• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3357-3376
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• 2015

Wireless sensor network is an important research topic that has attracted a lot of attention in recent years. However, most of the interest has focused on wireless sensor network to gather scalar data such as temperature, humidity and vibration. Scalar data are insufficient for diverse applications such as video surveillance, target recognition and traffic monitoring. However, if we use camera sensors in wireless sensor network to collect video data which are vast in information, they can provide important visual information. Video sensor networks continue to gain interest due to their ability to collect video information for a wide range of applications in the past few years. However, how to efficiently store the massive data that reflect environmental state of different times in video sensor network and how to quickly search interested information from them are challenging issues in current research, especially when the sensor network environment is complicated. Therefore, in this paper, we propose a fast algorithm for extracting key frames from video and describe the design and implementation of key frame extraction and sharing in Android for wireless video sensor network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.161-162
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• 2018

In this paper, we consider the development the database configuration to the search and management of the object information from GPS sensor and video sensor. Also, the design that the object trace of the video sensor to recognized object would be considered.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.101-108
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• 2017

A wireless image sensor node collecting image data for environmental monitoring or surveillance requires a large amount of energy to transmit the huge amount of video data. Even though solar energy can be used to overcome the energy constraint, since the collected energy is also limited, an efficient energy management scheme for transmitting a large amount of video data is needed. In this paper, we propose a method to reduce the number of blackout nodes and increase the amount of gathered data by selecting an appropriate video coding method according to the energy condition of the node in a solar-powered wireless video sensor network. This scheme allocates the amount of energy that can be used over time in order to seamlessly collect data regardless of night or day, and selects a high compression coding method when the allocated energy is large and a low compression coding when the quota is low. Thereby, it reduces the blackout of the relay node and increases the amount of data obtained at the sink node by allowing the data to be transmitted continuously. Also, if the energy is lower than operating normaly, the frame rate is adjusted to prevent the energy exhaustion of nodes. Simulation results show that the proposed scheme suppresses the energy exhaustion of the relay node and collects more data than other schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1481-1498
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• 2014

Automated activity monitoring has become important in many applications. In particular, automated monitoring is an important issue in large-scale management of group-housed livestock because it can save a significant part of farm workers' time or minimize the damage caused by livestock problems. In this paper, we propose an automated solution for measuring the daily-life activities of pigs by using video data in order to manage the group-housed pigs. Especially, we focus on the circadian rhythm of group-housed pigs under windowless and 24-hour light-on conditions. Also, we derive a cost-effective solution within the acceptable range of quality for the activity monitoring application. From the experimental results with the video monitoring data obtained from two pig farms, we believe our method based on circadian rhythm can be applied for detecting management problems of group-housed pigs in a cost-effective way.

• Spatial Information Research
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• v.12 no.4 s.31
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• pp.351-370
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• 2004

At present, environmental monitoring of linear infrastructure is based mainly on field sampling. The 'integrated mapping' approach has received only limited attention from field scientists. The increased environmental regulation of corridor targets has required remote sensing research to develop a sensor or technique for targets ranging from 15 m to 100 m in swath width. In an attempt to identify the optimal remote sensing system for linear targets, an overview is provided of the application requirements and the technology currently available. The relative limitation of traditional remote sensing systems in such a linear application is briefly discussed. It is noted that airborne video could provide, in a cost-effective manner, information required for a very narrow and long strip target utilising the narrow view angle and dynamic stereo coverage. The value of this paper is warranted in proposing a new concept of video infrastructure monitoring as a future research direction in the recognition of sensor characteristics and limitations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.9-13
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• 2019

In this paper, IoT based thermal sensor data and image sensor integrated environmental monitoring system for ship, and it is the monitoring system which can process and transmit the Full HD IP camera image and thermal data transmitted from the thermal module for processing and transmitting, and the viewer S/W is to be developed which provides in real time the information for actual surrounding temperature together with the image, and enables fire prediction which was impossible in the case of the existing equipment by estimating the temperature change as the thermal image is added to the image camera, and saves and analyzes all data while receiving the temperature data and image signal transmitted from the integrated thermal sensor environmental monitoring equipment for ship and displaying them as 2D on the monitoring system.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.89-99
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• 2018

Due to global warming, various natural disasters such as floods and droughts are increasing. If we can detect the possibility of natural disasters in advance, we can prevent massive damages caused by natural disasters. Recent advances in visual sensor technologies have enabled remote monitoring of a variety of natural environments, including lakes, rivers, and shores. In this paper, we propose a method to segment an image obtained from video sensor networks into regions in order to monitor the environment effectively. In the proposed method, we first partition the image into superpixels and model the connections between superpixels as a graph. Then, initial seeds for each region are set by using the prior information, and the initial seeds are expanded to form regions using agglomerative clustering. Experimental results show that the proposed method extracts the regions from natural environment images easily and accurately.

• Journal of KIISE
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• v.41 no.12
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• pp.1152-1159
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• 2014

In this paper, we presents a system to ensure the safety of residents through appropriate action or alarm in case the residents occurs an emergency situation and abnormal activity. We collect and analysis real-time data of living environment of the residents using video and sensor. The existing system have been determined by using only the sensor data it have several problems. Our system attach camera to solve the existing system problem. We use weighted difference image and motion vector. The existing system, it takes about 48 hours to determine that an abnormal activity occurs. However, our system takes less than 1 hour.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.6
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• pp.761-769
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• 2012

In this paper, we propose a low-power design strategy to minimize energy-consumption for surveillance and reconnaissance sensor networks. The sensor network consists of many different nodes with various operations such as target detection, packet relay, video monitoring, changing protocols, and etc. Each sensor node consists of sensing, computing, communication, and power components. These components are integrated on a single or multiple boards. Therefore, the power consumption of each component can be different on various operation types. First, we identified the list of components and measured power consumption for them from the first prototype nodes. Next, we focus on which components are the main sources of energy consumption. We propose many energy-efficient approaches to reduce energy consumption for each operation type.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.396-403
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• 2000

A thermal imaging system is implemented for the measurement and the analysis of the thermal distribution of the target objects. The main part of the system is a thermal camera in which a focal plane array typed sensor is introduced. The sensor detects the mid-range infrared spectrum of target objects and then it outputs a generic video signal which should be processed to form a frame thermal image. Here, a digital signal processor(DSP) is applied for the high speed processing of the sensor signals. The DSP controls analog-to-digital converter, performs correction algorithms and outputs the frame thermal data to frame buffers. With the frame buffers can be generated a NTSC signal and transferred the frame data to personal computer(PC) for the analysis and a monitoring of the thermal scenes. By performing the signal processing functions in the DSP the overall system achieves a simple configuration. Several experimental results indicate the performance of the overall system.