Zigbee Wireless Vehicular Identification and Authentication System

Dissanayake, Sarangi D.; Karunasekara, P. P. C. R.; Lakmanaarachchi, D.D.; Rathnayaka, A. J. Dinusha; Samarasinghe, A.T.L.K.

doi:10.1109/iciafs.2008.4783998

Cited by 25 publications

(6 citation statements)

References 4 publications

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“…This connection technology based on Radio Frequency (RF) that have range 1 km or more. To assurance connection between server and client through the highway , Xbee units must be install along the highway in equal distances during zigbee protocol [23] . …”

Section: Xbee Modulementioning

confidence: 99%

Real-Time Safety Automobile Driver System

Abdulbaki¹,

Khadim²

2015

IJCA

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The Driver Fatigue Detection (DFD) plays an important role in automobile safety and security. Driver fatigue is one of the leading causes of traffic accidents. Long-vehicles driving are needed to keep drivers under monitoring due to fatigue and more accidents. This monitoring include : eyes blinking , face expressions. Without these monitoring, the accidents is increasing and caused the driver death. Driver's tiredness and drowsiness are the major causes of traffic accidents on road. This proposed prototype is monitor the driver's fatigue level and analyze fatigue reason's (tiredness, drowse or a drunken ) and real-time DFD online. The proposed model depend on eye gestures (eyes blinking) and sensors such as an infrared camera (camera remotely) to detect driver expression. These sensors directly pointed towards the driver's face. This technology is not interactive with an outside driving situation .The system consist of Mesh network equipped Zigbee protocol , sensors and Xbee tag. The system analyze the variation of driver's eyes movement rate. According that parameters , the system can specify the level of driver's fatigue based on the response signals and alert driver. Practically. This system is robust, reliable, and accurate to detect fatigue levels.

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Section: Xbee Modulementioning

confidence: 99%

Real-Time Safety Automobile Driver System

Abdulbaki¹,

Khadim²

2015

IJCA

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“…Oxygen gas (O 2 ) deficient environment has termed as "hazardous" by (WHO) when the O 2 concentration is less than 19.5%. Low O 2 levels can impair sense of judgment, increases heart rate, and impair muscular coordination [2] . As experienced by most people, discomfort due to offensive smells is the prime concern regarding pollutants in vehicle cabins.…”

Section: Introductionmentioning

confidence: 99%

Design and Construction of Hazardous Gas Detection and Control System for Electric Vehicle Cabin

Adhav¹,

Salunke²

2023

IJRASET

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Electric vehicles (EVs) are a promising technology for achieving a sustainable transport sector due to their very low to zero carbon emissions, low noise, high efficiency, and flexibility in grid operation and integration. This chapter includes an overview of electric vehicle technologies as well as associated energy storage systems. Different types of electric-drive vehicles are presented. Also, if hazardous gas is detected inside of the cabin such as CO2 gas as a result of occupants of the vehicle, the system will open windows of the vehicle automatically. The advantage of this system is proper detection and faster response time leading to faster diffusion of the situation, compared with the manual methods. The gas sensor used in this project is MQ-7 and MQ-135 which detects the presence of hazardous gases both inside and outside of the vehicle cabin. These sensors will detect the concentration of the gas according to the voltage output of the sensor. To make the sensors operate in the control and data monitoring system, Arduino Uno was used as the microcontroller for the whole system. The circuit also includes Servo motor, buzzer, exhaust fan and LCD screen.

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“…The Zigbee Alliance defines 7 application profiles including building automation, remote control, smart energy, health care, home automation among others. Besides, the research community is also investigating the usage of Zigbee in vehicular applications such as intra-car wireless sensor networks (Tsai et al, 2007), wireless vehicular identification and authentication system (Dissanayake et al, 2008), wireless sensor networks for CO 2 monitoring (Hu et al, 2009). …”

Section: Zigbeementioning

confidence: 99%