Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Vehicular Ad-hoc Networks (VANETs) are major popular wireless environment for Intelligence Transport Systems (ITS). This paper concentrates on Location Identification and Driver Safety (LIDS). Location identification is mapping out by using RFID (Radio Frequency Identification) technology to recognize the current location and also corresponding surrounded areas. The additional feature to be included is to control the speed of vehicle, when ever vehicle crosses school and hospital zones. For driver safety can be carried out using grip force sensor and eye-ball sensor. Driver’s drowsiness is detected by the sensors and alerts the buzzer and stops when ever driver comes to normal state and pressing reset button. The complete system is controlled by an effectual low cost version of 8051 microcontroller (AT89S52). On the whole, LIDS suits well for safety vehicle system. The implementation results show better performance than already existing methods.
S.Shanmugam. 2014. \u201cLocation Identification and Driver Safety System in VANETs\u201d. Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 14 (GJCST Volume 14 Issue G3): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Neural Networks and Rules-based Systems used to Find Rational and
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Vehicular Ad-hoc Networks (VANETs) are major popular wireless environment for Intelligence Transport Systems (ITS). This paper concentrates on Location Identification and Driver Safety (LIDS). Location identification is mapping out by using RFID (Radio Frequency Identification) technology to recognize the current location and also corresponding surrounded areas. The additional feature to be included is to control the speed of vehicle, when ever vehicle crosses school and hospital zones. For driver safety can be carried out using grip force sensor and eye-ball sensor. Driver’s drowsiness is detected by the sensors and alerts the buzzer and stops when ever driver comes to normal state and pressing reset button. The complete system is controlled by an effectual low cost version of 8051 microcontroller (AT89S52). On the whole, LIDS suits well for safety vehicle system. The implementation results show better performance than already existing methods.
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