• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.29-35
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• 2023

Braille can be said to be an essential means used for the visually impaired to communicate or acquire information on visual materials in their lives. However, the rate of interpretation of braille among the visually impaired is insignificant at 5%. As a result, libraries for the visually impaired produce various types of materials that can obtain various information for the visually impaired and also have assistive technology equipment to interpret them. However, the publication rate of Braille books is too low to purchase and interpret Braille books. In addition, the Braille interpretation rate is too low, and the purchase of assistive technology devices is too expensive and slow. Therefore, in this paper, we implemented a system that displays Braille using Arduino to help visually impaired people in addition to the existing methods they use to obtain information. For Braille display, Korean data is transmitted from Python through serial communication between Python and Arduino, and Arduino, which receives the data, compares the Korean data with the data in the array in the program and retrieves the Braille values of the Korean data. Here, the Braille value was expressed by controlling the servo motor perpendicular or horizontal to the body using white and black circles based on the Braille list.

• Journal of Internet of Things and Convergence
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• v.7 no.3
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• pp.9-14
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• 2021

This paper discovers the energy loss factors through the insulation diagnosis of houses or buildings, and proposes directions for energy efficiency improvement. The energy efficiency factor of a building consists of insulation diagnosis, thermal bridge diagnosis, window diagnosis, airtight diagnosis, and equipment diagnosis. Among the residents and facilities in the energy welfare blind spot, an energy efficiency diagnosis was conducted for one senior citizen building located in Naju-si, Jeollanam-do, and energy efficiency diagnosis was conducted after insulation was installed. Energy measurement, diagnosis and analysis were performed using the IoT-based integrated wired/wireless energy diagnosis platform, Energy Finder. As a result of comparison, an overall energy saving rate of 16.38% was achieved. Annual heating energy consumption per unit area decreased from 333.51kWh before construction to 277.35kWh after construction, and annual cooling energy consumption per unit area decreased from 5.51kWh before construction to 5.22kWh after construction. The annual primary energy consumption per unit area decreased from 464.52kWh before construction to 403.69kWh after construction, and the annual energy cost was reduced from 3,063,307.14 won before construction to 2,641,072.49 won after construction. The additional improvement work is needed on the standards affecting energy efficiency other than insulation.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Land and Housing Review
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• v.14 no.2
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• pp.125-135
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• 2023

Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.461-467
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• 2019

Advances in location-aware and IoT (Internet of Things) technology increase the rapid generation of massive movement data. Knowledge discovery from massive movement data helps us to understand the urban flow and traffic management. This paper proposes a method to analyze frequent origin-destination sequence patterns from irregular spatiotemporal taxi pick-up locations. The proposed method starts by conducting cluster analysis and then run a frequent sequence pattern analysis based on identified clusters as a base unit. The experimental data is Seoul taxi trajectory data between 7 a.m. and 9 a.m. during one week. The experimental results present that significant frequent sequence patterns occur within Gangnam. The significant frequent sequence patterns of different regions are identified between Gangnam and Seoul City Hall area. Further, this study uses administrative boundaries as a base unit. The results based on administrative boundaries fails to detect the frequent sequence patterns between different regions. The proposed method can be applied to decrease not only taxis' empty-loaded rate, but also improve urban flow management.

• Smart Structures and Systems
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• v.31 no.1
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• pp.1-11
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• 2023

Assessment of the compressive strength of concrete plays a major role during formwork removal and in the prestressing process. In concrete, temperature changes occur due to hydration which is an influencing factor that decides the compressive strength of concrete. Many methods are available to find the compressive strength of concrete, but the maturity method has the advantage of prognosticating strength without destruction. The temperature-time factor is found using a LM35 temperature sensor through the IoT technique. An experimental investigation was carried out with 56 concrete cubes, where 35 cubes were for obtaining the compressive strength of concrete using a universal testing machine while 21 concrete cubes monitored concrete's temperature by embedding a temperature sensor in each grade of M25, M30, M35, and M40 concrete. The mathematical prediction model equation was developed based on the temperature-time factor during the early age compressive strength on the 1^st, 2^nd, 3^rd and 7^th days in the M25, M30, M35, and M40 grades of concrete with their temperature. The 14^th, 21^st and 28^th day's compressive strength was predicted with the mathematical predicted equation and compared with conventional results which fall within a 2% difference. The compressive strength of concrete at any desired age (day) before reaching 28 days results in the discovery of the prediction coefficient. Comparative analysis of the results found by the predicted mathematical model show that, it was very close to the results of the conventional method.

• Journal of Internet of Things and Convergence
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• v.6 no.2
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• pp.37-43
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• 2020

The paper proposed the method of calculating the latest approach angle that can reliably recognize multiple laser images even with the change in separation distance between screen and laser launch device. This method recognizes the angle of the laser pattern angle by using the distance of the laser pattern angle, and the angle extraction of the laser detects the laser image from the acquired image using the labeling algorithm, and performs the huff conversion to extract the angle of the straight line. The distance of the reference angle and angle of the laser image extracted using Euclidean distance among similarity scales is calculated, and the furnace is recognized using the calculated distance result value. Experiments with changing the separation distance to "200 cm to 400 cm" showed 100% recognition of individual strands at all separation distances. The experiment confirmed the reliability of the proposed method.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.59-64
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• 2022

Existing edge discovery techniques only found edges of defined shapes based on precise definitions of edges. Therefore, there are many limitations in finding edges for images of complex and diverse shapes that exist in the real world. A method for solving these problems and discovering various types of edges is a cost minimization method. In this method, the cost function and cost factor are defined and used. This cost function calculates the cost of the candidate edge model generated according to the candidate edge generation strategy. If a satisfactory result is obtained, the corresponding candidate edge model becomes the edge for the image. In this study, a new candidate edge generation strategy was proposed to discover edges for images of more diverse shapes in order to improve the disadvantage of only finding edges of a defined shape, which is a problem of the cost minimization method. In addition, the contents of improvement were confirmed through a simple simulation that reflected these points.

• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.47-54
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• 2022

The purpose of this study was to examine the mediating effect of family organization patterns of family resilience on the relationship between parenting stress and parenting efficacy. A total of 263 participants who have children with disabilities participated in this study by responding to the following questionnaires: Parenting Stress Index(PSI), Family Resilience Scale, Parenting Efficacy Scale. The collected data were analyzed using SPSS 25.0 and Amos 22.0. The main findings were as follows. There was a significant partial mediating effect of family organization patterns of family resilience on the relationship between parenting stress and parenting efficacy. The results of this study can provide useful information for family who have children with disabilities. suggestions for future study were discussed.

• Information Systems Review
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• v.21 no.3
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• pp.87-110
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• 2019

The Fintech services provide innovation to financial services users using various mobile devices and computers in wired and wireless communication environments. In this study, we develope a theoretical research framework to explain the psychology of Fintech services users based on a cognitive, affective, and conative framework. Using this framework, this study analyzes the relationships between the cognitive characteristics (i.e., innovation, relative advantage, ease of use, and usefulness), emotional characteristic (i.e., attitude), and behavioral characteristic (i.e., actual use) toward Fintech services users. This study conducted an online survey of people who have experienced using Fintech services. And the data of the collected Fintech services users was analyzed using structural equation model software (i.e., SMART PLS 2.0 M3). The results of the empirical analysis show the relationships between innovation, relative advantage, perceived usefulness, perceived ease of use, attitude, and actual use of Fintech service users. The results of this study provide useful information to improve the practical use of Fintech services users in the Internet of Things (IoT) environment.