Smart Contract Centric Inference Engine For Intelligent Electric Vehicle Transportation System
Prince Waqas Khan, Yung-Cheol Byun
Abstract
The provision of electric vehicles (EVs) is increasing due to the need for ecological green energy. The increment in EVs leads to an intelligent electric vehicle transportation system's need instead of cloud-based systems to manage privacy and security issues. Collecting and delivering the data to current transportation systems means disclosing personal information about vehicles and drivers. We have proposed a secure and intelligent electric vehicle transportation system based on blockchain and machine learning. The proposed method utilizes the state of the art smart contract module of blockchain to build an inference engine. This system takes the sensors' data from the vehicle control unit of EV, stores it in the blockchain, makes decisions using an inference engine, and executes those decisions using actuators and user interface. We have utilized a double-layer optimized long short term memory (LSTM) algorithm to predict EV's stator temperature. We have also performed an informal analysis to demonstrate the proposed system's robustness and reliability. This system will resolve the security issues for both information and energy interactions in EVs.