• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.155-157
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• 2024

Internet of Things (IoT) integrated with the Blockchain is the state of the art for keen cultivation and agriculture. Recently the interest in agribusiness information is enlarging owing to the fact of commercializing the smart farming technology. Agribusiness information are known to be untidy, and experts are worried about the legitimacy of information. The blockchain can be a potential answer for the expert's concern on the uncertainty of the agriculture data. This paper proposes an Agri-Banana plant system using Blockchain integrated with IoT. The system is designed by employing IoT sensors incorporated with Hyperledger fabric network, aims to provide farmers with secure storage for preserving the large amounts of IoT and agriculture data that cannot be tampered with. A banana smart contract is implemented between farmer peer and buyer peer of two different organizations under the Hyperledger fabric network setup aids in secure transaction of transferring banana from farmer to buyer.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.671-678
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• 2019

The semantic information provided through the semantic-based IoT system will produce new high value-added products that are completely different from what we have known and experienced. From this point of view, the key issue of current IoT technology and applications is the development of an intelligent IoT platform architecture. The proposed system collects the IoT data of the sensors from the cloud computer, converts them into RDF, and annotates them with semantics. The converted semantic data is shared and utilized through the ontology repository. We use KT's IoTMakers as a cloud computing environment, and the ontology repository uses Jena's Fuseki server to express SPARQL query results on the web using Daum Map API and Highcharts API. This gives people the opportunity to access the semantic IoT mash-up service easily and has various application possibilities.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.27-38
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• 2019

Sensors collect information for Internet of Things (IoT)-based services. However, indoor construction sites have a poor communication environment and many interfering elements that make it difficult to collect sensor information. In this study, a network was constructed between a Bluetooth Low Energy (BLE)-based IoT device based on a serverless IoT framework and a router. This experimental environment was applied to large- and small-scale indoor construction sites. Experiments were performed to test the communication performance of BLE-based IoT devices and routers at indoor construction sites. An analysis of the received signal strength indication (RSSI) graph patterns collected from the communication between the BLE-based IoT devices and routers for different testbed site situation revealed areas with good communication performance and poor communication performance due to interfering factors. The results confirmed that structural components of the building as well as the materials, equipment, and temporary facilities used in indoor construction interfere with the communication performance. Construction project managers will require improved technical knowledge of IoT, such as optimizing the router placement and matching communication between the router and workers, to improve the communication performance for large-scale indoor construction.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.5
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• pp.301-308
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• 2021

It is important to develop a digital SOC (Social Overhead Capital) maintenance system for preemptive maintenance in response to the rapid aging of social infrastructures. Abnormal signals induced from structures can be detected quickly and optimal decisions can be made promptly using IoT sensors deployed on the structures. In this study, a digital SOC monitoring system incorporating a multimetric IoT sensor was developed for long-term monitoring, for use in cloud-computing server for automated and powerful data analysis, and for establishing databases to perform : (1) multimetric sensing, (2) long-term operation, and (3) LTE-based direct communication. The developed sensor had three axes of acceleration, and five axes of strain sensing channels for multimetric sensing, and had an event-driven power management system that activated the sensors only when vibration exceeded a predetermined limit, or the timer was triggered. The power management system could reduce power consumption, and an additional solar panel charging could enable long-term operation. Data from the sensors were transmitted to the server in real-time via low-power LTE-CAT M1 communication, which does not require an additional gateway device. Furthermore, the cloud server was developed to receive multi-variable data from the sensor, and perform a displacement fusion algorithm to obtain reference-free structural displacement for ambient structural assessment. The proposed digital SOC system was experimentally validated on a steel railroad and concrete girder bridge.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.19-26
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• 2019

Recently, the importance of the internet of things (IoT) education has been emphasized due to the progress of research on IoT technology. Therefore, universities require an efficient IoT course. In this paper, we propose an undergraduate IoT course using the Bluetooth function of smartphone and Arduino kit. The proposed embedded IoT class uses the Bluetooth capabilities of the smartphone to connect Arduino and activate various sensors to encourage students to become interested in the class. According to students' midterm and final exam scores, students programming skills have been improved since students' projects were in progress during the course. Further, according to students' survey, the proposed IoT class is very effective in understanding the embedded IoT and 75% of the students satisfied with the proposed course.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.184-192
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• 2019

The existing digital signage systems inside the elevators are a lack of tailored contents appropriate to the space and environment inside or outside the elevators. Also, they almost impossible to flexibly respond to various contents disclosure according to the demand of the consumers or the elevator markets. Therefore we design and implement an IoT(Internet of Things)-based smart digital signage system for the safety of elevator passengers.. In order to provide IoT-based information to the smart digital signage within the elevator, we propose an IoT system as a set-top box with gyroscope sensor, acceleration sensor, RFID(Radio-Frequency Identification), fine dust sensor, etc., which processes various data collected by the sensors and provides the elevator passengers with various tailored contents such as elevator driving information, environmental information inside and outside the elevator, and disaster information in addition to simple advertisement information. The proposed IoT system is a set-top box that operates the smart digital signage and has an independent information control processor based on the IoT sensors that do not depend on the elevator control system. For the proposed smart digital signage, it supports an operating system that is independent of the elevator driving service as well as the media service. So the smart signage system has a characteristic that it does not depend on the elevator control system since it is a stand-along IoT-based information control system. With the proposed system providing intuitive content for the surge, steep descent, and radical movements of an elevator due to an emergency situation, the elevator passengers should be able to recognize the situation quickly and respond accordingly. In the near future, the proposed system will expand the market of digital signage applied in conjunction with the development of contents in the disaster, safety and environment fields, and expect expected to revitalize related industries associated with signage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.21-27
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• 2022

As society develops and becomes more complex, new and diverse types of disasters such as fine dust and infectious diseases are occurring. However, in the past, there was no PA(Public Address) system that provided accurate information to prepare for such a disaster. In this paper, we propose a public address system that automatically broadcasts an alarm by analyzing polluted air quality data collected from public data and IoT sensors. The warning level varies depending on the air quality, and the information provided by public data may show a significantly different result from the guide area due to various factors such as the distance from the measuring station or the wind direction. To compensate for this, we are going to propose a method for broadcasting by comparing and analyzing data obtained from public data and data from on-site IoT sensors.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.58-73
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• 2015

In the IoT environment, context information is important to provide context service to the user. For this, collected data from devices such as sensors or actuators, converts to context information using the ontology. Because the existing ontologies designed for target service, if the user wants to change the service requirements, service condition, service environment or another service, overall ontology will be redesigned to the changed service. To overcome this difficulty, we propose the cross-vertical ontology model called the Generic Ontology Models(GOMs). It can define the user's desired services without regarding to place and situation. Also, we propose IoT service concept model that represents data flow of the IoT service and IoT service environment. Moreover, as the use case, we show that the proposed GOMs are able to provide the IoT service well.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.103-114
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• 2022

The Internet of Things (IoT) is one of the fastest technologies that are used in various applications and fields. The concept of IoT will not only be limited to the fields of scientific and technical life but will also gradually spread to become an essential part of our daily life and routine. Before, IoT was a complex term unknown to many, but soon it will become something common. IoT is a natural and indispensable routine in which smart devices and sensors are connected wirelessly or wired over the Internet to exchange and process data. With all the benefits and advantages offered by the IoT, it does not face many security and privacy challenges because the current traditional security protocols are not suitable for IoT technologies. In this paper, we presented a comprehensive survey of the latest studies from 2018 to 2021 related to the security of the IoT and the use of machine learning (ML) and deep learning and their applications in addressing security and privacy in the IoT. A description was initially presented, followed by a comprehensive overview of the IoT and its applications and the basic important safety requirements of confidentiality, integrity, and availability and its application in the IoT. Then we reviewed the attacks and challenges facing the IoT. We also focused on ML and its applications in addressing the security problem on the IoT.