• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2480-2487
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• 2011

As sensor technology grows up in fields such as environmental hazards detecting system, ubiquitous sensor network, intelligent robot, the sensing and detecting system for sensor is increasing. The sensor data is measured by change of chemical and physical status. Because of decrepit sensor or various sensing environment, it is problem that sensor data is inaccurate result. So the reliability of sensor data is essential. In this paper, we proposes a reliable sensor signal processing platform for various sensor. To improve reliability, we use same sensors in multiple array structure. As sensor data is corrected by spatial and temporal relation signal processing algorithm for measured sensor data, reliability of sensor data can be improved. The exclusive protocol between platform components is designed in order to verify sensor data and sensor state in various environment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.169-172
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• 2002

A vision sensor measure range data using laser light source. This sensor generally use patterned laser which shaped single line. But this vision sensor cannot satisfy new trend which feeds foster and more precise processing. The sensor's sampling rate increases as reduced image processing time. However, the sampling rate can not over 30fps, because a camera has mechanical sampling limit. If we use multi line laser pattern, we will measure multi range data in one image. In the case of using same sampling rate camera, number of 2D range data profile in one second is directly proportional to laser line's number. For example, the vision sensor using 5 laser lines can sample 150 profiles per second in best condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.584-587
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• 2002

A vision sensor measure range data using laser light source. This sensor generally use patterned laser which shaped single line. But this vision sensor cannot satisfy new trend which needs laster and more precise processing. The sensor's sampling rate increases as reduced image processing time. However, the sampling rate can not over 30fps, because a camera has mechanical sampling limit. If we use multi line laser pattern, we will measure multi range data in one image. In the case of using same sampling rate camera, number of 2D range data profile in one second is directly proportional to laser line's number. For example, the vision sensor using 5 laser lines can sample 150 profiles per second in best condition.

• ETRI Journal
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• v.30 no.5
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• pp.696-706
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• 2008

With the increasing need for intelligent environment monitoring applications and the decreasing cost of manufacturing sensor devices, it is likely that a wide variety of sensor networks will be deployed in the near future. In this environment, the way to access heterogeneous sensor networks and the way to integrate various sensor data are very important. This paper proposes the common system for middleware of sensor networks (COSMOS), which provides integrated data processing over multiple heterogeneous sensor networks based on sensor network abstraction called the sensor network common interface. Specifically, this paper introduces the sensor network common interface which defines a standardized communication protocol and message formats used between the COSMOS and sensor networks.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.333-336
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• 2005

The advance of wireless telecommunication and observation technologies leads developing sensor and sensor network for serving the context information continuously. Besides, in order to understand and cope with the context awareness based on the sensor network, it is becoming important issue to deal with plentiful data transmitted from various sensors. Therefore, we propose a context awareness system to deal with the plentiful sensor data in a vast area such as the prevention of a forest fire, the warning system for detecting environmental pollution, and the analysis of the traffic information, etc. The proposed system consists of the context acquisition to collect and store various sensor data, the knowledge base to keep context information and context log, the rule manager to process context information depending on user defined rules, and the situation information manager to analysis and recognize the context, etc. The proposed system is implemented for managing renewable energy data management transmitted from a large scale area.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.6
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• pp.323-330
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• 2012

Wireless sensor networks need middleware system for efficiently managing the constrained resource and sensing data because they need different sensing data type and protocol to communicate with heterogeneous sensor networks. Thus this paper proposes data-centric sensor middleware for heterogeneous sensor networks. The proposed middleware have to support various query processing of user applications, high-level request of users, manage heterogeneous sensor systems and universal sensing data type for node and user application.

• Journal of Sensor Science and Technology
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• v.16 no.3
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• pp.187-191
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• 2007

This paper presents a development of the multi-channel data acquisition/logging system for a sensor signal processing and a method of the evaluation and a temperature compensation for the A/D converters with the specific analog and digital circuit including the software. Also, we have designed a hardware and a software filters with smart algorithm for better signal processing of the proposed system. Software approach was adopted to obtain the stable data from A/D converter.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.743-749
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• 2020

Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edge-server. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1603-1609
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• 2010

This Paper deals with a design, making a prtotype and test methods of Real-time towed Line Array Sensor Data processing board for fast data communication and long range data transmission with SFM(Serial FPDP Module) through Optic-fiber channel. Towed line array sensors are installed in Frigate and the each LAS A, B, C group data from LAS is packed a previously agreed protocol and transmitted to the signal processing unit. Considering the limited space of VME 6U size, LAS Data processing board is designed with MPC8265 PowerPC Controller of Freescale for main system control and Altera's CycloneIII FPGA for sensor data packing, self-test simulation data generation, S/W FIFO et cetera. LAS Data processing board have VxWorks, the RTOS(Real Time Operating System) that present many device drivers, peripheral control libraries on board for real-time data processing.

• Spatial Information Research
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• v.22 no.5
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• pp.9-18
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• 2014

According to the recent development of the ubiquitous computing environment, the use of spatio-temporal data from sensors with GPS is increasing, and studies on the Semantic Sensor Web using spatio-temporal data for providing different kinds of services are being actively conducted. Especially, the W3C developed the SSNO(Semantic Sensor Network Ontology) which uses sensor-related standards such as the SWE(Sensor Web Enablement) of OGC and defines classes and properties for expressing sensor data. Since these studies are available for the query processing about non-spatio-temporal sensor data, it is hard to apply them to spatio-temporal sensor data processing which uses spatio-temporal data types and operators. Therefore, in this paper, we developed the SWE based on SSNO which supports the spatio-temporal sensor data types and operators expanding spatial data types and operators in "OpenGIS Simple Feature Specification for SQL" by OGC. The system receives SensorML(Sensor Model Language) and O&M (Observations and Measurements) Schema and converts the data into SSNO. It also performs the efficient query processing which supports spatio-temporal operators and reasoning rules. In addition, we have proved that this system can be utilized for the web service by applying it to a virtual scenario.