• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.9-17
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• 2014

This paper proposes a binary particle swarm optimization (BPSO) algorithm for distributed node localization in wireless sensor networks (WSNs). Each unknown node performs localization using the value of the measured distances from three or more neighboring anchors, i.e., nodes that know their location information. The node that is localized during the localization process is then used as another anchor for remaining nodes. The performances of particle swarm optimization (PSO) and BPSO in terms of localization error and computation time are compared by using simulations in Matlab. The simulation results indicate that PSO-based localization is more accurate. In contrast, BPSO algorithm performs faster for finding the location of unknown nodes for distributed localization. In addition, the effects of transmission range and number of anchor nodes on the localization error and computation time are investigated.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.606-608
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• 2005

In this paper, we introduce localization server system calculated real location of objects using raw data of location-awareness from sensor node gateway. The software architecture of localization server system consists of location calculation and actuator control based on location. Also, this system supports for collecting raw data, calculating location of real objects using raw data, correcting error from outer environment, and server for applications based on location.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.885-890
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• 2012

In this Paper, we propose a Real-Time Localization Platform Built on WUSB (Wireless USB) over WBAN (Wireless Body Area Networks) protocol required for Wearable Computer systems. Proposed Real-Time Localization Platform Technique is executed on the basis of WUSB over WBAN protocol at each sensor node comprising peripherals of a wearable computer system. In the Platform, a WUSB host calculates the location of a receiving sensor node by using the difference between the times at which the sensor node received different WBAN beacon frames sent from the WUSB host. And the WUSB host interprets motion of the virtual object.

• Journal of Digital Convergence
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• v.13 no.7
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• pp.207-212
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• 2015

The sensor network that is component of the Internet of Things require a lot of research to select the best route to send information to the anchor node, to collect a number of environment and cost efficient for communication between the sensor life. On the sensor network in one of the components of IOT's environment, sensor nodes are an extension device with low power low capacity. For routing method for data transmission between the sensor nodes, the connection between the anchor and the node must be accurate with in adjacent areas relatively. Localization CA (Centroid Algorithm) is often used although an error frequently occurs. In this paper, we propose a range-free localization method between sensor nodes based on the Radical Line in order to solve this problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.530-536
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• 2008

Localization is one of the fundamental problems in wireless sensor networks (WSNs) that forms the basis for many location-aware applications. Localization in WSNs is to determine the position of node based on the known positions of several nodes. Most of previous localization method use triangulation or multilateration based on the angle of arrival (AOA) or distance measurements. In this paper, we propose an enhanced centroid localization method based on edge weights of adjacent nodes using fuzzy modeling and genetic algorithm when node connectivities are known. The simulation results shows that our proposed centroid method is more accurate than the simple centroid method using connectivity only.

• Journal of Engineering Education Research
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• v.15 no.5
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• pp.93-97
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• 2012

Most of ubiquitous computing devices such as stereo camera, ultrasonic sensor based MIT cricket system and other wireless sensor network devices are widely applied to the 2 Dimensional(2D) localization system in today. Because stereo camera cannot estimate the optimal location between moving node and beacon node in Wireless Personal Area Network(WPAN) under Non Line Of Sight(NLOS) environment, it is a great weakness point to the design of the 2D localization system in indoor environment. But the conventional 2D triangulation scheme that is adapted to the MIT cricket system cannot estimate the 3 Dimensional(3D) coordinate values for estimation of the optimal location of the moving node generally. Therefore, the 3D triangulation scheme based on the space segmentation in WPAN is suggested in this paper. The measuring data in the suggested scheme by computer simulation is compared with that of the geographic measuring data in the AutoCAD software system. The average error of coordinates values(x,y,z) of the moving node is calculated to 0.008m by the suggested scheme. From the results, it can be seen that the location correctness of the suggested scheme is very excellent for using the localization system in WPAN.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.33-42
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• 2013

This paper presents a multihop range-free localization algorithm to estimate the physical location of a normal node with local connectivity information in anisotropic sensor networks. In the proposed algorithm, a normal node captures the detour degree of the shortest path connecting an anchor pair and itself by comparing the measured hop count and the expected hop count, and the node estimates the distances to the anchors based on the detour degree. The normal node repeats this procedure with all anchor combinations and pinpoints its location using the obtained distance estimates. The proposed algorithm requires fewer anchors and less communication overhead compared to existing range-free algorithms. We showed the superiority of the proposed algorithm over existing range-free algorithms through MATLA simulations.

• Journal of IKEEE
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• v.22 no.3
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• pp.658-663
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• 2018

In this paper, we consider node deployment algorithms for the sequence-based localization (SBL) which is recently employed for in-door positioning systems, Whereas previous node selection or deployment algorithms seek to place nodes at centrold of the region where more targets are likely to be found, we observe that the boundaries dividing such regions can be good locations for the nodes in SBL systems. Motivated by this observation, we propose an efficient node deployment algorithm that determines the boundaries by using the well-known K-means algorithm and find the potential node locations based on the bi-section method for low-complexity design. We demonstrate through experiments that the proposed algorithm achieves significant localization performance over random node allocation with a substantially reduced complexity as compared with a full search.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2885-2890
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• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.837-840
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• 2010

Wireless Sensor Networks have been proposed for several location-dependent applications. For such systems, the cost and limitations of the hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point to point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we proposed a Coefficient Allocated DV-Hop (CA DV-Hop) algorithm which reduces node's location error by awarding a credit value with respect to number of hops of each anchor to an unknown node. Simulation results have verified the high estimation accuracy with our approach which outperforms the classical DV-Hop.