• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.400-403
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• 2021

As IoT technology becomes popular, more and more data is being generated, and the diversity of data is also increasing. In particular, in smart factory or Home IoT systems, data processing is very important because various data is collected and processed in real time through sensors. In this paper, we present a method for collecting, analyzing, and monitoring various data generated by sensors in IoT environment through Raspberry Pi. We also validate its usefulness by demonstrating that the above processed data can be operated in conjunction with smart mirror and mobile application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.425-426
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• 2021

Recently, there have been frequent incidents of talent accidents caused by youth driving without a license. Driving without a license is becoming a hotbed of curiosity and challenge for some young people, and there is a limit to managing smart keys at home to prevent this. Therefore, in this paper, using the facial recognition algorithm, the face of the driver sitting in the driver's seat is compared with the information stored in advance, and the system is designed to control the engine by determining that it is a registered driver. If the registered driver authentication is successful, the matching accuracy and Unlock message are output to the LCD connected to the Raspberry Pi.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.41-43
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• 2021

Robot Operating System (ROS) has been a prominent and successful framework used in robotics business and academia.. However, the framework has long been focused and limited to navigation of robots and manipulation of objects in the environment. This focus leaves out other important field such as speech recognition, vision abilities, etc. Our goal is to take advantage of ROS capacity to integrate additional libraries of programming functions aimed at real-time computer vision with a depth-image camera. In this paper we will focus on the implementation of an upgraded vision with the help of a depth camera which provides a high quality data for a much enhanced and accurate understanding of the environment. The varied data from the cameras are then incorporated in ROS communication structure for any potential use. For this particular case, the system will use OpenCV libraries to manipulate the data from the camera and provide a face-detection capabilities to the robot, while navigating an indoor environment. The whole system has been implemented and tested on the latest technologies of Turtlebot3 and Raspberry Pi4.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.481-483
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• 2023

본 논문에서는 다중 카메라환경에서의 안면인식 기반 영유아 활동 사진 자동 생성 시스템을 개발했다. 개발한 시스템은 어린이집에서 알림장 작성을 위한 촬영하는 동안 보육에 부주의하여 안전사고가 발생하는 것을 방지 할 수 있다. 시스템은 이동식 수집기와 분류 서버로 나뉘어 작동하게 된다. 이동식 수집기는 Raspberry Pi를 이용하였고 초당 1장 내외의 사진을 촬영하여 SAMBA를 사용 공유폴더에 저장한다. 분류 서버에서는 YOLOv5를 사용해 안면을 인식해 분류한다. OpenCV와 TensorFlow-Keras를 통해 분류된 사진에서의 표정을 파악하여 부모에게 전송할 웃는사진만을 분류하여 남겨둔다. 이외의 사진은 /dev/null로 이동하여 삭제된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.661-664
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• 2023

이 프로젝트의 목표는 공유 공간에서의 고객 이용 시간 관리를 향상하기 위해 라즈베리 파이와 센서 기술을 활용한 자동 시간 체크 시스템의 개발입니다. 이 시스템은 로드셀, 진동 감지 센서, 그리고 LiDAR 센서, 이 세 가지 센서를 활용해 의자에서 사용자의 존재 여부를 감지하고, 사람과 물건을 구별하며, 사용자가 의자에서 일어나는 시점을 파악합니다. 특히, 고객이 의자에 앉게 되면 시스템이 자동으로 시간을 체크하여 실시간으로 이용 시간을 측정하게 됩니다. 이렇게 수집된 정보는 웹 기반의 사용자 인터페이스를 통해 제공되어, 이용 시간 관리가 보다 편리해집니다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.327-334
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• 2024

In this paper, we developed a system with a near-infrared LED light source with a wavelength of 950nm to acquire palm vein images and a white LED light source to acquire palm creases based on Raspberry Pi. In addition, we implemented a unique pattern-extractable image processing technology that can prevent counterfeiting and enhance security of mixed creases and palmprints through image pre-processing (Gray scaling, Histogram Equalization, Blurring, Thresholding, Thinning) for the acquired vein and palm images, and secured a source technology that can be used in a security-enhanced system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2143-2148
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• 2016

Recently due to development of IT technology, ideas and technology that blend with environment have evolved. This technology can help people's living environment and in the future it is an essential component of the connected society. In this paper, we propose WiT(WiFI Trashcan) which takes advantage of the IT technology fusion and environmental factors at the same time to create a more pleasant environment. WiT provides a free WiFi when trash is disposed in the trash can. WiT detects whether a user disposes trash, determines the volume of the trash and provides free WiFi. To detect trash we use ultrasonic sensor and trash weight is measured by using weight sensor. Also by using Phython programming the measured sensor value is transmitted to Raspberry Pie and WiFi delivery time is determined. We used Arduino and Raspberry Pi to design and implement WiT.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.163-169
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• 2024

India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.

• 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.