• Journal of Sensor Science and Technology
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• v.15 no.1
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• pp.7-12
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• 2006

The multi-functional one-chip sensor has been fabricated to reduce output variation under various water environment. There were a temperature sensor, a piezoresistive type pressure sensor, and a electrode type conductivity sensor in the fabricated one-chip sensor. This sensor was measured water depth in the range of $0{\sim}180cm$, temperature in the range of $0{\sim}50^{\circ}C$, and salinity in the range of 0 $0wt%{\sim}5wt%$, respectively. Since the change of water depth in solution environment depends on various factors such as salinity, latitude, temperature, and atmospheric pressure, the water depth sensor is needed to be compensated. We tried to compensate the salinity and temperature dependence for the pressure in water by using lookup-table method.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.1
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• pp.195-201
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• 2012

Environmental information monitoring system with a control system and a sensor node transfers real-time collected data from sensor node to the remote control system. Operability of the control system can significantly decrease depending on its operating environment, type of sensor and the number of sensor installed on the sensor node and the communication environment between the control system and sensor node. In this study, we proposed and implemented component-based environmental information monitoring system using the appropriate components depending on operating environment in order to increase operational efficiency.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.138-147
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• 2017

In this paper, we introduce smart multi-sensor and environment monitoring system for managing growth and development of the agricultural produces. This system is able to help to collect the sensor information about the growing environment and to monitor in wired and wireless environments. Existing systems installed each kinds of sensor to gather information. In this case, installation cost was incurred about each sensor and the position of sensor set up manually. Therefore, this paper designed and implemented smart multi-sensor that simplify sensors in order to minimize the cost for installing each sensor. In addition, this system is able to monitor position and data information of smart multi-sensor using RFID communication

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.27-33
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• 2010

In this study, we conducted the classification experiments with GMM (Gaussian Mixture Model) from combining the extracted features by using microphone, Gyro sensor and Acceleration sensor in 9 different environment types. Existing studies of Context Aware wanted to recognize the Environment situation mainly using the Environment sound data with microphone, but there was limitation of reflecting recognition owing to structural characteristics of Environment sound which are composed of various noises combination. Hence we proposed the additional application methods which added Gyro sensor and Acceleration sensor data in order to reflect recognition agent's movement feature. According to the experimental results, the method combining Acceleration sensor data with the data of existing Environment sound feature improves the recognition performance by more than 5%, when compared with existing methods of getting only Environment sound feature data from the Microphone.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.83-92
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• 2010

Sensor networks applications can be employed by a vast range of applications. Environmental information monitoring systems and ecosystem surveillance are representative application using sensor networks. But, limited battery capacity of sensor node is a key feature that determines lifetime of networks and system. It also affects quality of collected data. We recognized factors that affects lifetime of environment sensor nodes through the experiment of environment information system deployed over campus. We will show useful proposals for future construction of sensor network application systems.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.334-340
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• 2007

This paper introduces a prototype smart home environment that is built in the research building to demonstrate the feasibility of a robot-assisted future home environment. Localization, navigation, object recognition and handling are core functionalities that an intelligent service robot should provide. A huge amount of research effort has been made to make the service robot perform these functions with its own sensors, actuators and a knowledge base. With all complicated configuration of sensors, actuators and a database, the robot could only perform the given tasks in a predefined environment or show the limited capabilities in a natural environment. We started a smart home environment for service robots for simple service robots to provide reliable services by communicating with the environment through the wireless sensor networks. In this paper, we introduce various types of smart devices that are developed for assisting the robot in the environment by providing sensor and actuator capabilities. In addition, we present how the devices are integrated to constitute the smart home environment for service robots.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.221-230
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• 2016

With emerging the Internet of Things (IoT) paradigm, the sensor network and sensor platform technologies have been changed according to exploding amount of sensors. Sensor Registry System (SRS) as a sensor platform is a system that registers and manages sensor metadata for consistent semantic interpretation in heterogeneous sensor networks. However, the SRS is unsuitable for the IoT environment. Therefore, this paper proposes sensor registry data model to register and manager sensor information in the IoT environment. We analyze Semantic Sensor Network Ontology (SSNO) for improving the existed SRS, and design metamodel based on the analysis result. We also build tables in a relational database using the designed metamodel, then implement SRS as a web application. This paper applies the SSNO and sensor ontology examples with translating into the proposed model in order to verify the suitability of the proposed sensor registry data model. As the evaluation result, the proposed model shows abundant expression of semantics by comparison with existed models.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.42-48
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• 2011

It is very important for a mobile robot to recognize and model its environments for navigation. However, the grid map constructed by sonar sensors cannot accurately represent the environment, especially the narrow environment, due to the angular uncertainty of sonar data. Therefore, we propose a map building scheme which combines sonar sensors and IR sensors. The maps built by sonar sensors and IR sensors are combined with different weights which are determined by the degree of translational and rotational motion of a robot. To increase the effectiveness of sensor fusion, we also propose optimal sensor arrangement through various experiments. The experimental results show that the proposed method can represent the environment such as narrow corridor and open door more accurately than conventional sonar sensor-based map building methods.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.567-569
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• 2006

This study proposes the method to make a map of moving environment area and passed area by sensor using for recognizing environment or avoiding obstacle. We win develop an efficient algorithm to use sensors and get the data by the user friendly system. Through this system, we win study the way to know of the driving environment of moving robot on the long distance point. To this, we use only one ultra-sonic sensor with a servo motor which rotates 180 degree and loads an ultra-sonic sensor. A sensor can measure 1m${\sim}$8m range and a servo motor can distinguish 15 degree by 12 divide of 180 degree. By this feature of operating system, the robot which has these sensor module detects around of area and moves another point. In this way, users gather the data of detecting distance and change the data to X-Y coordinates. And users derive a map from these accumulate data.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.699-701
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• 1995

An input estimation technique is derived in multi-sensor environment. The proposed approach distribute the computational burden of input estimation to each local sensor and fusion center without loss of its optimality. The performances of proposed method in 2-sensor system are compared with those in single sensor system. Simulation results show that a reliable maneuvering target tracking system can be constructed in multi-sensor environment via proposed approach.