• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.143-151
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• 2016

In this paper, a real-time air quality monitoring system based on wireless network is designed and implemented for industrial park or multiuse facilities. The existing gas detector is high price and hard to apply the remote monitoring system. On the other hand, demand for air quality monitoring is increasing because of industrial gas accident, air pollution, and so on. In Korea, indoor air regulation was established by law. According to indoor air regulation, CO2, CO, and NO2 are important gases as the air quality standard. So we study the gas detector for indoor air quality and the wireless network system. The wireless network consist of sensor network and WCDMA to apply various place. To verify the performance of the implemented gas detector, the gas measurement experiment is performed in laboratory environment by using the realized gas detecting wireless sensor node. And we evaluate the experiment results.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.4
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• pp.260-273
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• 2007

The wireless sensor network (WSN) nodes are required to operate for several months with the limited system resource such as memory and power. The hardware platform of WSN has 128Kbyte program memory and 8Kbytes data memory. Also, WSN node is required to operate for several months with the two AA size batteries. The MAC, Network protocol, and small application must be operated in this WSN platform. We look around the problem of memory and power for WSN requirements. Then, we propose a new computing model of system software for WSN node. It is the Atomic Object Model (AOM) with Dual Priority Scheduling. For the verification of model, we design and implement IEEE 802.15.4 MAC protocol with the proposed model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1335-1343
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• 2009

This paper focuses on the implementation of hand held typeARM11 Platform for gas sensor based on Embedded Linux OS. The S3C6400, which is ARM11 architecture based, is the key component of the ARM11 Platform, Bluetooth is adapted to consist the network for the wireless transmission of environmental data between a sensor node and hand held type ARM11 Platform. Linux is ported to the Platform, QT/embedded is used for the application development.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.21-28
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• 2021

In this paper, a novel data transferring method is introduced that can transmit sensor data without using data bandwidth or an extra-processing cycle in a delay insensitive network. The proposed method uses human devices as Mules, does not disturb the device owner for permission, and saves energy while transferring sensor data to the collection hub in a wireless sensor network. This paper uses IP addressing technique as the data transferring mechanism by embedding the sensor data with the IP address of a Mule. The collection hub uses the ARP sequence method to extract the embedded data from the IP address. The proposed method follows WiFi standard in its every step and ends when data collection is over. Every step of the proposed method is discussed in detail with the help of figures in the paper.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.429-432
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• 2007

For smart structure technologies, the interests in wireless sensor networks for structural health monitoring are growing. The wireless sensor networks reduce the installation of the wire embedded in the whole structure and save the costs. But the wireless sensor networks have lots of limits and there are lots of researches and developments of wireless sensor and the network for data process. Most of the researches of wireless sensor network is applying to the civil engineering structure and the researches for the highrise building are required. And strain-based SHM gives the local damage information of the structures which acceleration-based SHM can not. In this paper, concept of wireless sensor network for structural health monitoring of highrise building is suggested. And verifying the feasibility of the strain-based SHM a strain sensor board has developed and tested by experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.479-482
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• 2003

We propose a real time gas monitoring system for classifying various gases with different concentrations. Using thermal modulation of operating temperature of two sensors, we extract patterns of gases from the voltage across the load resistance. We adopt the relative resistance as a pre-processing method and an ART2 neural network as a pattern recognition method. The proposed method has been implemented in a real time embedded system with tin oxide gas sensors, TGS 2611, 2602 and an MSP430 ultra-low power microcontroller in the test chamber.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.1-12
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• 2008

Home network is a technology that provides possibilities of monitoring/controling/mutilating-recognition between optional home network machines in residences. Currently, home network or other networks like entertainment, residential electronic networks are jumbled together with heterogeneous networks in a rampaging condition. In a reality of high expectation for home networks system like the mutual application for various machines, we are required to have the unification technology for conveniences to satisfy expectations. This thesis reflects how to develop Java applications or mutual products based on convenient interfaces actually that process various sensors which create real time data stream in Java platform through Java based sensor data-stream processing embedded middleware design and realization in real time.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.525-529
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• 2009

On the limited urban area meteorological data are hard to be collected because of the cost problem. The facilities collecting the data require high installment cost. Recently, the sensor network technique comes to the fore as a solution. Furthermore a mobile phone also becomes to be recognized as a sensor. This paper studies an application to service the meteorological map using mobile phone sensor. A design results for system implementation are introduced in this paper.

• ETRI Journal
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• v.30 no.1
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• pp.47-58
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• 2008

In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction-level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction-level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz-compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction-level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine-grained optimization of their software.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.4
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• pp.206-216
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• 2010

Wireless sensor networks (WSNs) are used to collect various data in environment monitoring applications. A spatial clustering may reduce energy consumption of data collection by partitioning the WSN into a set of spatial clusters with similar sensing data. For each cluster, only a few sensor nodes (samplers) report their sensing data to a base station (BS). The BS may predict the missed data of non-samplers using the spatial correlations between sensor nodes. ASAP is a representative data collection algorithm using the spatial clustering. It periodically reconstructs the entire network into new clusters to accommodate to the change of spatial correlations, which results in high message overhead. In this paper, we propose a new data collection algorithm, name EPDC (Energy-efficient Periodic Data Collection). Unlike ASAP, EPDC identifies a specific cluster consisting of many dissimilar sensor nodes. Then it reconstructs only the cluster into subclusters each of which includes strongly correlated sensor nodes. EPDC also tries to reduce the message overhead by incorporating a judicious probabilistic model transfer method. We evaluate the performance of EPDC and ASAP using a simulation model. The experiment results show that the performance improvement of EPDC is up to 84% compared to ASAP.