• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.554-561
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• 2017

IoT (Internet of Things) devices are often located in environments where indoor or underground, signals are difficult to reach. In addition, the transmission power is low, the base station should be designed to be able to receive signals even at low reception sensitivity. For this reason, a device having a poor channel condition can be transmitted at a low data rate using a low coding rate or repetition. When the coverage class is divided according to the channel condition and the data rate, the packet length may vary from one coverage class to another, and the performance of the slotted aloha random access may be degraded. We will focus on two methods of using shared-resource and seperate resources among multiple slotted aloha methods. In particular, when devices with different coverage classes use shared resources, performance of a device with a bad channel condition may deteriorate. Conversely, when using separate resources for each coverage class, there is a problem that congestion may occur which increases the number of devices that perform random access to one resource area. In this paper, we propose some methods to overcome this problem. This study is mainly focused on MTC devices, and is considered to be a high possibility of future development.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.51-57
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• 2019

In this paper, we analyzed the performance of IoT based smart wearable mine detection device. There are various mine detection methods currently used by the military. Still, in the general field, mine detection is performed by visual detection, probe detection, detector detection, and other detection methods. The detection method by the detector is using a GPR sensor on the detector, which is possible to detect metals, but it is difficult to identify non-metals. It is hard to distinguish whether the area where the detection was performed or not. Also, there is a problem that a lot of human resources and time are wasted, and if the user does not move the sensor at a constant speed or moves too fast, it is difficult to detect landmines accurately. Therefore, we studied the smart wearable mine detection device composed of human body antenna, main microprocessor, smart glasses, body-mounted LCD monitor, wireless data transmission, belt type power supply, black box camera, which is to improve the problem of the error of mine detection using unidirectional ultrasonic sensing signal. Based on the results of this study, we will conduct an experiment to confirm the possibility of detecting underground mines based on the Internet of Things (IoT). This paper consists of an introduction, experimental environment composition, simulation analysis, and conclusion. Introduction introduces the research contents such as mines, mine detectors, and research progress. It consists of large anti-personnel mine, M16A1 fragmented anti-mine, M15 and M19 antitank mines, plastic bottles similar to mines and aluminum cans. Simulation analysis is conducted by using MATLAB to analyze the mine detection device implementation performance, generating and transmitting IoT signals, and analyzing each received signal to verify the detection performance of landmines. Then we will measure the performance through the simulation of IoT-based mine detection algorithm so that we will prove the possibility of IoT-based detection landmine.