• Convergence Security Journal
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• v.10 no.2
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• pp.11-17
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• 2010

Recent technological advances allow us to envision a future where large numbers of low-power, inexpensive sensor devices are densely embedded in the physical environment, operating together in a wireless network. This paper considers localization for mobile sensors; localization must be invoked periodically to enable the sensors to track their location. Localizing more frequently allows the sensors to more accurately track their location in the presence of mobility. In this paper, we test and analyze the accuracy of a moving node localization by Received Signal Strength (RSS).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.623-628
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• 2009

The emergence of compact and low-power wireless communication sensors and actuators in the technology supporting the ongoing miniaturization of processing and storage allows for entirely the new kinds of embedded systems. These systems are distributed and deployed in environments where they may have been designed into a particular control method, and are often very dynamic. Collection of devices can communicate to achieve a higher level of coordinated behavior. Wireless sensor nodes deposited in various places provide light, temperature, and activity measurements. Wireless sensor nodes attached to circuits or appliances sense the current or control the usage. Together they form a dynamic and multi-hop routing network connecting each node to more powerful networks and processing resources. Wireless sensor networks are a specific-application and therefore they have to involve both software and hardware. They also use protocols that relate to both applications and the wireless network. Wireless sensor networks are consumer devices supporting multimedia applications such as personal digital assistants, network computers, and mobile communication devices. Wireless sensor networks are becoming an important part of industrial and military applications. The characteristics of modem embedded systems are the capable of communicating adapting the different operating environments. In this paper, We designed and implemented sensor network system which shows through host PC sensing temperature and humidity data transmitted for wireless sensor nodes composed wireless temperature and humidity sensor and designs sensor nodes using embedded system with the intention of studying USN.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.3
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• pp.42-48
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• 2016

Extensive research effort has been made during the last decade to utilize wireless smart sensors for evaluating and monitoring structural integrity of civil engineering structures. The wireless smart sensor commonly has sensing and embedded computation capabilities as well as wireless communication that provide strong potential to overcome shortcomings of traditional wired sensor systems such as high equipment and installation cost. However, sensor malfunctioning particularly in case of long-term monitoring and unreliable wireless communication in harsh environment are the critical issues that should be properly tackled for a wider adoption of wireless smart sensors in practice. This study presents a wireless smart sensor network(WSSN) that can estimate unmeasured responses for the purpose of data recovery at unresponsive sensor nodes. A software program that runs on WSSN is developed to estimate the unmeasured responses from the measured using the Kalman filter. The performance of the developed network software is experimentally verified by estimating unmeasured acceleration responses using a simply-supported beam.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.323-334
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• 2014

In this paper, we proposed indoor positioning system with improved accuracy. The proposed indoor location measurement system is based pedestrian location measurement method that use the embedded sensor of smartphone. So, we do not need wireless external resources, such as GPS or WiFi signals. The conventional methods measure indoor location by generating a movement route of pedestrian by step and direction recognition. In this paper, to correct the direction sensor error, we use the common feature of the normal indoor floor map that the indoor path is lattice-structured. And we quantize moving directions depending on the direction of indoor path. In addition, we propose moving direction measuring method using geomagnetic sensor and gyro sensor to improve the accuracy. Also, the proposed step detection method uses angle and accelerometer sensors. The proposed step detection method is not affected by the posture of the smartphone. Direction errors caused by direction sensor error is corrected due to proposed moving direction measuring method. The proposed location error correction method corrects location error caused by step detection error without the need for external wireless signal resources.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5201-5206
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• 2014

A 'Light switch remote control' was made with an android smartphone and a smart light switch, which can use wireless communication on this paper. A smart light switch uses an embedded board and Bluetooth communication to receive and transmit data, and it receives and sends data again with a smartphone and wireless communication. This study used the flexibility of sensors that could be added later to utilize the embedded board as a gateway. This skill is being serviced now in a new apartment and building. On the other hand, existing households that do not support this skill can use it if they change only the switch. In conclusion, this system ensured user convenience and flexibility of system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.998-1013
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• 2013

Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.5
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• pp.423-443
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• 2009

We present the design and implementation of a unique sensing and actuation application -- the Illuminator: a sensor network-based intelligent light control system for entertainment and media production. Unlike most sensor network applications, which focus on sensing alone, a distinctive aspect of the Illuminator is that it closes the loop from light sensing to lighting control. We describe the Illuminator's design requirements, system architecture, algorithms, implementation and experimental results. The system uses the Illumimote, a multi-modal and high fidelity light sensor module well-suited for wireless sensor networks, to satisfy the high-performance light sensing requirements of entertainment and media production applications. The Illuminator system is a toolset to characterize the illumination profile of a deployed set of fixed position lights, generate desired lighting effects for moving targets (actors, scenic elements, etc.) based on user constraints expressed in a formal language, and to assist in the set up of lights to achieve the same illumination profile in multiple venues. After characterizing deployed lights, the Illuminator computes optimal light settings at run-time to achieve a user-specified actuation profile, using an optimization framework based on a genetic algorithm. Uniquely, it can use deployed sensors to incorporate changing ambient lighting conditions and moving targets into actuation. Experimental results demonstrate that the Illuminator handles various high-level user requirements and generates an optimal light actuation profile. These results suggest that the Illuminator system supports entertainment and media production applications.

• Smart Structures and Systems
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• v.10 no.3
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• pp.209-228
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• 2012

Structural health monitoring with wireless sensor networks has received much attention in recent years due to the ease of sensor installation and low deployment and maintenance costs. However, sensor network technology needs to solve numerous challenges in order to substitute conventional systems: large amounts of data, remote configuration of measurement parameters, on-site calibration of sensors and robust networking functionality for long-term deployments. We present a structural health monitoring network that addresses these challenges and is used in several deployments for monitoring of bridges and buildings. Our system supports a diverse set of sensors, a library of highly optimized processing algorithms and a lightweight solution to support a wide range of network runtime configurations. This allows flexible partitioning of the application between the sensor network and the backend software. We present an analysis of this partitioning and evaluate the performance of our system in three experimental network deployments on civil structures.

• ETRI Journal
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• v.36 no.5
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• pp.808-818
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• 2014

To deal with the major challenges of embedded sensor networks, we consider the use of magnetic fields as a means of reliably transferring both information and power to embedded sensors. We focus on a power allocation strategy for an orthogonal frequency-division multiplexing system to maximize the transferred power under the required information capacity and total available power constraints. First, we consider the case of a co-receiver, where information and power can be extracted from the same signal. In this case, we find an optimal power allocation (OPA) and provide the upper bound of achievable transferred power and capacity pairs. However, the exact calculation of the OPA is computationally complex. Thus, we propose a low-complexity power reallocation algorithm. For practical consideration, we consider the case of a separated receiver (where information and power are transferred separately through different resources) and propose two heuristic power allocation algorithms. Through simulations using the Agilent Advanced Design System and Ansoft High Frequency Structure Simulator, we validate the magnetic-inductive channel characteristic. In addition, we show the performances of the proposed algorithms by providing achievable ${\eta}$-C regions.

• Smart Structures and Systems
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• v.4 no.6
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• pp.759-777
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• 2008

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.