• Journal of Information Technology Services
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• v.16 no.2
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• pp.129-138
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• 2017

This paper is concerned with an Internet of Things (IoT)-based unmanned home-delivery box system, in which the system is developed with a prototype using a weight sensor, shock sensor, the Arduino and Raspberry-Pi of open-source hardware platforms. The developed system provides several functions such as a safe storage means, prevention of delivery-theft, and remote control of the home-delivery box, etc. Specifically, the system recognizes the arrival of goods by detecting the weight of deliveries and sends the arrived message of deliveries to the recipient' smartphone, and also controls (i.e., open and close) the locker of the unmanned home-delivery box system remotely with the smartphone. Furthermore, the developed system provides automatically a warning alarm around the unmanned home-delivery box when an external shock is applied to the home-delivery box, and sends a message on the shock to the recipient' smartphone. The major functions of the developed home-delivery box system have been verified in a realistic environment, and confirmed to work well. With the application of the developed home-delivery box system to the homes and offices where recipients are always not to stay, it is expected to significantly improve the safety of delivered goods as well as to effectively prevent the delivery operatives posing as a crime.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.651-653
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• 2015

Common Embedded boards like the Arduino, Raspberry Pi, BeagleBone Black, leverages smart home systems, machine tools and various products in our day to day life. Managing and dealing frequent large scale incidents involving recent reagents and hazardous materials can be dangerous and difficult to detect in advance like in an event of an accidents or fires. In this paper I have done research by utilizing an Embedded (BeagleBone Black) boards sensors and RFID management system to detect a hazardous situation like fire in real time and avoiding it by sending out an alert message to the admin user to minimizing the risk. This system provides immediate information to the administrator of any hazardous situation and prevents any accidents from occurring.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.51-57
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• 2017

Digital signage is becoming part of daily life across a wide range of visual advertisements segments market used in stations, hotels, retail stores, hotels, etc. The current digital signage system used in market is generally works on limited user interactivity with static contents. In this paper, a new approach is proposed using computer vision based dynamic audience adaptive cost-effective digital signage system. The proposed design uses the Camera attached Raspberry Pi Open source platform to employ the real-time audience interaction using computer vision algorithms to extract facial features of the audience. The real-time facial features are extracted using Haar Cascade algorithm which are used for audience gender specific rendering of dynamic digital signage content. The audience facial characterization using Haar Cascade is evaluated on the FERET database with 95% accuracy for gender classification. The proposed system, developed and evaluated with male and female audiences in real-life environments camera embedded raspberry pi with good level of accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.145-150
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• 2019

We develop the system realization of whale sound reconstruction by inverse MFCC algorithm with the weighted L2-norm minimization techniques. The output products from this research will contribute to the whale tourism and multimedia content industry by combining whale sound contents with the prototype of 3D printing. First of all, we develop the softwares for generating whale sounds and install them into Raspberry Pi hardware and fasten them inside a 3D printed whale. The languages used in the development of this system are the C++ for whale-sounding classification, MATLAB and Python for whale-sounding playback algorithm, and Rhino 6 for 3D printing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1252-1256
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• 2016

Internet of Things(IoT)-devices are now expanding inter-connecting networking technologies to invent healthcare monitoring system especially for assessing physiological conditions of the chronically-ill patients those with cardiovascular diseases. Hence, IoT system is expected to be utilized for home healthcare by dedicating the original usage of IoT devices to collect the biomedical data such as electrocardiogram(ECG) and photoplethysmography(PPG) signal. The aim of this work is to implement health monitoring system by integrating IoT devices with Raspberry-pi components to measure and analyze ECG and the multi-channel PPG signals. The acquired data and fiducial features from our system can be transmitted to mobile devices via wireless networking technology to support the concept of tele-monitoring services based on IoT devices.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.213-218
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• 2019

In this paper, we study autonomous navigation system for path guide system by using RFID that is enable to navigate and load in hotel. In case of a mobile robot used in a general autonomous navigation guidance system, a large amount of sensors are added to the system in order to improve the accuracy, resulting in cost problems. Therefore, to reduce the number of sensors, and to increase the accuracy and recognition rate, an autonomous driving guidance system was implemented using one of the inexpensive small micro controller units (MCU) such as Raspberry Pi3.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.527-532
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• 2021

In this paper, we propose an efficient finite field computation method for Rainbow algorithm, which is the only multivariate quadratic-equation based digital signature among the current US NIST PQC standardization Final List algorithms. Recently, Chou et al. proposed a new efficient implementation method for Rainbow on the Cortex-M4 environment. This paper proposes a new multiplication method over the finite field that can reduce the number of XOR operations by more than 13.7% compared to the Chou et al. method. In addition, a multiplicative inversion over that can be performed by a 4x4 matrix inverse instead of the table lookup method is presented. In addition, the performance is measured by porting the software to which the new method was applied onto RaspberryPI 3B+.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.509-515
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• 2022

As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1229-1236
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• 2022

In this paper, we studied accident-aware smart streetlights to prevent secondary accidents when driving on highways. It used Arduino and sensors to inform drivers of weather conditions, incorporated functions such as LED brightness control according to sunlight and night driving vehicles, and used Raspberry Pi camera OpenCV to learn various traffic accidents, natural disasters, and wildlife.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.61-67
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• 2022

The Internet of Things(IoT) is one of the key technologies in the Fourth Industrial Revolution. The IoT is a system that acquires information from various sensors and provides meaningful information to users. The method of obtaining information from sensor is using WIFI, Bluetooth and Server. is not accessible to external users because of different type of networks or local area communication. For this reason, there is a problem that external user cannot receive notification in regard to sensor information. In this paper, we want to establish a cloud message environment using Google's FCM(Firebase Cloud Messaging) and find out through experiments how users can receive notifications even if they are outside.