• International journal of advanced smart convergence
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• v.12 no.2
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• pp.173-181
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• 2023

Data collection is an essential element in the construction and operation of a smart factory. The quality of data collection is greatly influenced by network conditions, and existing wireless network systems for IoT inevitably lose data due to wireless signal strength. This data loss has contributed to increased system instability due to misinformation based on incorrect data. In this study, I designed a distributed MQTT IoT smart sensor and gateway structure that supports wireless multicasting for smooth sensor data collection. Through this, it was possible to derive significant results in the service latency and data loss rate of packets even in a wireless environment, unlike the MQTT QoS-based system. Therefore, through this study, it will be possible to implement a data collection management system optimized for the domestic smart factory manufacturing environment that can prevent data loss and delay due to abnormal data generation and minimize the input of management personnel.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.122-125
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• 2005

Data collection system is now widely used. This system is divided by embedded system and communication module. And data collection system in the remote area is using Satellite communication. So, data collection system is complicated and expensive. This paper proposes stabilization and cheapness of remote data collection system in dusty. The system can be composed simply through third party Satellite Communication programming of terminal including embedded system. Finally, collected data is transmitted to multi-user through web agent.

• Journal of Multimedia Information System
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• v.7 no.2
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• pp.137-140
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• 2020

In this paper, we propose a simplified tag collection algorithm to improve the performance of ISO / IEC 18000-7, the standard of active RFID systems. In the proposed algorithm, the collection command is modified to include the result of the listening period response from the previous round. The tag, which has received the collection command, checks whether the slot to which it has responded is collided, transmits additional data to its data slot without a point-to-point read command and sleep command, and transitions to the sleep mode. The collection round in the standard consists of a series of collection commands, collection responses, read commands, read responses, and sleep commands. On the other hand, in the proposed tag collection algorithm, one collection round consists only of a collection command and a collection response. As a result of performance analysis, it can be seen that the proposed technique shows superior performance compared to the standard.

• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.1 s.1
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• pp.91-102
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• 2001

This study aims to provide a program for the municipal solid waste collection and transportation management through data consolidation and field research of the materials about waste collection and transportation in a small city. The field research was conducted in the collection zone of the housing, apartment and business section within C city area. As a result, the main factor of collection and transportation plan required at the waste collection and transportation process and the central mean applying at the small city were calculated. The process that systemize the waste collection and transportation step and the expert system were constructed. In conclusion, the developed management system of the municipal solid waste collection and transportation can be wildly used by adding the data of other zone.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.479-488
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• 2022

In recent years, with the rapid development of machine learning technology, research utilizing machine learning has been actively conducted in fields such as cognition, reasoning and judgment, and action among various technologies constituting intelligent systems. In order to utilize this machine learning, it is indispensable to collect data for learning. However, the types of data generated vary according to the environment in which the data is generated, and the types and forms of data required are different depending on the learning model to be used for machine learning. Due to this, there is a problem that the existing data collection method cannot be reused in a new environment, and a specialized data collection module must be developed each time. In this paper, we propose a specification-based methology for data collection in artificial intelligence system to solve the above problems, ensure the reusability of the data collection method according to the data collection environment, and automate the implementation of the data collection function.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.121-128
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• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.31-48
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• 2023

The popularization of smart devices and subsequent optimization of their sensing capacity has resulted in a novel mobile crowdsensing (MCS) pattern, which employs smart devices as sensing nodes by recruiting users to develop a sensing network for multiple-task performance. This technique has garnered much scholarly interest in terms of sensing range, cost, and integration. The MCS is prevalent in various fields, including environmental monitoring, noise monitoring, and road monitoring. A complete MCS life cycle entails task allocation, data collection, and data aggregation. Regardless, specific drawbacks remain unresolved in this study despite extensive research on this life cycle. This article mainly summarizes single-task, multi-task allocation, and space-time multi-task allocation at the task allocation stage. Meanwhile, the quality, safety, and efficiency of data collection are discussed at the data collection stage. Edge computing, which provides a novel development idea to derive data from the MCS system, is also highlighted. Furthermore, data aggregation security and quality are summarized at the data aggregation stage. The novel development of multi-modal data aggregation is also outlined following the diversity of data obtained from MCS. Overall, this article summarizes the three aspects of the MCS life cycle, analyzes the issues underlying this study, and offers developmental directions for future scholars' reference.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.310-316
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• 2022

The smart tourism service provides services such as travel planning and tour guides to tourists using key technologies of the 4th industrial revolution, such as the Internet of Things, communication infrastructure, big data, artificial intelligence, AR/VR, and drones. We are developing smart tourism services such as recommended travel products, my travel itinerary, tourism information, and chatbots for tourists through the smart tourism app. In this paper, we develop a smart tourism service system that provides real-time location-based tourism information and weather information to tourists. The smart tourism service system consists of a smart tourism app, a smart tourism information system, and an IoT data collection device. The smart tourism information system receives weather information from the IoT data collection device installed in the tourist destination. The location-based smart tourism service is provided as a smart tourism app in the smart tourism information system according to the Beacon's UUID in the IoT data collection device. The smart tourism information system stores the Beacon's UUIDs received from tourists and provides a safe hiking service for tourists.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.956-961
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• 2009

When construction engineers perform their work in the jobsite, they have to record as-built conditions in the project log (Data Collection). On the other hand, the engineers often have to refer to the construction documents when necessary at the job faces (Data Access). The practice of Data Collection and Data Access in the jobsite can be greatly enhanced by utilizing mobile computing with wireless communications. In this paper, two cases of mobile computing applications for construction field management are presented; Mobile Specifications System and Mobile Data Collection System. The demonstration of the process for developing two mobile applications is the primary purpose of the paper. The problems and issues involved with adopting mobile computing for construction field are also presented. The simple information framework for mobile computing has been also proposed as an outcome of the research. As for development tools, readily available relational database and wireless network have been used. The use of commercial mobile broadband was examined for data communication where local area network is not available.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1170-1177
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• 2006

We apply VRP(Vehicle Routing Problem) to sludge collection system in this study. Sewage stores of villages are located in each village around a multipurpose dam. Sludge which is produced in sewage store of village is transported from the sewage store of village to the sewage treatment plants by the special purpose vehicle such as the tank lorry. In this paper, we propose sludge collection strategies which allocate each sewage store of village to sewage treatment plants and decide the schedule of sludge collection in order to collect sludge efficiently. The strategies aim to decrease transportation cost with deciding proposed vehicle routing and scheduling the sludge collection. When we decide route of vehicles, we consider the collection time in sewage store of village, distance between sewage store of villages and vehicle information as average velocity of vehicle, operation time of vehicle driver. We also develop the SCMS(Sludge Collection Management System) based on windows system with real data which is used in certain circumstance. And we experiment to figure out vehicle route and transportation cost throughout changing input data.