• Journal of Environmental Health Sciences
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• v.46 no.4
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• pp.444-456
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• 2020

Objectives: This study developed an index for the indoor air quality management of city buses to allow the provision of indoor air quality information to city bus users. Methods: Nine city buses in Seoul were measured for PM₁₀, PM_2.5, CO₂, temperature, and relative humidity through IoT sensors. Big data collected through the sensors was analyzed to identify indoor air quality on city buses and graded through the index. Results: As a result of dividing the measured city bus data into five grades through the IAQ index, PM₁₀ was rated "good" for 30.4% of the total measured values, and 9.2% were rated "risky". For PM_2.5, 67.7 percent were rated "good" and 0.4 percent were rated "risky". For CO₂, 0.9% were 'good' and 1.1% were 'risky'. The results of the classification through the IAQ index for city buses showed that the impact of good, normal, sensitive, bad, and dangerous were 2.7, 38.8, 46.0, 12.4, and 0.1%, respectively. According to the analysis by measurement area, Seocho-gu, Gangnam-gu, Seongdong-gu, Gwangjin-gu, and Dobong-gu are "normal" and other areas (Seodaemoon-gu, Jongno-gu, Yongsan-gu, Jung-gu, Seongbuk-gu, Dongdaemun-gu, Junggye-gu, Gangbuk-gu, and Nowon-gu) are all rated "sensitive". Conclusions: When analyzing cases where PM₁₀ and CO₂ indices are in the "bad" zone, the concentration is generally found to increase during rush hour, during which there are a large number of passengers. It is expected that indoor air quality management in vehicles will be necessary during rush hour.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.87-95
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• 2020

With the advent of the 4^th industrial revolution and the combination of IoT, there have been diverse domestic and foreign researches for the development of construction industry. Especially, in the large-scale earthwork site where many and various construction equipments are put into, the control system between construction equipments is important for the increase of productivity. Thus, after developing the fleet management system for the optimum operation of construction equipments, the problems were checked and improved for each step in the process of application at site. In order to verify the site application process of the fleet management system for the optimum operation of construction equipments, the analysis on the productivity was performed by inputting the data used for the actual site and the site data using this system and then comparing the data through simulation. The analysis was limited to excavator and dump. In the results of the analysis, the rate of work per hour was increased to the range of 4 % while the cost price was decreased to 4 %. Even though the results of the analysis could be different depending on the site applied, the results showing the increase of workload of equipments and the decrease of cost price in the complex project at earthwork site verify the increase of productivity.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.109-126
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• 2018

With massive and dense production, the livestock industry is rapidly moving into a large-scale, capital-intensive industry especially in swine, poultry, and ducks. However, livestock epidemics can pose a serious threat to the livestock industry and the lives of the people. The government has established and operates the National Animal Protection and Prevention System (KAHIS) since 2013 in order to control the threat, in accordance with the five stages. The digitalized data and information are excellent in ease of management, but it is also pointed out that it is difficult to take countermeasures through linkage with the data in an emergency situation. Recently, the technology of the fourth industrial revolution such as Internet of Things (IoT), Big Data, Artificial intelligence (AI) has been rapidly implemented to the livestock industry, which makes smart livestock disease control system possible. Therefore, this study investigated the domestic and overseas cases which apply 4th Industrial Revolution technology in the industry, and derived 13 possible candidate tasks in the near future. In order to ascertain the priority of policy formulation, we surveyed the expert groups and examined the priority of each of the five stages of the prevention and the priority of each stage. The results of this study are expected to contribute to the establishment of policies for the advancement of smart livestock disease control research and livestock protection.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2444-2452
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• 2022

The field-programmable gate array (FPGA) is gaining popularity in industrial automation such as nuclear power plant instrumentation and control (I&C) systems due to the benefits of having non-existence of operating system, minimum software errors, and minimum common reason failures. Separate functions can be processed individually and in parallel on the same integrated circuit using FPGAs in comparison to the conventional microprocessor-based systems used in any plant operations. The use of FPGAs offers the potential to minimize complexity and the accompanying difficulty of securing regulatory approval, as well as provide superior protection against obsolescence. Wireless sensor networks (WSNs) are a new technology for acquiring and processing plant data wirelessly in which sensor nodes are configured for real-time signal processing, data acquisition, and monitoring. ZigBee (IEEE 802.15.4) is an open worldwide standard for minimum power, low-cost machine-to-machine (M2M), and internet of things (IoT) enabled wireless network communication. It is always a challenge to follow the specific topology when different Zigbee nodes are placed in a large network such as a plant. The research article focuses on the hardware chip design of different topological structures supported by ZigBee that can be used for monitoring and controlling the different operations of the plant and evaluates the performance in Vitex-5 FPGA hardware. The research work presents a strategy for configuring FPGA with ZigBee sensor nodes when communicating in a large area such as an industrial plant for real-time monitoring.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.243-248
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• 2015

U-Healthcare is a convergence service with medical care and IT which enables to examine, manage and maintain the patient's health any time and any place. For communication conducted in U-Healthcare service, the transmission methods are used that patient's medical checkup analysis results or emergency data are transmitted to hospital server using wireless communication method. At this moment when the attacker who executes the malicious access makes DRDoS(Distributed Reflection DoS) attack to U-Healthcare devices or BS(Base Station), various damages occur that contextual information of urgent patients are not transmitted to hospital server. In order to deal with this problem, this study suggests DRDoS attack scenario and countermeasures against DRDoS and converges with Big Data which could process large amount of packets. When the attacker attacks U-Healthcare devices or BS(Base Station), DB is interconnected and the attack is prevented if it is coincident. This study analyzes the attack method that could occur in U-Healthcare devices or BS which are remote medical service and suggests countermeasures against the security threat using Big Data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1460-1468
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• 2015

As the number of IoT service increases, the interest of lightweight block cipher algorithm, which consists of simple operations with low-power and high speed, is growing. LEA(Leightweight Encryption Algorithm) is recently adopted as one of lightweight encryption standards in Korea. In this paper a pipeline LEA architecture is proposed to process large amounts of data with high throughput. The proposed pipeline LEA can communicate with external modules in the 32-bit I/O interface. It consists of input, output and encryption pipeline stages which take 4 cycles using a muti-cycle pipeline technique. The experimental results showed that the proposed pipeline LEA achieved more than 7.5 Gbps even though the key length was varied. Compared with the previous high speed LEA in accordance with key length of 128, 192, and 256 bits, the throughput of the pipeline LEA was improved 6.45, 7.52, and 8.6 times. Also the throughput per area was improved 2, 1.82, and 2.1 times better than the previous one.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.147-157
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• 2018

Recently, with the advancement of network technologies, and the activation of IoT and social network services, many graph stream data have been generated. As the relationship between objects in the graph streams changes dynamically, studies have been conducting to detect or analyze the change of the graph. In this paper, we propose a scheme to incrementally detect frequent patterns by using frequent patterns information detected in previous sliding windows. The proposed scheme calculates values that represent whether the frequent patterns detected in previous sliding windows will be frequent in how many future silding windows. By using the values, the proposed scheme reduces the overall amount of computation by performing only necessary calculations in the next sliding window. In addition, only the patterns that are connected between the patterns are recognized as one pattern, so that only the more significant patterns are detected. We conduct various performance evaluations in order to show the superiority of the proposed scheme. The proposed scheme is faster than existing similar scheme when the number of duplicated data is large.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.218-236
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• 2023

This study attempted to analyze the environmental equity of fine dust(PM₁₀) in Daegu using MGWR(Multi-scale Geographically Weighted Regression) and KT(Korea Telecom Corporation) sensor data. Existing national monitoring network data for measuring fine dust are collected at a small number of ground-based stations that are sparsely distributed in a large area. To complement these drawbacks, KT sensor data with a large number of IoT(Internet of Things) stations densely distributed were used in this study. The MGWR model was used to deal with spatial heterogeneity and multi-scale contextual effects in the spatial relationships between fine dust concentration and socioeconomic variables. Results indicate that there existed an environmental inequity by land value and foreigner ratio in the spatial distribution of fine dust in Daegu metropolitan city. Also, the MGWR model showed better the explanatory power than Ordinary Least Square(OLS) and Geographically Weighted Regression(GWR) models in explaining the spatial relationships between the concentration of fine dust and socioeconomic variables. This study demonstrated the potential of KT sensor data as a supplement to the existing national monitoring network data for measuring fine dust.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.143-149
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• 2016

Recent accidents caused by toxic chemicals and the social problems caused by frequent. As of 2010, there are more than 100,000 types of deadly toxic chemicals being distributed throughout Korea, and severely intoxicated patients along with an enormous number of patients can be induced at the time of an accident involving deadly toxic chemicals. Internationally, the seriousness of large-scale disasters due to a NBC disaster (nuclear, biologic and chemical disaster) is being highlighted as well. So, we obtain the information of the RFID tag attached to a glass bottle with containing the toxic chemical to transfer the data to the smart device has been studied a system that can monitor the status of the toxic chemical in real time. The proposed system is the information was sent to the main system using a zigbee communication by recognizing the tag vial containing the toxic chemical with the 13.56MHz bandwidths good permeability. User may check the information in real time by utilizing the smart device. However, the error of the system for managing the toxic chemical generates a result that can not be predicted. Failure of the system was detecting the error by using a comparator as this can cause an error. And the detected error proposed a duplex system so that they do not affect the overall system.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.465-470
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• 2017

This paper designs and implements a smart garden system using probabilistic filter algorithm using SLAM that can be used in apartment or veranda. To do this, we used Arduino and environtal sensors, which are open hardware controllers, and designed to control and observe automatic water supply, lighting, and growth monitoring with three wireless systems (Bluetooth, Ethernet, WiFi). This system has been developed to make it possible to use it in an indoor space such as an apartment, rather than a large-scale cultivation system such as a conventional plant factory which has already been widely used. The developed system collects environmental data by using soil sensor, illuminance sensor, humidity sensor and temperature sensor as well as control through smartphone app, analyzes the collected data, and controls water pump, LED lamp, air ventilation fan and so on. As a wireless remote control method, we implemented Bluetooth, Ethernet and WiFi. Finally, it is designed for users to enable remote control and monitoring when the user is not in the house.