• International journal of advanced smart convergence
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• v.6 no.4
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• pp.50-55
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• 2017

Workers' demands for new applications, especially mobile applications, are increasing. Many industry analysts, researchers and corporate executives say the demand for mobile applications is becoming increasingly difficult to follow in the IT department. Gartner predicts that by 2021, the demand for mobile application development within the enterprise will increase about five times faster than IT can deliver applications. The purpose of this paper is to provide an environment where non-developers who are in charge of business development can develop apps and webs for their work. The basic concept of a new innovative App development tool, Smart Maker Authoring Tool is to develop Apps on the level using easy-to-learn Word or Excel in a computer. The main feature is that the app is developed by a non-developer worker. The coding technology is perfectly optimized to the structure and operation mechanism of the IT Infra such as hardware devices and operating system, which are the targets for implementing a desired function. Rather, it shows excellent software productivity. The most important feature of future business development is that it is developed by a non-developer worker. In this paper, we propose a no-code and low-code platform for non - developers to develop their business. In the future, we will link the IoT based Arduino system and artificial intelligent interpretation system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.257-270
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• 2022

In this paper, we design a smart factory risk improvement system and risk improvement method using AI edge devices. The smart factory risk improvement system collects, analyzes, prevents, and promptly responds to the worker's work performance process in the smart factory using AI edge devices, and can reduce the risk that may occur during work with improving the defect rate when workers perfom jobs. In particular, based on worker image information, worker biometric information, equipment operation information, and quality information of manufactured products, it is possible to set an abnormal risk condition, and it is possible to improve the risk so that the work is efficient and for the accurate performance. In addition, all data collected from cameras and IoT sensors inside the smart factory are processed by the AI edge device instead of all data being sent to the cloud, and only necessary data can be transmitted to the cloud, so the processing speed is fast and it has the advantage that security problems are low. Additionally, the use of AI edge devices has the advantage of reducing of data communication costs and the costs of data transmission bandwidth acquisition due to decrease of the amount of data transmission to the cloud.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.89-97
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• 2021

Voice interface can not only make daily life more convenient through artificial intelligence speakers but also improve the working environment of the factory. This paper presents a voice-assisted work management system that supports both speech and speaker recognition. This system is able to provide machine control and authorized worker authentication by voice at the same time. We applied two speech recognition methods, Google's Speech application programming interface (API) service, and DeepSpeech speech-to-text engine. For worker identification, the SincNet architecture for speaker recognition was adopted. We implemented a prototype of the work management system that provides voice control with 26 commands and identifies 100 workers by voice. Worker identification using our model was almost perfect, and the command recognition accuracy was 97.0% in Google API after post- processing and 92.0% in our DeepSpeech model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.497-500
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• 2018

As the fourth industrial revolution began to take off in earnest, the quality and quantity of data shared among devices began to increase exponentially over the network. In addition, the category of devices where people are exposed to such data has become diversified into desktops, mobile phones, smart phones, smart pads, and smart watches. As a result, the medium that contacts the data has begun to change, and the place where modern society has the most data is smart device. However, smart devices still leave much to be desired in terms of network speed and hardware specifications to handle large amounts of data at one time. Therefore, in this paper, we analyze the use of Service Worker, IndexedDB, and LocalStroage, which can retrieve a large amount of web contents more efficiently from mobile devices, and suggest ways to improve it.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.37-43
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• 2019

The existing smart farm technology has been systematized for the mass production rather than the consumer. There are many problems such as economical aspect to apply to actual rural environment due to aging. The purpose of this study is to apply smart farm technology based on the applicability of population aged in rural areas. Due to the heat wave, the crops in general greenhouse cultivation facilities suffered from damage such as sunlight damage. To minimize such damage, adjust the temperature and humidity environment or install a light-shielding film. However, the workers in the rural areas are aging and the elderly who are farming alone have a lot of difficulties in doing so. In the case of people with weak physical strength, there is a danger that they may lead to safety accidents when carrying heavy loads. In this paper, we propose 'Smart Palm capable of automatic transportation function', applying small smart vehicles that follow workers to existing smart farms to improve and prevent these problems. It is a smart farm that performs the control functions of the existing smart greenhouse environment, installs the rail for each trough, and has a vehicle that follows the worker. The smart app can directly control the greenhouse and the vehicle remotely manually.

• Fashion & Textile Research Journal
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• v.26 no.2
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• pp.218-226
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• 2024

In recent times, many accidents have occurred due to challenges in accurately identifying the location of workers, posing a significant societal concern demanding resolution. Therefore, it is essential to develop smart luminescent safety attire to enhance worker visibility in dim environments, thereby curbing accidents. In this study, we propose the utilization of textile-based OLED devices in creating smart luminescent safety clothing, aiming to augment the discernibility of workers over extended distances in low-luminance environments. In view of this, we engineered an attachable textile-based OLED module that balances high luminous efficiency with wearer comfort. Subsequently, a prototype smart luminescent safety clothing was demonstrated, and a performance evaluation was conducted to determine whether any discomfort occurred on wearing it. The fabricated OLED luminous module exhibited high luminance, thus validating the feasibility of creating smart luminescent attire with adequate brightness. Furthermore, there was no significant wearing stress observed, even after wearing it for more than 8 hours, and there was no impediment to various work-related movements. Through this research, we successfully demonstrated OLED based on smart luminescent safety clothing, which has the potential for wide-ranging applications across various industries and occupations, and is expected to play a crucial role in averting safety incidents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.24-30
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• 2021

In this study, an augmented reality (AR) app that detects the screw-assembly state of a car valve-body and assists the assembly work is developed and the effectiveness of the app is shown through testing. The app creates the contents indicating the screw-assembly position and order, and the screw-assembly state. Then, the contents are registrated onto the valve-body image on a smart-phone screen to be shown to the worker during assembly. To this end, the features are extracted from the 2D image of the valve-body and the location of the valve-body is tracked. By extracting the areas where the screws are to be assembled, and periodically determining the luminance of these areas, it is checked whether the screws are assembled in order at the predetermined position of the valve-body. When an error is detected during assembly, a warning sound is notified to the worker, and the worker can check the assembly state on the smart-phone screen and handle the error, immediately. Study results found that it takes about 65 ms to detect the assembly state of the five screws, and the assembly state is detected without error for 1 hour.

• Smart Media Journal
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• v.11 no.9
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• pp.30-38
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• 2022

It is important to grasp biometric data in real time for prompt action in the event of a safety accident at a work site where the risk of safety accidents exists. Among them, blood oxygen saturation is the most important factor in maintaining human life, so real-time oxygen saturation measurement and monitoring is necessary according to the situation as a preemptive response for worker safety management. By receiving real-time bio-signals from workers wearing health and life-risk protective clothing, and sharing and analyzing the worker's risk status in an external system, it is possible to diagnose the worker's current condition and efficiently respond to emergencies that may occur to the worker. In this paper, we propose a wearable oxygen saturation measurement platform technology that can monitor the risk of harmful gases and oxygen saturation of the wearer in real time and ensure the wearer's activity and safety in order to cope with emergency situations at the scene of an accident. If we overcome the limitations identified through the results of the proposed system later and apply improved biodata such as motion correction to the platform, we expect that it will be usable not only in hazardous gas environments, but also in hospitals and homes for emergency patients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.433-439
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• 2021

In this paper, we propose a method to implement an IoT-based sensor network for each workplace of a shipyard. Here, at the most common welding workplace in shipyards, the shipbuilding blocks are used as a communication medium to transmit information such as the worker's location, welding progress, and working hour to a server using LoRa and powerline communication. To achieve the data communication, inductive couplers and hybrid modems have been manufactured and installed on wire feeders and pin jigs to establish a sensor network. As a result of field test, the proposed system shows a success rate of data transmission and a rate of successful recognition of worker's location of about 98% or more. In addition, the process management system platform can record and display the work process data generated at the field in real time. The proposed system can be a starting point for enhancing the competitiveness of Korean shipbuilding industry through the establishment of a smart shipyard.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.1
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• pp.48-56
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• 2023

This paper implements many-to-many communication between users and develops a multi-functional smart helmet for worker protection and environmental safety in the shipbuilding and shipping industry. First, the communication situation is recorded in the field to perform signal processing for noise that interferes with communication. Then, it deals with the contents of developing smart helmets, data acquisition, algorithms, and simulations. The simulation results analyzed by applying the adaptive algorithm are shown, and their usefulness is confirmed. In conclusion, looking at the optimization process for the convergence factor of the Least Mean Square and Filtered-x Least Mean Square Adaptation Algorithm was possible. It is thought that it has laid the foundation for implementing many-to-many communication, the function of smart helmets that reduces or removes various noises at the shipyard in the future.