• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.362-367
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• 2018

A complementary metal oxide semiconductor (CMOS) binary image sensor is proposed for low-power and low-noise operation. The proposed binary image sensor has the advantages of reduced power consumption and fixed pattern noise (FPN). A gate/body-tied (GBT) p-channel metal-oxide-semiconductor field-effect transistor (PMOSFET)-type photodetector is used as the proposed CMOS binary image sensor. The GBT PMOSFET-type photodetector has a floating gate that amplifies the photocurrent generated by incident light. Therefore, the sensitivity of the GBT PMOSFET-type photodetector is higher than that of other photodetectors. The proposed CMOS binary image sensor consists of a pixel array with $394(H){\times}250(V)$ pixels, scanners, bias circuits, and column parallel readout circuits for binary image processing. The proposed CMOS binary image sensor was analyzed by simulation. Using the dynamic comparator, a power consumption reduction of approximately 99.7% was achieved, and this performance was verified by the simulation by comparing the results with those of a two-stage comparator. Also, it was confirmed using simulation that the FPN of the proposed CMOS binary image sensor was successfully reduced by use of the double sampling process.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.105-109
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• 2023

In this study, we present a power-efficient driving method for gas sensor systems based on the analysis of input signal characteristics. The analysis of the gas sensor output signal characteristics in the frequency domain shows that most of the signal portions are distributed in a relatively low frequency region when extracting the gas sensor signal, which can lead to further performance improvement of the gas sensor system. Therefore, the proposed gas signal extracting technique changes the operating frequency of the read-out circuit based on the frequency characteristics of the output signal of the gas sensor, resulting in a reduction of power consumption at the whole system level. The proposed sensing technique, which can be applied to a general-purpose commercial gas sensor system, was implemented in a printed circuit board (PCB) to verify its effectiveness at the commercial level.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.141-148
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• 2009

Wireless Sensor Networks (WSN) can be applied to various industry fields and environment analysis fields with the progress of various sensor technologies. Also WSN help automatically monitoring of sensor nodes installed at wide area. Especially, the tiny sensor nodes recently developed for the environment analysis require much more electronic power. The reasons are the measurable fields are departmentalized and the more detailed measuring fields are created by the development of various materials and applications. Furthermore, the sensor nodes operated by small batteries for the fields require low cost and low power consumption in wireless networks technology. The power efficiency is the most important factor for the WSN life time. Because the sensor nodes are installed at wide area and hard to recover. This paper proposes the WSN algorithm is applied sensor node that has low power consumption and efficiency measurement.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.131-135
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• 2011

In this paper, we describe the design and implementation of wireless smart plug having AC power sensor and intelligent standby power control algorithm for energy sensor network. The adaptive standby power control algorithm has function to apply different threshold of standby power by using learning algorithm depending on electric equipments. As using the proposed algorithm, user convenience will be more better and power consumption can be more reduced. The implemented prototypes of wireless smart plug and wireless access point were tested to verify the required functions and performance. As a result, we confirmed practicality of wireless smart power sensor and satisfaction of given design specifications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7B
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• pp.649-658
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• 2009

Due to limited size and limited battery lifetime of sensor node, one has to address the power saving issue in wireless sensor network. The existing power saving algorithm based on data reuse was proposed for the cluster structured wireless sensor network. We state the problem of existing power saving algorithm and propose new power saving algorithm for tree structured wireless sensor network. The proposed algorithm reduces power consumption by buffering the sensed data at the selected relay node for its data lifetime. The optimum buffering node is selected so that the power saving gain is maximized and at the same time, power consumption among sensor nodes are equally distributed in the network. With computer simulations, it is shown that the proposed algorithm outperforms the conventional algorithm in terms of power saving gain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.886-889
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• 2010

Power consumption measurement in sensor network is difficult to proceed by survey in real field. Thus, through simulation, the power consumption is estimated and replacement time of nodes are decided. A simulation tool simulates various facts such as power consumption, packet transmission traffic, network topology and etc. In this paper, it suggests sensor node power model to simulate power consumption which has large importance among simulation facts in sensor network. This model omits calculating expressions that the data originally surveyed can substitute with, according to power consumption property of each functions in sensor node in order to minimize calculations in simulation. In this case accuracy of power consumption estimation will be reduced, but can simulate it faster due to reduced calculation. Suggested model is fitted to analyze power consumption difference between two or more sensor network algorithms with rapid simulation speed rather than accurate simulation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.201-209
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• 2009

In power plant operations, sensor values often exhibit erroneous values due to their failures or the intrusions of various noises. However, most of the power plant monitoring and fault diagnosis systems perform their tasks based on the assumptions that the collected sensor values are correct all the times. These assumptions, which are not valid, often lead to serious consequences such as power plant trips. In this paper, we propose a power plant sensor value validation technique that can utilize the relationships existing among the sensor values as the sensor redundancy. The proposed technique is applied to the flow meters installed along boiler feed water systems of a typical tubular type boiler thermal power plant and shows a good potential of future applications.

• Smart Structures and Systems
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• v.17 no.4
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• pp.631-646
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• 2016

Although the deployment of wireless sensors for structural sensing and monitoring is becoming popular, supplying power to these sensors remains as a daunting task. To address this issue, there have been large volume of ongoing energy harvesting studies that aimed to find a way to scavenge energy from surrounding ambient energy sources such as vibration, light and heat. In this study, a magnetic resonance based wireless power transfer (MR-WPT) system is proposed so that sensors inside a concrete structure can be wirelessly powered by an external power source. MR-WPT system offers need-based active power transfer using an external power source, and allows wireless power transfer through 300-mm thick reinforced concrete with 21.34% and 17.29% transfer efficiency at distances of 450 mm and 500 mm, respectively. Because enough power to operate a typical wireless sensor can be instantaneously transferred using the proposed MR-WPT system, no additional energy storage devices such as rechargeable batteries or supercapacitors are required inside the wireless sensor, extending the expected life-span of the sensor.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.593-603
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• 2019

In wearable healthcare systems, sensor devices can be deployed in places around the human body such as the stomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensor batteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the human body. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensor devices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce battery energy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, such as sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energy consumption more than previous systems that only consider the sensor part. In this paper, we propose a new approach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energy management of sensor devices. Our proposed approach judges the current channel condition based on the values of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPL without communication to save the sensor's batteries. Otherwise, they find an optimal TPL. To compare performance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensor devices. Our experimental results show that our new algorithm is better than other TPC algorithms, such as linear, binary, hybrid, and ATPC.

• Economic and Environmental Geology
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• v.31 no.1
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• pp.53-57
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• 1998

Transient electromagnetic (TEM) method is also affected by cultural and natural electromagnetic (EM) noises, since it uses part of the broadband ($10^{-2}$ to $10^5Hz$) spectrum. Especially, predominant EM noise which affects a moving transmitter-receiver TEM system is sensor motion-induced noise. This noise is caused by the sensor motion in the earth magnetic field. The technique for reducing the sensor motion-induced EM noise presented in this paper is based on Halverson stacking. This Halverson stacking is generally used in a time-domain induced polarisation (IP) system to reject DC offset and linear drift. According to spectrum analysis of the vertical component of sensor motion-induced noise, the frequency range affected by the motion of an EM sensor is less than about 700 Hz in this study. With the decrease of the frequency, the spectral power caused by the motion of a sensor increases. For example, at the frequency of 200 Hz, the spectral power of the sensor motion-induced noise is $-90dBVrms^2$ while the spectral power of the EM noise measured with a fixed sensor on the ground is $-105dBVrms^2$, and at the frequency of 100 Hz, the spectral power of the sensor motion-induced noise is $-70dBVrms^2$ while the spectral power of the EM noise measured with a fixed sensor on the ground is $-105dBVrms^2$. With applying Halverson stacking to an artificial noise transient generated by adding a noise-free transient to sensor motion-induced noise measured without pulsing, it is shown that the filtered transient is nearly consistent with the noise-free transient within a delay time of $0.5{{\mu}sec}$. The inversion obtained from this filtered transient is in accord with the true model with an error of 5%.