• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.481-486
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• 2007

Wireless Sensor Network(WSNs) consists of small sensor nodes with sensing, computation, and wireless communication capabilities. The large number of sensor nodes in a WSN means that there will often be some nodes which give erroneous sensor data owing to several reasons such as power shortage and transmission error. Generally, these sensor data are gathered by a sink node to monitor and diagnose the current environment. Therefore, this can make it difficult to get an effective monitoring and diagnosis. In this paper, to overcome the aforementioned problems, intelligent sensor data validation method based on PCA(Principle Component Analysis) is utilized. Furthermore, a practical implementation using embedded system is given to show the feasibility of the proposed scheme.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.27-36
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• 2011

The sensor nodes of sensor network system are capable of wireless communication with sink nodes. They also acquire and transmit sensor data in broad region where people cannot access easily. However, the transmission of redundant data from sensor nodes reduces the lifetime of the entire system and substantial amount of resulted data needs to be resorted before implementing them to the specific applications. In this paper, the mobile agent middleware to eliminate the redundant sensor data is designed and implemented. In the proposed system, the mobile agent visits the destination sensor nodes according to the migration list offered by the meta table in the name space of the naming agent, eliminates the redundant sensor data corresponding to user condition, and acquires and transmits sensor data according to the purpose and needs. Thus, the excess transmission of the sensor data is avoided and the lifetime of the entire system can be extended. Moreover, the experiments using the mobile agent middleware with the conditions and limitations that are possible in real situation ore done to verify the successful elimination of the redundant sensor data and the efficiency of the data acquisition. Also, we show the potential applicability of the mobile agent middleware in various active sensor networks through the active rule based mobile agent middleware or the interaction with the active rule system.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.441-457
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• 2014

Observed from the recent performance evaluation of clustering schemes in wireless sensor networks, we found that most of them did not consider various sensor characteristics and its application environment. Without considering these, the performance evaluation results are difficult to be trusted because these networks are application-specific. In this paper, for the fair evaluation, we measured several clustering scheme's performance variations in accordance with sensor data pattern, number of sensors per node, density of points of interest (data density) and sensor coverage. According to the experiment result, we can conclude that clustering methods are easily influenced by POI variation. Network lifetime and data accuracy are also slightly influenced by sensor coverage and number of sensors. Therefore, in the case of the clustering scheme that did not consider various conditions, fair evaluation cannot be expected.

• Journal of Sensor Science and Technology
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• v.14 no.3
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• pp.150-155
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• 2005

We propose a newly developed automobile sensor monitoring system incorporated with a tire pressure monitoring sensor(TPMS). The RF-transmitter based on a tire pressure sensor, sends a frame data about measured tire-pressure to RF receiver. And the various sensing signals based on sensors such as fuel-level sensor, engine oil level sensor and temperature sensors, are converted into 10-bit digital data. The microprocessor displays converting data such as tire pressure, trip distance, fuel quantity, coolant temperature and car-room temperature, on LCD panel. The proposed system can be successfully adapted to monitoring of the tire pressure and various automobile sensors.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.475-480
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• 2023

When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

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

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.99-102
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• 2003

In this paper, we have developed a system for monitoring and processing the real time sensor data in remote site through Internet. For realizing this system, measurement equipment and protocol are used to transmit the measurement data to remote server and to process measurement data. In server part, the received data from remote site sensor is converted to text or graphic charts for user. The measurement device in sensor part receives the sensor data form sensor and store the received data to its internal memory for transmitting data to server part through Internet. Also the measurement device can receive data form server. The temperature sensor is corrected to the measurement device located in laboratory and the measurement device measures temperature of laboratory which can be confirmed by user through Internet. We have developed a server program working on the Linux to store measurement data from measurement device to server memory. The program is use for SNMP(Simple Network Management Protocol) to exchange data with measurement device. Also the program changes the measurement data into text and graphic charts for user display. The program is use apache PHP program for user display and inquiry. The real time temperature measurement system can be applly for many parts of industry and living.

• Journal of Sensor Science and Technology
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• v.16 no.5
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• pp.361-368
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• 2007

Small size real-time ECG signal analysis function by QRS-complex detection was put into sensor nodes. Wireless sensor nodes attached on the patient’s body transmit ECG data continuously in normal u-healthcare system. So there are heavy communication traffics between sensor nodes and gateways. New developed platform for real-time analysis of ECG signals on sensor node can be used as an advanced diagnosis and alarming system for healthcare. Sensor node does not need to transmit ECG data all the time in wireless sensor network and to server PC via gateway. When sensor node detects suspicion or abnormality in ECG, then the ECG data in the network was transmitted to the server PC for further powerful analysis. This system can reduce data packet overload and save some power in wireless sensor network. It can also increase the server performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.672-677
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• 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
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• v.11 no.4
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• pp.51-58
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• 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.