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Ȩ Ȩ > ¿¬±¸¹®Çå > ¿µ¹® ³í¹®Áö > TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)

TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) An App Visualization design based on IoT Self-diagnosis Micro Control Unit for car accident prevention
¿µ¹®Á¦¸ñ(English Title) An App Visualization design based on IoT Self-diagnosis Micro Control Unit for car accident prevention
ÀúÀÚ(Author) YiNa Jeong   EunHee Jeong   ByungKwan Lee  
¿ø¹®¼ö·Ïó(Citation) VOL 11 NO. 02 PP. 1005 ~ 1018 (2017. 02)
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(Korean Abstract)
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(English Abstract)
This paper proposes an App Visualization (AppV) based on IoT Self-diagnosis Micro Control Unit (ISMCU) for accident prevention. It collects a current status of a vehicle through a sensor, visualizes it on a smart phone and prevents vehicles from accident. The AppV consists of 5 components. First, a Sensor Layer (SL) judges noxious gas from a current vehicle and a driver¡¯s driving habit by collecting data from various sensors such as an Accelerator Position Sensor, an O2 sensor, an Oil Pressure Sensor, etc. and computing the concentration of the CO collected by a semiconductor gas sensor. Second, a Wireless Sensor Communication Layer (WSCL) supports Zigbee, Wi-Fi, and Bluetooth protocol so that it may transfer the sensor data collected in the SL to ISMCU and the data in the ISMCU to a Mobile. Third, an ISMCU integrates the transferred sensor information and transfers the integrated result to a Mobile. Fourth, a Mobile App Block Programming Tool (MABPT) is an independent App generation tool that changes to visual data just the vehicle information which drivers want from a smart phone. Fifth, an Embedded Module (EM) records the data collected through a Smart Phone real time in a Cloud Server. Therefore, because the AppV checks a vehicle¡¯ fault and bad driving habits that are not known from sensors and performs self-diagnosis through a mobile, it can reduce time and cost spending on accidents caused by a vehicle¡¯s fault and noxious gas emitted to the outside.
Å°¿öµå(Keyword) Self-diagnosis   sensor modeling   APP design   Eco-drive   sensor network  
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