An IoT Blockchain Network-Based Approach for Optimizing Smart Contracts in Electric Vehicles for Environmental Control

Abstract

This study proposes a smart contract model for optimizing energy management in electric vehicles based on IoT blockchain networks. The model consists of three hierarchical layers: prediction, optimization, and control. In the prediction layer, a Kalman filter is used to remove noise and extract environmental features. The optimization layer utilizes the BAT algorithm to optimize energy consumption and user comfort, incorporating user preferences into the comfort index formula. A convolutional fuzzy logic controller is integrated with the prediction module to enhance performance. The control module tunes membership functions dynamically to improve control performance. The Hyperledger Fabric network is employed for evaluating the proposed model, considering metrics such as caliper, latency, throughput, and resource utilization. This research aims to address challenges related to energy management trade-offs, data privacy, security, and cost in IoT-based systems for electric vehicles.