Blockchain based Automated Construction Model Accuracy Prediction using DeepQ Decision Tree

Abstract

A growth of Industry 4.0 standards are increasing day by day. Various research application and problem statements are coming to create multiple automation environments. Blockchain technology is the important evolution to produce dynamic and avoid intermediate middleware processing systems. In this paper we propose a blockchain based automated construction modelling and analysis system. Here we check the efficiency of the system by using collaboration, transparency, workflow and reliable data model. DeepQ based classification and prediction method is used to measure the accuracy index. Decision tree algorithm is used to divide the process model and generate the chain codes. 1500 trained dataset and 750 dataset is taken from Revit construction model set and apply blockchain codes to process the dataset. The simulations are taken effectively and reach the accuracy as 96%.