• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.107-116
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• 2013

We proposed the WSN monitoring system applied the augmented reality to visualize effectively an indoor WSN. To implement system, we used wireless sensor network, indoor location determination, location-based augmented reality technology. First, we composed the wireless sensor networks indoors and implement web server and then get data from server DB using Android phones. Then, we obtained the (x, y) coordinates using the triangulation method from RSSI of three point of the strongest signal strength of the AP's. Also, we adjusted coordinates using the Kalman filter. Finally, we inserted the adjusted coordinates to the latitude and the longitude of the Mixare that use the GPS signal, and we got location of user and wireless sensor in the server DB. After that, we implemented augmented reality system using the android phone and wireless sensor location and data and real life image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.477-485
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• 2015

Most existing simulators for wireless sensor networks(WSNs) are modeling battery-based sensors and providing MAC and routing protocols designed for battery-based WSNs. However, recently, as energy harvesting sensor systems have been studied more extensively, there is an increasing need for appropriate simulators, but few related studies have employed such simulators. Unlike existing simulators, simulators for energy harvesting WSNs require a new energy model that is integrated with the energy-harvesting model, rechargeable battery model, and energy-consuming model. Additionally, it should enable the applications of the well-known MAC and routing protocols designed for energy-harvesting WSNs, as well as a user-friendly interface for convenience. In this work, we design and implement a user-friendly simulator for solar energy-harvesting WSNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2504-2526
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• 2016

Wireless sensors are always deployed in brutal environments, but as we know, the nodes are powered only by non-replaceable batteries with limited energy. Sending, receiving and transporting information require the supply of energy. The essential problem of wireless sensor network (WSN) is to save energy consumption and prolong network lifetime. This paper presents a new communication protocol for WSN called Dynamical Threshold Control Algorithm with three-parameter Particle Swarm Optimization and Ant Colony Optimization based on residual energy (DPA). We first use the state of WSN to partition the region adaptively. Moreover, a three-parameter of particle swarm optimization (PSO) algorithm is proposed and a new fitness function is obtained. The optimal path among the CHs and Base Station (BS) is obtained by the ant colony optimization (ACO) algorithm based on residual energy. Dynamical threshold control algorithm (DTCA) is introduced when we re-select the CHs. Compared to the results obtained by using APSO, ANT and I-LEACH protocols, our DPA protocol tremendously prolongs the lifecycle of network. We observe 48.3%, 43.0%, and 24.9% more percentages of rounds respectively performed by DPA over APSO, ANT and I-LEACH.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8B
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• pp.630-635
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• 2008

Recently, in order to improve the energy efficiency of WSN(Wireless Sensor Network), widely research have teen carried on. But, up to the present, Majority of methods are based on direct communication between CH(cluster head) and sink node, and based on the assumption that node can regulate signal energy actively according to the distance between nodes. So it's hard to implement those methods. Based on the theory that node has fixed radio wave radius, this paper present a multi leveling routing protocol. According to the simulation of the presented protocol, we have proved the energy saving efficiency and the implementation in real WSN.

• Journal of Computing Science and Engineering
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• v.4 no.2
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• pp.128-152
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• 2010

With the advance of computer and communication technologies, wireless sensor networks (WSNs) are increasingly used in many aspects of our daily life. However, since the battery lifetime of WSN nodes is restricted, the WSN lifetime is also limited. Therefore, it is crucial to determine this limited lifetime in advance for preventing service interruptions in critical applications. This paper proposes a feasible static analysis approach to estimating the worstcase lifetime of a WSN. Assuming known routes with a given sensor network topology and SMAC as the underlying MAC protocol, we statically estimate the lifetime of each sensor node with a fixed initial energy budget. These estimations are then compared with the results obtained through simulation which run with the same energy budget on each node. Experimental results of our research on TinyOS applications indicate that our approach can safely and accurately estimate worst-case lifetime of the WSN. To the best of our knowledge, our work is the first one to estimate the worst-case lifetime of WSNs through a static analysis method.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.7
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• pp.241-244
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• 2014

Wireless Sensor Network(WSN) has been attracting lots of interest in recent years for smart surveillance systems. WSN-based surveillance systems need to figure out the occurrence or existence of events or objects and to find out where the events have occurred or the objects are present. In our surveillance system, it is needed to give an alarm only when the detected object is human (not pets or rodents) for reducing false alarms and improving the system reliability. In this paper, we propose a height prediction mechanism to determine if the detected object is human using Heron's formula. Finally, we verify the performance of our proposed mechanism through various experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7B
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• pp.721-727
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• 2009

Wireless Sensor Networks(WSN) make use of low cost and energy constrained sensor nodes. Thus, reaching the successful execution of its tasks with low energy consumption is one of the most important issues. The limitation of existing hierarchical algorithms is that many times the data are transmitted to the opposite direction to the sink. In this paper, DDACM (Data Direction Aware Clustering Method) is proposed. In this method, the nearest node to the sink is elected as cluster head, and when its energy level reaches a threshold value, the cluster head is reelected. We also make a comparison with LEACH showing how this method can reduce the energy consumption minimizing the reverse direction data transmission.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.265-273
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• 2007

This paper expands an analytical performance model of 802.11 to accurately estimate throughput and energy demand of 802.11-based wireless sensor network (WSN) when sensor nodes employ Reed-Solomon (RS) codes, one of block forward error correction (FEC) techniques. This model evaluates these two metrics as a function of the channel bit error rate (BER) and the RS symbol size. Since the basic recovery unit of RS codes is a symbol not a bit, the symbol size affects the WSN performance even if each packet carries the same amount of FEC check bits. The larger size is more effective to recover long-lasting error bursts although it increases the computational complexity of encoding and decoding RS codes. For applying the extended model to WSNs, this paper collects traffic traces from a WSN consisting of two TIP50CM sensor nodes and measures its energy consumption for processing RS codes. Based on traces, it approximates WSN channels with Gilbert models. The computational analyses confirm that the adoption of RS codes in 802.11 significantly improves its throughput and energy efficiency of WSNs with a high BER. They also predict that the choice of an appropriate RS symbol size causes a lot of difference in throughput and power waste over short-term durations while the symbol size rarely affects the long-term average of these metrics.

• Journal of IKEEE
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• v.22 no.2
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• pp.289-301
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• 2018

IIoT, the IoT technology applied to the industrial field, is being used as a monitoring technology for increasing in production rate and safety of workers. However, monitoring through the construction of IIoT network using Ethernet and RS485 in production lines where dozens to hundreds of machine tools are manufacturing components, have difficulties of infrastructure cost and network flexibility and fluidity. Therefore, in this paper, using IEEE 802.15.4 standard WSN device to construct a Ad-Hoc WSN in the production line. In addition, the transmission period and order of the sensor nodes are set by applying the EtherCAT communication method in which the payload frames are shared by all the sensor nodes. From this, we have overcome the problem of reliability decline and real-time issue due to the packet collision of wireless network and confirmed that it is a wireless network routing method that can be used in the actual industrial field.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.245-252
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• 2020

Unexpected equipment defects can cause a huge economic losses in the society at large. Although condition monitoring can provide solutions, the signal processing algorithms must be developed to predict mechanical failures using data acquired from various sensors attached to the equipment. The signal processing algorithms used in a condition monitoring requires high computing efficiency and resolution. To improve condition monitoring on a wireless sensor network(WSN), data visualization can maximize the expressions of the data characteristics. Thus, this paper proposes the extraction of visual feature from temperature data over time using condition monitoring based on a WSN to identify environmental conditions of equipment in a large-scale infrastructure. Our results show that time-frequency analysis can visually track temperature changes over time and extract the characteristics of temperature data changes.