Open AccessIdentification of mobile vehicle through multilayer intercommunication
Author(s) -
Ranjan Goyal,
Anuradha Gnanaprakasam,
Paritosh Pal Singh
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v17.i3.pp1390-1398
Subject(s) - computer science , testbed , identification (biology) , task (project management) , key (lock) , software deployment , simple (philosophy) , object (grammar) , vehicle tracking system , computer security , internet of things , real time computing , computer network , artificial intelligence , engineering , systems engineering , philosophy , botany , epistemology , segmentation , biology , operating system
In the recent times of data transmission, applying the Internet of Things (IoT) device, networking to the various IoT modules is still a great challenge with the deployment stage. Very few localities in the world have the deployed IoT module integrated in its communication, but still maximum of the location are in testbed. As a practical application, the IoT modules can be used to collect the information about either the drunken person who is driving the vehicle or the heavily loaded vehicles. The vehicle that we are about to search should be integrated with the IoT module. In this paper, a novel approach for object tracking specifically the drunken driving person and the heavily loaded vehicle is proposed to ensure the follow of rules and prevent any mis happening. The task is to identify the exact vehicle which does not follow the rules which can be tracked and eliminated. For that we are proposing a simple methodology on identifying the vehicle by the tracking the locality of the vehicle as a cluster of nodes where the cluster provides the key inference on how the vehicles are interrelated in the learning environment.