• Journal of Digital Convergence
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• v.14 no.7
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• pp.175-184
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• 2016

The purpose of the study focuses on increasing dangers of using smartphones while driving recently, and then is to come up with measures to reduce traffic accidents caused by using devices like a smartphone. This study conducted a survey of drivers using their smartphones while driving to understand risks caused by using a smartphones while operating vehicles. Results showed that a lot of activities may lead to distracted driving, such as texting, making phone calls, using GPS or road maps, game, etc. In this paper, we presented that functions of smartphone should be controlled partially while driving for safe driving performance. These results suggest that using IoT-based smart devices like a beacon and a smartphone application implemented, tentatively called "Safe driving solution", while driving can reduce traffic accidents. Thus, in order to effectively prevent dangerous driving due to the use of smartphones, a "Safe driving solution" which restricts all functions except for calls and driver assistance functions is suggested.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1551-1558
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• 2021

Beacon signals used in indoor positioning system are reflected and distorted, resulting in noise signals. KF(Kalman Filter) has been widely used to remove this noise. In order to apply the KF, optimization process considering the signal type, signal strength, and environmental elements of each product is required. In this paper, we propose a solution to the optimization problem of KF Parameters using GA(Genetic Algorithm) in BLE(Bluetooth Low Energy) Beacon-based indoor positioning system. After optimizing KF Parameters by applying the proposed technique with a certain distance between Beacon and receiver, we compared the estimated distance passed through KF with the unfiltered distance. The proposed technique is expected to reduce the time required and improve accuracy of KF Parameters optimization in an indoor positioning system based on RSSI (Received Signal Strength Indication).

• Tunnel and Underground Space
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• v.32 no.2
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• pp.93-106
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• 2022

This study developed applications that allows truck drivers to record ore production data using smart devices at mine sites and to create a daily work report (operation report) in a PC environment. For this, four operating mines in Korea were selected as study areas, and daily work reports used there were investigated. The information elements included in the daily work report of each mine were analyzed. Because the information to be collected for writing ore production data and format of report are different for each mine, four types of applications were developed for the study areas. Ore production data could be recorded by receiving a signal from a Bluetooth beacon and by operating the application directly by the truck driver. The collected data files are uploaded to the cloud server, and the uploaded data files can be converted into a daily work report using the developed applications in a PC environment.

• Tunnel and Underground Space
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• v.32 no.4
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• pp.254-271
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• 2022

The performance of truck haulage operations in an underground mine was evaluated using the time usage model and key performance indicators (KPIs) proposed by Global Mining Guidelines Group (GMG). An underground mine that mainly produces iron and titanium iron was selected as a study area, and truck haulage data were collected using Bluetooth beacons and tablet PCs. The collected data were analyzed to identify unit operations, activities, events, and required time of truck haulage operations, and time categories were classified based on the time usage model. The performance of the haulage operations was evaluated using nine indicators in terms of availability, utilization, and effectiveness. As a result, in terms of availability, uptime was 33.9%, physical availability was 95.7%, and mechanical availability was 94.9%. In the case of utilization, use of availability was 83.1%, asset utilization was 28.1%, and operating and effective utilization were 79.6% and 77.7%, respectively. Also, in terms of efficiency, operating efficiency was high at 97.6%, and production effectiveness was found to be 49%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1855-1862
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• 2022

Various indoor location-based services can be provided through indoor presence determination and indoor positioning technology using Beacon. However, since the BLE signal advertised by the beacon has an unstable RSSI due to problems such as multi-path fading, it is difficult to guarantee the accuracy of indoor presence determination. In this paper, data were collected while the classroom door was open to ensure accuracy in various situations. Based on the collected data, we propose an indoor presence determination method considering the characteristics of the signal. The proposed method uses support vector machine, showed about 10% accuracy improvement compared to the results using raw RSSI only. This method has the advantage of being able to accurately determine indoor presence with only one receiver. It is expected that the proposed method can implement a low-cost system for determining indoor presence with high accuracy.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.119-125
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• 2022

With the recent increase in dementia patients due to aging, measures to prevent their wandering behavior and disappearance are urgently needed. To solve this problem, various authentication methods and location detection techniques have been introduced, but the security problem of personal authentication and a system that can check indoor and outdoor overall was lacking. In order to solve this problem, various authentication methods and location detection techniques have been introduced, but it was difficult to find a system that can check the security problem of personal authentication and indoor/outdoor overall. In this study, we intend to propose a system that can identify personal authentication, basic health status, and overall location indoors and outdoors by using wristband-type wearable devices in a private blockchain environment. In this system, personal authentication uses ECG, which is difficult to forge and highly personally identifiable, Bluetooth beacon that is easy to use with low power, non-contact and automatic transmission and reception indoors, and DGPS that corrects the pseudorange error of GPS satellites outdoors. It is intended to detect wandering behavior and abnormal signs by locating the patient. Through this, it is intended to contribute to the prompt response and prevention of disappearance in case of wandering behavior and abnormal symptoms of dementia patients living at home or in nursing homes.