many applications in wireless sensor networks (WSNs). In this article, we address a scenario where a subset of sensors, called anchor nodes, knows its own position and helps other nodes determine theirs through range-based positioning techniques. Such techniques benefit from a high degree of connectivity, since range measurements from at least four anchor nodes are necessary (three-dimensional scenario). On the other hand, WSN topologies, most notably the cluster-tree topology, tend to limit connectivity between nodes to save energy. This results in very poor performance of the network in terms of localization. In this article, we propose LACFA, a network formation algorithm that increases the probability of localization of sensors in a cluster-tree topology. It does so by properly allocating anchor nodes to different clusters during the network formation phase. Our algorithm achieves very high localization probability when compared with existing cluster formation algorithms, at no additional cost. Moreover, a distributed cluster formation algorithm, with no need for any centralized information exchange mechanisms, is defined.
EURASIP Journal on Wireless Communications and Networking 10/2011; 2011(121):1. DOI:10.1186/1687-1499-2011-121 · 0.72 Impact Factor
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