• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.743-754
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• 2022

This paper contains the results of the development and performance evaluation of the environmental data monitoring system for the fish farm. For the hardware development, the analogue sensor is used to collect dissolved oxygen, pH, salinity, and temperature of the fish farm water, and the digital sensor is used for collecting ambient temperature, humidity, and location information via a GPS module to be sent to cloud-based Firebase DB. A set of LoRa transmitters and receivers is used as a communication module to upload the collected data. The data stored in Firebase is retrieved as a graph on a web and mobile application to monitor the environmental data changes in real-time. A notification will be delivered if the collected data is outside the determined optimal value. To evaluate the performance of the developed system, a response time from hardware modules to web and mobile applications is ranging from 6.2 to 6.85 seconds, which indicates satisfactory results.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.147-154
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• 2020

In this study, we created a system that can determine the number of vehicles entering and departing a charging station in real time for solving waiting time problems during refueling. Accordingly, we use the You Only Look Once object detection algorithm to detect and count the number of vehicles in the charging station and send the data to the Firebase Realtime Database. The result is shown using an Android application that provides a map function with the Kakao Maps API at the user interface side. Our system has an accuracy of 91% and an average response time of 3.1 s. Therefore, this system can be used by drivers to determine the availability of a charging station and to identify the charging station with the least waiting time for charging their vehicle.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.473-480
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• 2019

The smart home is a technology that can monitor and control by connecting everything to a communication network in various fields such as home appliances, energy consumers, and security devices. The Smart home is developing not only automatic control but also learning situation and user's taste and providing the result accordingly. This paper proposes a model that can provide a comfortable indoor environment control service for the user's characteristics by detecting the user's behavior as well as the automatic remote control service. The whole system consists of ESP 8266 with sensor and Wi-Fi, Firebase as a real-time database, and a smartphone application. This model is divided into functions such as learning mode when the home appliance is operated, learning control through learning results, and automatic ventilation using indoor and outdoor sensor values. The study used moving averages for temperature and humidity in the control of home appliances such as air conditioners, humidifiers and air purifiers. This system can provide higher quality service by analyzing and predicting user's characteristics through various machine learning and deep learning.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.67-76
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• 2023

COVID-19, which occurred in 2019, has a strong contagious power, has serious symptoms of infection and after-effects, and death in severe cases depending on the underlying disease and symptoms. As COVID-19 is highly contagious, in Korea, screening clinics have been set up across the country to determine whether or not to be positive for COVID-19 and isolate the infected to prevent the spread of COVID-19. However, there are cases where COVID-19 test applicants flock to screening clinics and cannot receive tests due to longer waiting times, and there is a risk that secondary infections may occur in the atmosphere. In this study, the reservation and notification system can be applied from the existing screening care system to solve spatial constraints, reducing waiting time with screening appointments, and solving population bottlenecks to screening clinics. Taking the COVID-19 pandemic as an experience, we propose a system that can present directions in future pandemic situations. To process real-time data, we use Google's Firebase to use Realtime Database in the cloud environment. Because a real-time database is used, users can check the status of screening clinics in real time through the app, make reservations, and receive notifications about test reservations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.374-380
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• 2022

This paper shows the results of a study that predicts changes in seawater conditions in sea farms using machine learning-based long short term memory (LSTM) algorithms. Hardware was implemented using dissolved oxygen, salinity, nitrogen ion concentration, and water temperature measurement sensors to collect seawater condition information from sea farms, and transferred to a cloud-based Firebase database using LoRa communication. Using the developed hardware, seawater condition information around fish farms in Tongyeong and Geoje was collected, and LSTM algorithms were applied to learning results using these actual datasets to obtain predictive results showing 87% accuracy. Flask and REST APIs were used to provide users with predictive results for each of the four parameters, including dissolved oxygen. These predictive results are expected to help fishermen reduce significant damage caused by fish group death by providing changes in sea conditions in advance.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.21-27
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• 2024

This paper presents the implementation of a personalized real-time information-providing application utilizing filtering and web crawling technologies. The implemented application performs web crawling based on the user-set keywords within web pages, using the Jsoup library as a basis for the selected keywords. The crawled data is then stored in a MySQL database. The stored data is presented to the user through an application implemented using Flutter. Additionally, mobile push notifications are provided using Firebase Cloud Messaging (FCM). Through these methods, users can efficiently obtain the desired information quickly. Furthermore, there is an expectation that this approach can be applied to the Internet of Things (IoT) where big data is generated, allowing users to receive only the information they need.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1317-1319
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• 2021

본 논문은 뉴미디어 시대의 새로운 온라인 독서 관리 시스템을 제안한다. 우리는 본 시스템을 사용자로 하여금 흥미로운 독서 취미 활동을 영위할 수 있도록 하는 것을 목표로 개발하였다. 아두이노에 무게센서, 조도센서, LCD 등을 부착한 스마트 북스탠드 '수북 홀더'와 이와 호환되는 안드로이드 OS 애플리케이션 '수북'을 설계하였다. 수북 홀더를 통해 수집된 사용자 독서 시간 데이터와 사용자 기록 데이터를 활용하여 저장 및 분석하고, Firebase Database 내에 관리한다. 본 논문의 시스템은 사용자의 좋은 독서 습관 형성에 도움을 주고 같은 취미를 가진 사람들 간 시공간적 제약 없이 소통할 수 있는 플랫폼을 제공한다.