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

• Journal of Korea Multimedia Society
• /
• v.19 no.3
• /
• pp.573-584
• /
• 2016

Recent application range of sensor networks is becoming diverse. It means collected sensor data types are becoming diverse too. These sensor data have their own characteristics. Thus achieving energy efficiency, existing sensor network management policy consider their own characteristics. However, it is inefficient to apply the existing network management schemes for controlling such kind of data at the same time. Because, existing network management schemes considered one type of data only. Therefore, we propose a novel routing scheme that is able to efficient energy conservation through effective data controlling on multi-sensor application environment.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.8B
• /
• pp.1003-1011
• /
• 2011

In this paper, a real-time multi-source sensor data management system based on wireless sensor network is proposed and implemented. The proposed management system is designed to transmit the wireless data to the server in order to monitor and control the multi-source target's status efficiently by analyzing them. The proposed system is implemented to make it possible to control and transmit the wireless sensor data by classifying them, of which data are issued from the clustered sources composed of a number of the remote multiple sensors. In order to evaluate the performance of the proposed system, we measure and analyze both the transmission delay time according to the distance and the data loss rate issued from multiple data sources. From these results, it is verified that the proposed system has a good performance.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.5 no.6
• /
• pp.672-677
• /
• 2010

Recently, the efficient management system for large-scale sensor data has been required due to the increasing deployment of large-scale sensor networks. In this paper, we propose a cloud-based sensor data management system with low cast, high scalability, and efficiency. Sensor data in sensor networks are transmitted to the cloud through a cloud-gateway. At this point, outlier detection and event processing is performed. Transmitted sensor data are stored in the Hadoop HBase, distributed column-oriented database, and processed in parallel by query processing module designed as the MapReduce model. The proposed system can be work with the application of a variety of platforms, because processed results are provided through REST-based web service.

• Journal of Internet Computing and Services
• /
• v.11 no.4
• /
• pp.51-58
• /
• 2010

In this paper, we introduce various attempts to transmit sensor data efficiently for design of a water quality monitoring system under the USN environment. The representative methods are the sensor management on a sensor node and the clustering on a sink node. The sensor management includes controls of sensing intervals, data accumulations, and data transmissions. And the clustering is one of efficient data compression methods using data mining technology. From the experimental results we confirmed that the proposed transmission method using the sensor management and the clustering outperformed common transmission method.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.2
• /
• pp.126-131
• /
• 2008

Wireless Sensor Network(WSNs) consists of small sensor nodes with sensing, computation, and wireless communication capabilities. It has new information collection scheme and monitoring solution for a variety of applications. Faults occurring to sensor nodes are common due to the limited resources and the harsh environment where the sensor nodes are deployed. In order to ensure the network quality of service it is necessary for the WSN to be able to detect the faulty sensors and take necessary actions for the reconstruction of the lost sensor data caused by fault as earlier as possible. In this paper, we propose an recursive PCA-based fault detection and lost data reconstruction algorithm for sensor networks. Also, the performance of proposed scheme was verified with simulation studies.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.12 no.3
• /
• pp.1-9
• /
• 2016

The current meaning of "Big Data" refers to all the techniques for value eduction and actionable analytics as well management tools. Particularly, with the advances of wireless sensor networks, they yield diverse patterns of digital records. The records are mostly semi-structured and unstructured data which are usually beyond of capabilities of the management tools. Such data are rapidly growing due to their complex data structures. The complex type effectively supports data exchangeability and heterogeneity and that is the main reason their volumes are getting bigger in the sensor networks. However, there are many errors and problems in applications because the managing solutions for the complex data model are rarely presented in current big data environments. To solve such problems and show our differentiation, we aim to provide the solution of actionable analytics and semantic reusability in the sensor web based streaming big data with new data structure, and to empower the competitiveness.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.2
• /
• pp.95-101
• /
• 2019

Sensor application systems for remote monitoring and control are required, such as the establishment of databases and IoT service servers, to process data being transmitted and received through radio communication modules, controllers and gateways. This paper designs and implements database server, IoT service server, data processing middleware and IoT management system for IoT based services based on the controllers, communication modules and gateway middleware platform developed. For this, we firstly define the specification of the data packet and control code for the information classification of the sensor application system, and also design and implement the database as a separate server for data protection and efficient management. In addition, we design and implement the IoT management system so that functions such as status information verification, control and modification of operating environment information of remote sensor application systems are carried out. The implemented system can lead to efficient operation and reduced management costs of sensor application systems through site status analysis, setting operational information, and remote control and management.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.1
• /
• pp.39-45
• /
• 2014

This paper proposes an architecture of a sensor network for gathering data under a powerful beam cluster tree architecture. This architecture is used when there is a need to gather data from sensor node where there is no sink node connected to an existing network, or it is required to get a series of data specific to an event or time. The transmit distance of the beam signal is longer than that of the usual sensor node. The nodes of the network make a tree network when receiving a beam message transmitting from the powerful root node. All sensor nodes in a sink tree network synchronize to the superframe and know exactly the sequence value of the current superframe. When there is data to send to the sink node, the sensor node sends data at the corresponding allocated channel. Data sending schemes under the guaranteed time slot are tested and the delay and jitter performance is explained.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.5 no.2
• /
• pp.123-131
• /
• 2009

Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. Recently, Nilsson et al. proposed a key management scheme for PCS/SCADA, which was claimed to provide forward and backward secrecies. In this paper, we define four different types of adversaries or attackers in wireless sensor network environments in order to facilitate the evaluation of protocol strength. We then analyze Nilsson et al. 's protocol and show that it does not provide forward and backward secrecies against any type of adversary model.