• International conference on construction engineering and project management
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• 2011.02a
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• pp.17-22
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• 2011

A considerable number of construction disasters occur on pathways. Safety management is usually performed on construction sites to prevent accidents in activity areas. This means that the safety management level of hazards on pathways is relatively minimized. Many researchers have noted that hazard identification is fundamental to safety management. Thus, algorithms for helping safety managers to identify hazardous areas are developed using automated data collection technology. These algorithms primarily search for potential hazardous areas by comparing workers' location logs based on a real-time location system and optimal routes based on BIM. Potential hazardous areas are filtered by identified hazardous areas and activity areas. After that, safety managers are provided with information about potential hazardous areas and can establish proper safety countermeasures. This can help to improve safety on construction sites.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1189-1204
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• 2018

Detecting and capturing 3D human structures from the intensity-based image sequences is an inherently arguable problem, which attracted attention of several researchers especially in real-time activity recognition (Real-AR). These Real-AR systems have been significantly enhanced by using depth intensity sensors that gives maximum information, in spite of the fact that conventional Real-AR systems are using RGB video sensors. This study proposed a depth-based routine-logging Real-AR system to identify the daily human activity routines and to make these surroundings an intelligent living space. Our real-time routine-logging Real-AR system is categorized into two categories. The data collection with the use of a depth camera, feature extraction based on joint information and training/recognition of each activity. In-addition, the recognition mechanism locates, and pinpoints the learned activities and induces routine-logs. The evaluation applied on the depth datasets (self-annotated and MSRAction3D datasets) demonstrated that proposed system can achieve better recognition rates and robust as compare to state-of-the-art methods. Our Real-AR should be feasibly accessible and permanently used in behavior monitoring applications, humanoid-robot systems and e-medical therapy systems.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.91-98
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• 2016

We propose a method to train a model that can predict the probability of a crime being committed. CCTV data by matching criminal events are required to train the crime prediction model. However, collecting CCTV data appropriate for training is difficult. Thus, we collected actual criminal records and converted them to an appropriate format using variables by considering a crime prediction environment and the availability of real-time data collection from CCTV. In addition, we identified new specific crime types according to the characteristics of criminal events and trained and tested the prediction model by applying neural network partial least squares for each crime type. Results show a level of predictive accuracy sufficiently significant to demonstrate the applicability of CCTV to real-time crime prediction.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.21-27
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• 2019

Recently, embedded systems have been introduced in various fields such as smart factories, industrial drones, and medical robots. Since sensor data collection and IoT functions for machine learning and big data processing are essential in embedded systems, it is essential to port the operating system that is suitable for the function requirements. However, in embedded systems, it is necessary to separate the hard real-time system, which must process within a fixed time according to service characteristics, and the flexible real-time system, which is more flexible in processing time. It is difficult to port the operating system to a low-performance embedded device such as 8BIT MCU to perform simultaneous real-time. When porting a real-time OS (RTOS) to a low-specification MCU and performing a number of tasks, the performance of the real-time and general processing greatly deteriorates, causing a problem of re-designing the hardware and software if a hard real-time system is required for an operating system ported to a low-performance MCU such as an 8BIT MCU. Research on the technology that can process real-time processing system requirements on RTOS (ported in low-performance MCU) is needed.

• Journal of Internet Computing and Services
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• v.4 no.6
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• pp.1-11
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• 2003

This paper is introduced about Design driven testing, for real time system, based on use case approaches, We focuses on a part of an extended use case approach for real time software development, which partitions design schema into layered design component architecture of functional components called "design component", We developed a use case action matrix to contain a collection of related scenarios each describing a specific variant of an executable sequence of use case action units, which reflected the behavioral properties of the real time system design, in this paper, we attempt to apply real time system with design driven testing with test plan metrics which is introduced which produces an ordering of this scenario set to enhance productivity and both promote and capitalize on test case reusability of existing scenarios.scenarios.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.472-476
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• 2010

Nowadays, as the indices of the major search engines grow to a tremendous proportion, vertical search services can help customers to find what they need. Real time search is valuable because it lets you know what's happening right now on any given topic. In this paper, we designed a new architecture to implement a high performance real time search system. Based on the real time search's characters, we divided the whole system to two parts which are collection system and search system. The evaluation results showed that our design has the potential to provide the real time search transparent scalability while maintaining the replication overhead costs in check.

• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.42-52
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• 1998

This paper proposes an extended TCP/IP protocol, LAN/TCP, that can be used for the distributed soft real-time systems connected through the Ethernet-based local area network. Since LAN/TCP shows soft real-time performance with keeping compatibility and interoperability with the standard TCP/IP, the existing application software can be used without any modification. LAN/TCP also provides the periodic transmission mode(PTM) with which the periodical data collection and updating the control signals can be efficiently implemented with relatively small traffic overhead. This paper includes the computer simulation and experimental results of the proposed protocol.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.33-39
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• 2020

A smart grid is a next-generation power grid that can improve energy efficiency by applying information and communication technology to the general power grid. The smart grid makes it possible to exchange information about electricity production and consumption between electricity providers and consumers in real-time. Advanced metering infrastructure (AMI) is the core technology of the smart grid. The AMI provides two-way communication by installing a modem in an existing digital meter and typically include smart meters, data collection units, and meter data management systems. Because the AMI requires data collection units to control multiple smart meters, it is essential to ensure network availability under heavy network loads. If the load on the work done by the data collection unit is high, it is necessary to allocation new data collection units to ensure availability and improve energy efficiency. In this paper, we discuss the allocation scheme of data collection units for the energy efficiency of the AMI.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.159-166
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• 2018

This paper introduces a manufacturing facility visualization system for the monitoring of smart factories. With the development of technology and the emergence of such terms as the Fourth Industrial Revolution and Industry 4.0, technologies for smart factories are becoming more important. A Manufacturing Execution System that can improve productivity and help decision making by monitoring production plants in real-time is one of the key technologies for smart factories. The application of digital twin technology for more accurate monitoring technology is also an important issue. However, digital twin implementations require an integrated infrastructure that can integrate facility data from multiple manufacturers. Therefore, this paper designs and develops a visualization program that can verify real-time information of facilities using data collection system based on international standard protocol for heterogeneous collection and monitoring of facility data. This allows a factory to consolidate equipment data from multiple manufacturers and to view them in real-time.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.216-221
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• 2022

The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.