• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권3호
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• pp.857-872
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• 2014

Recent researches reveal that great benefit can be achieved for data gathering in wireless sensor networks (WSNs) by employing mobile data collectors. In order to balance the energy consumption at sensor nodes and prolong the network lifetime, a multi-track large-scale mobile data collection mechanism (MTDCM) is proposed in this paper. MTDCM is composed of two phases: the Energy-balance Phase and the Data Collection Phase. In this mechanism, the energy-balance trajectories, the sleep-wakeup strategy and the data collection algorithm are determined. Theoretical analysis and performance simulations indicate that MTDCM is an energy efficient mechanism. It has prominent features on balancing the energy consumption and prolonging the network lifetime.

• Journal of Multimedia Information System
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• 제7권2호
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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.

• 디지털산업정보학회논문지
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• 제16권1호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.5805-5825
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• 2019

Smartphones are important platforms because of their sophisticated computation, communication, and sensing capabilities, which enable a variety of applications in the Internet of Things (IoT) systems. Moreover, advancements in hardware have enabled sensors on smartphones such as environmental and chemical sensors that make sensor data collection readily accessible for a wide range of applications. However, dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users that vary throughout the day, which greatly affects the efficacy of sensor data collection. Therefore, it is necessary to consider phone users mobility patterns to design data collection schedules that can reduce the loss of sensor data. In this paper, we propose a mobility-based weighted adaptive opportunistic scheduling framework that can adaptively adjust to the dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users and provide prioritized scheduling based on various application scenarios, such as velocity, region of interest, and sensor type. The performance of the proposed framework is compared with other scheduling frameworks in various heterogeneous smartphone user mobility scenarios. Simulation results show that the proposed scheduling improves the transmission rate by 8 percent and can also improve the collection of higher-priority sensor data compared with other scheduling approaches.

• International Journal of Computer Science & Network Security
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• 제23권3호
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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 smart convergence
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• 제12권2호
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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.

• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.43-49
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• 2019

Today, with the development of the internet of things, wearable devices related to personal health care have become widespread. Various global information and communication technology companies are developing various wearable health devices, which can collect personal health information such as heart rate, steps, and calories, using sensors built into the device. However, since individual health data includes sensitive information, the collection of irrelevant health data can lead to personal privacy issue. Therefore, there is a growing need to develop technology for collecting sensitive health data from wearable health devices, while preserving privacy. In recent years, local differential privacy (LDP), which enables sensitive data collection while preserving privacy, has attracted much attention. In this paper, we develop a technology for collecting vast amount of health data from a smartwatch device, which is one of popular wearable health devices, using local difference privacy. Experiment results with real data show that the proposed method is able to effectively collect sensitive health data from smartwatch users, while preserving privacy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3501-3518
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• 2020

The method of DNS data collection is one of the most important parts of DNS simulation. DNS data contains a lot of information. When it comes to analyzing the DNS security issues by simulation on the cyber range with customized features, we only need some of them, such as IP address, domain name information, etc. Therefore, the data we need are supposed to be light-weighted and easy to manipulate. Many researchers have designed different schemes to obtain their datasets, such as LDplayer and Thales system. However, existing solutions consume excessive computational resources, which are not necessary for DNS security simulation. In this paper, we propose a light-weighted active data collection method to prepare the datasets for DNS simulation on cyber range. We evaluate the performance of the method and prove that it can collect DNS data in a short time and store the collected data at a lower storage cost. In addition, we give two examples to illustrate how our method can be used in a variety of applications.

• 창의정보문화연구
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• 제7권4호
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• pp.265-277
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• 2021

인공지능 기술의 핵심은 데이터다. 기술의 발달로 데이터의 양이 이전보다 폭발적으로 증가하면서 인공지능 기술 또한 빠르게 발전하고 있다. 하지만 인공지능 교육에 대한 높은 관심에 비해 인공지능과 연계된 데이터 교육 연구는 아직 부족하다. 기존의 인공지능 데이터 교육의 사례 분석 결과, 데이터 과학의 과정 및 일부를 교육하는 사례를 확인할 수 있었으나, 데이터 수집과 관련된 연구는 많지 않았다. 피지컬 컴퓨팅 교구의 활용이 초등학생의 인공지능 교육에 긍정적인 영향을 줄 것이라는 연구와 함께 피지컬 도구를 활용한 데이터 수집 사례를 연구하였으나, 데이터 수집과 관련한 연구 사례 또한 드물었다. 따라서 본 연구에서는 피지컬 도구를 활용한 효율적인 데이터 수집 방법을 설계하였다. 모듈형 피지컬 컴퓨팅 교구인 코블S를 활용하여 데이터 수집 프로그램의 구조도를 만들고 서비스 측면과 사용자 측면의 프로그램 화면의 예시를 구성하였다. 본 연구는 설계 측면의 제안으로 향후 프로그램 제작 및 프로그램과 연동하여 사용할 수 있는 인공지능 교육 플랫폼 구축이 되어야 한다는 점에서 제한점이 있다.

• 한국방재학회 논문집
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• 제1권1호
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• pp.91-102
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• 2001

본 연구에서는 체계화되지 못한 중소도시의 쓰레기 수집 수송의 자료를 정리, 현장 조사를 통한 쓰레기 수집 수송 관리를 위한 프로그램을 작성하였다. 대상은 C시로 하였으며, 수집구역을 주택, 아파트, 상가지역으로 한정지어 현장 조사를 실시하였고, 폐기물 관리 프로그램을 작성하였다. 연구 결과는 쓰레기 수집 수송단계의 필요한 인자와 중소도시에 적용 가능한 평균 값을 도출하였고, 중소도시의 쓰레기 수집 수송단계를 체계화하는 단계와 expert system을 구축하였다. 또한, Visual Basic을 이용한 쓰레기 수집 수송 관리 프로그램을 개발하였다. 결과적으로 본 연구로 개발되어진 도시폐기물의 수집 수송 관리 시스템은 다른 지역의 현장 Data를 추가함으로서 광범위하게 이용될 수 있을 것이다.