The Feasibility Evaluation Model of Industrial Robot Entrepreneurship Based on Data Collection

Abstract

Artificial intelligence and robots are changing the economic and entrepreneurship environment in the industrial revolution. Artificial intelligence and robotics have become prevalent in modern economic, professional, social, and daily lives. As a function of its ability to update and develop business processes and innovative ideas, services, and products and resolve difficult tasks to achieve new, entrepreneurship has experienced massive development. Significant changes are occurring in entrepreneurship and economic growth due to artificial intelligence. Therefore, this paper aims to understand the effect and components of data entrepreneurship overall with the help of an artificial intelligence-based feasibility evaluation model (AI-FEM). Robot, edge and physical resource layers are described in depth in this document. We first deploy an edge node near the data sources to combine multiple devices’ interfaces and function as a raw data filter. Then it provides opportunity recognition, opportunity development, and opportunity implementation processes are part of the framework’s processes described in this paper. This paper aims to develop a basic framework for evaluating AI’s potential implications for the interaction between entrepreneurship and economic growth. The economic growth of industrial robots reduces basic labor costs. However, it increases hourly compensation, suggesting that the productivity-enhancing advantage of industrial robots equals the wage-increasing influence. The results show that the system is feasible and performs better in real-time and network transmission than in an AI-based industry scenario. The experimental results of AI-FEM show the high-performance ratio of 95.5%, productivity ratio of 96.3%, reliability ratio of 93.4%, the employment rate of 92.6%, an efficiency ratio of 93.6%, industrial management ratio of 90.3%, and cost-effectiveness ratio of 20.3% compared to other methods.