• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.116-119
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• 2015

In this paper we propose an algorithm for environment monitoring using multiple mobile sensor (MS) nodes. Our focus is on maximizing sensing coverage of a group of MS nodes for monitoring a phenomenon in an unknown and open area over time. In the proposed algorithm, MS nodes are iteratively relocated to new positions at which a higher sensing coverage can be obtained. We formulated an integer linear programming (ILP) optimization problem to find the optimal positions for MS nodes with the objective of coverage maximization. The performance evaluation was performed to confirm that the proposed algorithm can enable MS nodes to relocate to high interest positions, and obtain a maximum sensing coverage.

• Smart Structures and Systems
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• v.17 no.4
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• pp.669-690
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• 2016

Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describes a data management infrastructure for bridge monitoring applications. Specifically, NoSQL database systems such as MongoDB and Apache Cassandra are employed to handle time-series data as well the unstructured bridge information model data. Standard XML-based modeling languages such as OpenBrIM and SensorML are adopted to manage semantically meaningful data and to support interoperability. Data interoperability and integration among different components of a bridge monitoring system that includes on-site computers, a central server, local computing platforms, and mobile devices are illustrated. The data management framework is demonstrated using the data collected from the wireless sensor network installed on the Telegraph Road Bridge, Monroe, MI.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.89-96
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• 2016

In this paper, we study mobile data collector (MDC) based data-gathering schemes in wireless sensor networks. In Such networks, MDCs are used to collect data from the environment and transfer them to the sink. The majority of existing data-gathering schemes suffer from high data-gathering latency because they use only a single MDC. Although some schemes use multiple MDCs, they focus on maximizing network lifetime rather than minimizing packet delay. In order to address the limitations of existing schemes, this paper focuses on minimizing packet delay for given number of MDCs and minimizing the number of MDCs for a given delay bound of packets. To achieve the minimum packet delay and minimum number of MDCs, two optimization problems are formulated, and traveling distance and traveling time of MDCs are estimated. The interior-point algorithm is used to obtain the optimal solution for each optimization problem. Numerical results and analysis are presented to validate the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.672-674
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• 2014

Mobile communication technology was one of the GPS technology, SmartPhone, Tablet PC is equipped with a GPS. So the user has a navigation, speed and his position to send and receive a variety of information. Therefore, in this paper, Mobile devices, GPS, Wi-Fi and mobile networks, and the communication module uses algorithms to analysis of acceleration and output, the user is currently using the system to find out the kind of transportation. This is the users who are using a particular transport unnecessary information and apply it to different areas do not think I will be able to.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.482-485
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• 2007

Recent generation of wireless computing has focus on the integrating of exisitng technologies to enhance the mobile capabilities and developing a new approaches to meet the needs of the growing pool of applications. This paper describes an integrated IEEE802.15.4 wireless CDMA based healthcare system that interacts and received the data wirelessly from wireless medical devices of patient and forward to medical center by using the cellular network. Mobile application had been developed not only as the middle ware to handle the receive and transmit of medical data between wireless sensor network and cellular network but also provides the interface for monitoring and analyzing the health condition of patients continuously at cellular phone regardless of its physical location. This system thus enables the remote healthcare monitoring and supports medical data seamlessly roams between IEEE802.15.4 wireless network and CDMA network beyond and outside the hospital environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5A
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• pp.466-473
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• 2010

Several protocols which are based on tree topology to guarantee the important metrics such as energy efficiency in sensor networks have been proposed. However, studies on the effect of topologies in sensor networks, where base node has a high mobility, are very few. In this paper, we propose a minimum Wiener index tree as a suitable topology to the wireless sensor networks with high mobile base node. The minimum Wiener index spanning tree problem which aims to find a tree with minimum Wiener index from a given weighted graph was proved to be NP-hard. We designed a branch and bound algorithm for this problem. To evaluate the performance of proposed tree, the comparisons with minimum spanning tree in terms of transmission distance, energy consumption during one round, and network lifetime was performed by simulations. Our proposed tree outperformed in transmission distance and energy efficiency but underperformed in lifetime.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.2014-2025
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• 2015

Wireless Sensor Networks (WSNs) are special network which has purpose of usage for gathering information of certain area and observing situation. WSNs consist of small nodes with sensing event such as temperature, movement or certain objects. The sensor has the capabilities to collect data and route data back to the sink. The sensors route data either to other sensors or back to a sink in one direction. That is, traditional WSNs communicate asymmetrically. However, under the new paradigm of the Internet of Things (IoTs) or Cyber Physical system (CPS), WSNs have potential to be used as important area. So, more research is necessary to communicate with each moving objects symmetrically in WSNs. In this paper, we proposed symmetric communication scheme among mobile objects in wireless sensor network. Simulation results show that our scheme is superior th the existing ones in terms of energy consumption and transmission success ratio.

• Journal of KIISE:Information Networking
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• v.30 no.6
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• pp.755-763
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• 2003

To improve performance over noisy wireless channels, mobile wireless networks employ forward error correction(FEC) techniques. The performance of static FEC algorithms, however, degrades by poorly matching the overhead of their correction code to the degree of the fluctuating underlying channel error. This paper proposes an adaptive FEC technique called FECA(FEC-level Adaptation), which dynamically tunes FEC strength to the currently estimated channel error rate at the data link layer. FECA is suitable for wireless networks whose error rate is high and slowly changing compared to the round-trip time between two communicating nodes. One such example network would be a sensor network in which the average bit error rate is higher than $10^{-6}$ and the detected error rate at one time lasts a few hundred milliseconds on average. Our experiments show that FECA performs 15% in simulations with theoretically modeled wireless channels and in trace-driven simulations based on the data collected from real sensor networks better than any other static FEC algorithms.

• Journal of Sensor Science and Technology
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• v.30 no.1
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• pp.15-19
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• 2021

Image processing is one of the major techniques that are used for computer vision. Nowadays, researchers are using machine learning and deep learning for the aforementioned task. In recent years, digit recognition tasks, i.e., automatic meter recognition approach using electric or water meters, have been studied several times. However, two major issues arise when we talk about previous studies: first, the use of the deep learning technique, which includes a large number of parameters that increase the computational cost and consume more power; and second, recent studies are limited to the detection of digits and not storing or providing detected digits to a database or mobile applications. This paper proposes a system that can detect the digital number of meter readings using a lightweight deep neural network (DNN) for low power consumption and send those digits to an Android mobile application in real-time to store them and make life easy. The proposed lightweight DNN is computationally inexpensive and exhibits accuracy similar to those of conventional DNNs.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.5
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• pp.739-744
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• 2013

In the past several years there has been increasing the studies using ubiquitous technology as the base technology of IT-convergence. The cooltown, one of the ubiquitous projects, is based on the web technology and the mobile environment. However, in the cooltown system, users only get a pre-made web-page. In this paper, we propose the algorithm improved usability applying the context-awareness based on the sensor network. In this paper, we can provide a custom tailored service overlooked in the existing system from this.