• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.371-379
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• 2009

Conventional sensor node operating systems do not support sensor abstraction for sensor applications. So, application programmers have to take charge of developing the hardware and the device drivers for the applications by themselves. In this paper, we present an as architecture to support sensor abstraction. The as provide not only application programmers with API library to access sensor devices, but also sensor developers with HAL library to access sensor hardware. This can reduce the development burden of application programmers significantly. In this paper, at first, we define the sensor HW interface to ease the attachment of sensors. Second, we describe the sensor access API for application programmers. Third, we define the HAL library for sensor device programmers to use. Finally, we show that the as can support sensor abstraction by illustrating the sample programs.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.177-184
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• 2009

Environmental monitoring systems are widely developed for analyzing environment and understanding an ecosystem according to the advance of wireless communication and various sensing techniques. To extract useful information, it requires high cost for processing a query, because these systems have to handle huge volume of raw sensor data which is transmitted from a wide area in environmental monitoring applications. Besides, it is also hard to answer an user defined query which requests to check current and near future condition. In this paper, we propose the monitoring system structure for processing a user defined query for environmental monitoring. It also describes the utilization of sensor data filtering and abstraction model. The designed abstraction model which is based on the slope grid in GIS supports fast data access and update. To analyze condition, the extracted data from abstraction model of each sensor type is combined in a query processor. It is useful to provide meaningful information to users.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.446-451
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• 2015

Recently, researches on sensor-based U-health applications that provide personal health information such as blood pressure, body temperature, and glucose, have actively been studied. The health information obtained via sensors, however, may have accuracy problems so that they can not be used unprocessed. This paper proposes a sensor abstraction layer for enhancing the accuracy of sensor readings from biomedical sensors that interact with smart phones. This layer recognizes sensor types and converts sensor readings into a form as specified in ISO/IEEE 11073 Personal Health Standard. When necessary, not only a filtering method that eliminates outlier values from sensor readings but also a summarization method that transforms them into more suitable forms, can also be applied. An android-based development board is used for the evaluation of proposed sensor abstraction layer. The results obtained by applying filtering and summarization show improved accuracy over unprocessed sensor readings of the body temperature and heartbeat sensors.

• 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.337-340
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• 2005

Context-awareness techniques in ubiquitous computing environment provide various services to users who need to get information via the analysis of collected information from sensors in a spatial area. Context-awareness has been increased in ubiquitous computing and is applied to many different applications such as disaster management system, intelligent robot system, transportation management system, shopping management system, and digital home service. Many researches have recently focused on services that provide the appropriate information, which are collected from Internet by different kinds of sensors, to users according to context of their surrounding environment. In this paper, we propose an abstraction model to manage the large-scale contextual information and their metadata which are collected from different kinds of in-situ sensors in a spatial area and are presented them on the web. This model is composed of the modules expressing functional elements of sensors using sensorML(Sensor Model Language) based on XML language and the modules managing contextual information, which is transmitted from the sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.94-96
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• 2022

Plug & Play techniques have been proposed in various ways to overcome the complexity of sensors/drivers in IoT application development. IEEE1451 standard abstracts sensors/drivers into a data structure called TEDS. As a result, characteristics of the sensor/driver are unnecessary when connecting the sensor/driver to the host device. The method proposed by ETRI is a format in which device drivers of sensors/drivers are dynamically loaded and connected to hosts, and there is no particular abstraction data structure. Both schemes are located at both ends in terms of the abstraction unit of the sensor/driver. We present the problem based on this fact, and what optimized methods can exist in the middle of it. In this paper, we analyze existing Plug&Play techniques. Also, we specify abstraction units of sensors/drivers, and analyze them.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.2
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• pp.72-80
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• 2009

In this parer, we propose a hardware abstraction architecture(HAA) for low cost flash memories that can be applicable to wireless sensor nodes. The proposed HAA consists of three layers. The three layers are 1) HHL(Hardware Interlace Layer), HAL(Hardware Adaption Layer), and HPL(Hardware Presentation Layer), where HIL provides a platform independent interlace to applications of upper layers, HAL performs hardware resource management, program status control, and generation of logical instructions as main core of the HAA, and HPL initializes hardware and communicates data between MCU and flash memory. We implemented our HAA on AT45DB flash memory, and the HAA used 4,384 bytes program memory and 195 bytes data memory respectively. Since the proposed HAA is composed of well defined three layers and shows a low utilization of memory, it can provides a high efficiency in terms of flexibility, scalability, and re-usability, and thus the HAA is well suited for wireless sensor nodes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2127-2133
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• 2010

In this paper, we proposed an architecture for supporting sensor transparency in sensor node operating systems, design the standard APIs (Application Programming Interfaces) and sensor device abstraction to provide the sensor transparency and implemented the sensor transparency in the TinyOS, the most well known sensor node operating system. With the proposed sensor node operating system which can support the sensor transparency, application developers can develop the target applications independent to each sensor device by using the standard APIs provided by the sensor node operating system and the sensor device manufacturers also can develop sensor device drivers by using the standard hardware interfaces and HAL (Hardware Adaptation Layer) interfaces independent to the specific hardware platform of sensor nodes.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.770-775
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• 2009

Along with the advance of USN technology in a human-oriented informatization society these days, society is quickly changing into a ubiquitous computing society in which information even between objects can be organically combined and utilized. In order to successfully build such a ubiquitous computing society, it is indispensable to have core USN technologies such as USN sensor nodes, sensor networks, USN middleware, and USN applied services that efficiently manage sensing information collected from sensor nodes, and support the abstraction function for the composition of sensor networks. In order to process the transmission event of sensing values that are generated from various USN terminal devices, this study designs a process that performs the abstraction of data for the efficient process of diverse sensing values transferred from USN and RFID terminal devices.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.281-285
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• 2008

Wireless sensor networks are closely related with the geometric environment in which they are deployed. We consider the probable case when a routing protocol runs on an environment with many complex obstacles like downtown surroundings. In addition, there are no unrealistic assumptions in order to increase practicality of the protocol. Our goal is to find a routing protocol for maximizing network lifetime by using only connectivity information in the complex sensor network environment. We propose a topology-based routing algorithm that accomplishes good performance in terms of network lifetime and routing complexity as measures. Our routing algorithm makes routing decision based on a weighted graph as topological abstraction of the complex network. The graph conduces to lifetime enhancement by giving alternative paths, distributing the skewed burden. An energy estimation method is used so as to maintain routing information without any additional cost. We show how our approach can be used to maximize network lifetime and by extensive simulation we prove that out approach gives good results in terms of both measures-network lifetime and routing complexity.