A Smart Vehicle Charging Station Identification Based On IOT with Hybrid Grey Wolf-Bat Optimization Enriched On Artificial Neural Networks Recognition Methods

Author:

Arumugam VijayaprabhuORCID

Abstract

The tendency towards the green energy resolution, in the recent days there is a substantial increase in electric vehicles. Hence, identification of available charging station towards the travel is a major issue. For this purpose, this research work intends to develop a smart vehicle charging station with proper route mapping and monitoring units. The aim of this work is to identify the nearby available charging point by developing an advanced charging station with Internet of things (IOT) enabled. The availability of charging slot for the particular time is also identified by the image processing. In particular, Anisotropic Filtering (AF) will be suitable for this work for improving the image quality by reducing the noise. Along with that co-occurrence matrix is deployed for texture analysis of the image processing. Hybrid Grey Wolf Bat optimizer (GWBO) is utilized for efficient tracking of fastest route. At last, Artificial Neural network (ANN) technique implementation perfectly identifies whether the empty space is available or not in the charging station for our vehicle. Various scales are analyzed for the validation of results with the conventional methods.

Publisher

Qeios Ltd

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