• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.6-9
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• 2006

IEEE 802.15.4는 저전력 무선 개인 네트워크 기술의 표준으로서 USN(ubiquitous sensor network)의 핵심 무선 통신 기술로 각광을 받고 있다. 그러나 IEEE 802.15.4는 제한된 RF 전송범위와 스타 토폴로지를 기반으로 하는 통신 기법만을 제공하고 있으며, 인접한 PAN 간(inter-PAN)의 통신 기술은 정의되어 있지 않다. 이러한 기술상의 제약으로 IEEE 802.15.4는 통신 영역이 매우 제한적이며, 이에 따라 통신시 음영지역이 발생하는 문제점을 가지고 있다. 현재까지 통신영역 확장을 위한 주요 기술적 사항인 효율적인 토폴로지 형성방법, 주소할당 및 라우팅 방법, 인접 네트워크 간의 비콘 충돌 회피 기법 등에 대한 활발한 연구가 진행되어 왔다. 이중 인접한 네트워크간의 비콘 충돌 방지 기법은 IEEE 802.15.4의 네트워크가 비콘에 의해서 관리된다는 점을 고려하였을 때 데이터 전송 및 네트워크 유지를 위해 우선적으로 해결되어야 할 사항이다. 본 연구에서는 제안된 비콘 충돌 회피 기법을 분석하고, 이중 비활성 구간(inactive portion)을 활용한 기법에 대한 구체적인 구현 방안을 제시 하였다. 또한 상용 임베디드 장치인 Nano-24에 설계한 비콘 충돌 회피 기법을 구현하여 동작을 검증, 분석하였다.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.122-131
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• 2013

We address the problem of effective vehicular routing in hostile scenarios where malicious nodes intend to jeopardize the delivery of messages. Compromised vehicles can severely affect the performance of the network by a number of attacks, such as selectively dropping messages, manipulating them on the fly, and the likes. One of the best performing solutions that has been used in static wireless sensor networks to deal with these attacks is based on the concept of watchdog nodes (also known as guard nodes) that collaborate to continue the forwarding of data packets in case a malicious behavior in a neighbor node is detected. In this work, we consider the beacon-less routing algorithm for vehicular environments routing protocol, which has been previously shown to perform very well in vehicular networks, and analyze whether a similar solution would be feasible for vehicular environments. Our simulation results in an urban scenario show that watchdog nodes are able to avoid up to a 50% of packet drops across different network densities and for different number of attackers, without introducing a significant increase in terms of control overhead. However, the overall performance of the routing protocol is still far from optimal. Thus, in the case of vehicular networks, watchdog nodes alone are not able to completely alleviate these security threats.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.97-105
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• 2022

Human casualties from fires are increasing worldwide. The majority of human deaths occur during the evacuation process, as occupants panic and are unaware of the location of the fire and evacuation routes. Using an Internet of Things (IoT) sensor and reinforcement learning, we propose a method to find the safest evacuation route by considering the fire location, flame speed, occupant position, and walking conditions. The first step is detecting the fire with IoT-based devices. The second step is identifying the occupant's position via a beacon connected to the occupant's mobile phone. In the third step, the collected information, flame speed, and walking conditions are input into the reinforcement learning model to derive the optimal evacuation route. This study makes it possible to provide the safest evacuation route for individual occupants in real time. This study is expected to reduce human casualties caused by fires.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.280-286
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• 2022

In order to efficiently collect data, it is essential to locate the facilities and analyze the movement data. The current technology for location collection can collect data using a GPS sensor, but GPS has a strong straightness and low diffraction and reflectance, making it difficult for indoor positioning. In the case of indoor positioning, the location is determined by using wireless network technologies such as Wifi, but there is a problem with low accuracy as the error range reaches 20 to 30 m. In this paper, using BLE 4.2 built in Raspberry Pi, we implement Bluetooth Smart Ready. In detail, a beacon was produced for Advertise, and an experiment was conducted to support the serial port for data transmission/reception. In addition, advertise mode and connection mode were implemented at the same time, and a 3-count gradual algorithm and a quadrangular positioning algorithm were implemented for Bluetooth RSSI error correction. As a result of the experiment, the average error was improved compared to the first correction, and the error rate was also improved compared to before the correction, confirming that the error rate for position measurement was significantly improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.640-642
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• 2021

In order to collect a lot of data clearly and efficiently, it is essential to know the locations of the current facilities and analyze the movement data. The current location collection technology can collect data using a GPS (Global Positioning System) sensor, but in the case of GPS, it has strong straightness and low diffraction and reflectivity, making it difficult to position indoors. It is impossible to measure the distance between the server and the client because the signal sensitivity cannot be received. This paper implements an indoor positioning system using beacons and scanners in Raspberry Pi 3 B+. It controls Advertise Mode and Connection Mode at the same time using the scanner algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1248-1253
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• 2010

In this paper, the compensation algorithm for localization using the concept of equivalent distance rate(AEDR) in order to compensate ranging error in the SDS-TWR(Symmetric Double-Sided Two-Way Ranging) is proposed and the performance of the proposed algorithm is analyzed by the localization experiments. The ranging error of the SDS-TWR in the distance between mobile node and beacon node is measured to average 1m~8m by ranging experiments. But it is confirmed that the performance of the localization by the AEDR is better than that of the SDS-TWR 4 times in university auditorium and corridor, and the localization error of above 3~10m is reduced to average 2m and that of below 3m is reduced to average 1m respectively. It is concluded that the AEDR is superior to the NLOS(Non Line Of Sight) than LOS(Line Of Sight) in performance of ranging compensation for localization, and the AEDR is more helpful to localization systems practically considering the environment of sensor networks is under NLOS.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.305-307
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• 2012

무선 센서 네트워크에서 실시간 서비스는 중요한 이슈들 중 하나이다. 일반적으로, 기존의 연구는 이를 위해 비컨 (beacon)에 의존한다. 최근, 자원 제약적인 환경의 무선 센서 네트워크에서는 비컨으로 인한 제어 오버헤드 또한 부담이므로, 이를 극복하기 위한 비컨리스 라우팅이 제안되었다. 그러므로, 비컨리스 방안을 기반으로 한 실시간 통신이 활용 된다면 적은 에너지 소모로 환경적 제약에 유리하게 작용할 것이다. 그러나 이를 위해서는 새로운 도전에 직면한다. 전통적인 실시간 통신에서는, 요구 시간 안에 데이터를 전달하기 위해 각 노드들이 단일 홉 지연 시간을 파악하고 있어야 한다. 이 지연 시간은 비컨 메시지를 통한 이웃 노드 정보에 기반하여 파악되며, 이를 바탕으로 송신자가 적합한 다음 중계 노드를 선정한다. 그러나, 수신자 기반의 비컨리스 방안에서는 수신자가 스스로 다음 중계 노드를 결정하는 방식이기 때문에 기존의 송신자를 기준으로 한 지연 시간을 그대로 사용할 수 없다. 또한 비컨리스 라우팅을 위한 경쟁 지연 시간도 단일 홉 지연 시간에 포함되어야 한다. 따라서, 지연 시간 측정 원리가 새롭게 설계되어야 한다. 본 논문에서는 수신자 기반의 실시간 라우팅 방안을 제안한다. 제안 방안에서, 우리는 새로운 지연시간 측정 방법을 제시한다. 송신자로부터 수신자로의 단일 홉 지연 시간은 수신자에 의해 계산되어, 수신자는 실시간 제약 사항을 만족하는지 스스로가 결정할 수 있다. 시뮬레이션 결과를 통해 제안 방안이 비컨없이도 우수한 성능으로 실시간 서비스를 지원할 수 있음을 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5785-5804
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• 2019

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.719-729
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• 2017

Recently, the field of agriculture has been gaining a new leap with the integration of ICT technology in agriculture. In particular, smart farms, which incorporate the Internet of Things (IoT) technology in agriculture, are in the spotlight. Smart farm technology collects and analyzes information such as temperature and humidity of the environment where crops are cultivated in real time using sensors to automatically control the devices necessary for harvesting crops in the control device, Environment. Although smart farm technology is paying attention as if it can solve everything, most of the research focuses only on increasing crop yields. This paper focuses on the development of a system architecture that can harvest high quality crops at the optimum stage rather than increase crop yields. In this paper, we have developed an architecture using apple trees as a sample and used the color information and weight information to predict the harvest time of apple trees. The simple board that collects color information and weight information and transmits it to the server side uses Arduino and adopts model-driven development (MDD) as development methodology. We have developed an architecture to provide services to PC users in the form of Web and to provide Smart Phone users with services in the form of hybrid apps. We also developed an architecture that uses beacon technology to provide orchestration information to users in real time.