• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.173-178
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• 2019

Recently, the types and amount of data generated, collected, and measured in IoT such as smart home, security, and factory are increasing. The technologies for IoT service include sensor devices to measure desired data, embedded software to control the devices such as signal processing, wireless network protocol to transmit and receive the measured data, and big data and AI-based analysis. In this paper, we focused on developing a gateway for interfacing heterogeneous sensor network protocols that are used in various IoT devices and propose a heterogeneous network interface IoT gateway. We utilized a OpenWrt-based wireless routers and used 6LoWAN stack for IP-based communication via BLE and IEEE 802.15.4 adapters. We developed a software to convert Z-Wave and LoRa packets into IP packet using our Python-based middleware. We expect the IoT gateway to be used as an effective device for collecting IoT big data.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.321-326
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• 2021

Wireless communication is a core technology constituting the Internet of Things (IoT), but there is no suitable educational equipment to learn various wireless communication technologies used in the Internet of Things through practice. This paper deals with the development of advanced education and training equipment that can perform various IoT wireless communication practices. It uses an Arduino mega board as a device to control various sensors. As wireless network technologies to send and receive the sensing date wirelessly, it makes use of RFID/NFC and Bluetooth among WPAN technologies, WiFi among WLAN technologies and LoRa and 2.4GHz wireless transceiver among WWAN technologies. In addition, GPS, infrared communication, I2C communication, and SPI communication are organized so that various IoT wireless communication technologies can be learned through practice. In addition, since the educational equipment developed in this paper is equipped with two devices, it is designed to perform transmission and reception experiments for wireless network technology within the equipment.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.485-489
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• 2018

For the construction of smart factory that are part of the Fourth Industrial Revolution, data from the production environments and production machines should be collected, analyzed, and feedback should be given to predict when failures take place or parts should be replaced. For this purpose, a system that monitors the production environments and the status of the production machines are required. In this paper, the monitoring system for mobile devices and PC is implemented by collecting environmental data from production sites and sensor data of production machine using LoRa, a low-power wireless communication technology. On the mobile devices, production environments and vibration data can be displayed in real time. In PC monitoring program, sensor data can be displayed graphically to check standard deviation and data variation. The implemented system is used to collect data such as temperature, humidity, and atmospheric pressure of the production environment, and vibration data of production machines.

• Journal of Platform Technology
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• v.9 no.1
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• pp.32-39
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• 2021

Existing environmental measuring devices mainly focus on electromagnetic wave and eco-friendly product certification and durability test, and sensor reliability verification and verification of measurement data are conducted mainly through sensor performance evaluation through type approval and registration, acceptance test, initial calibration, and periodic test. This platform has established an ICT-based environmental monitoring sensor reliability verification system that supports not only performance evaluation for each target sensor, but also a verification system for sensor data reliability. A sensor board to collect sensor data for environmental information was produced, and a sensor and data reliability evaluation and verification service system was standardized. In addition, to evaluate and verify the reliability of sensor data based on ICT, a sensor data platform monitoring prototype using LoRa communication was produced, and the test was conducted in smart cities. To analyze the data received through the system, an optimization algorithm was developed using machine learning. Through this, a sensor big data analysis system is established for reliability verification, and the foundation for an integrated evaluation and verification system is provide.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.591-593
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• 2019

LPWA has a small amount of data that can be transmitted at one time, but it can collect a very wide range of information, so it is suitable for gathering information of apartment meter or collecting data intermittently sent from industrial site. However, most of the application studies on LPWA are limited to outdoor, especially LOS environment, so it is difficult to collect information for application to apartment and industrial sites. In this paper, we have measured the communication coverage within the building, which is a NLOS environment, so that LPWA communication can be applied to apartments and industrial sites. For the experiment, LoRa module was created using sx1276, Class A was applied, and the spread factor was changed for each layer. As a result, in case of spreading factor 7 that shows increasing error and losses from the 7 floor, but the in case of spreading factor 12, the data could be seamlessly received even on the 9th floor without error and losses.

• 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 IKEEE
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• v.27 no.3
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• pp.225-233
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• 2023

This paper implements a system that monitors human body lifting information in the event of a marine accident. The monitoring system performs ultrasonic communication through a lifting device controller that transmits underwater environment information, and LoRa communication is performed on the water to provide GPS information within 10 km to the control center or mother ship. The underwater lifting controller transmits pneumatic sensor, gyro sensor, and temperature sensor information. In an environment where the underwater conditions increase by one atmosphere of water pressure every 10m in depth, and the amount of air in the instrument decreases by half compared to land, a model of a 60kg underwater mannequin is used. Using one 38g CO2 cartridge in the lifting appliance SMB(Surface Maker Buoy), carry out a lifting appliance discharge test based on the water level rise conditions within 10 sec. Underwater communication constitutes a data transmission environment using a 2,400-bps ultrasonic sensor from a depth of 40m to 100m. The monitoring signal aims to ensure the safety and safe human structure of the salvage worker by providing water depth, water temperature, and directional angle to rescue workers on the surface of the water.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.525-530
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• 2024

The need for an environmental monitoring system that obtains and provides environmental information in real time is increasing. In particular, in the case of water quality management in public waters, regular management must be conducted through manual and automatic measurement by law, and air pollution also requires regular measurement and management to reduce fine dust and exhaust gas in connection with the realization of carbon neutrality. In this study, we implemented a system that can measure and monitor water pollution and air pollution information in real time. A hovercraft capable of moving on land and water simultaneously was used as a measurement tool. Water quality measurement and air pollution measurement sensors were installed on the hovercraft body, and a communication module was installed to transmit the information to the monitoring system in real time. The structure of a hovercraft for environmental measurement was designed, and a LoRa module capable of low-power, long-distance communication was applied as a real-time information transmission communication module. The operational performance of the proposed system was confirmed through actual hardware implementation.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.27-32
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• 2018

Nowadays, to prevent electrical accidents in Korea, inspectors directly performed checking general electrical facilities as a cycle from every one to three years. It is difficult to presuppose an omen because intact conditions of electrical equipments are not kept at the time of inspection. In this paper, in order to ensure effectiveness of an online basis electric inspection, we developed an electrical safety IoT system using LoRa communication technology to enable monitoring mainly electrical safety components such as overcurrent, overvoltage, resistive leakage current, and power. Then we proposed a method for verifying performances of the prosed electrical safety IoT system. Resistive leakage currents are calculated by using difference of phase between voltages and currents. We verified that average errors are 0.97%, which reference goal is ${\pm}5%$ for a device, through reliability test according to conditions. Results of this research can be used as basic study materials to develop technologies for measuring three phase leakage current and for implementing public electrical safety. platform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.178-180
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• 2021

In this paper, we design a system to monitor environmental data in fish farms in real-time and provide machine learning-based prediction services to prevent damage on fish farms caused by changes in the sea environment. The proposed system will install an IoT device module consisting of sensors that can measure hydrogen concentration, salinity, dissolved oxygen, and water temperature, which can be transferred to Cloud DB using LTE or LoRa communication technology and then monitor the real-time condition through a web or mobile application. In addition, it has a function to prepare for changes within the environment of fish farms by applying machine learning-based prediction technology using collected data.