CHATGPT POTENTIAL TO SELECT TECHNOLOGY IN RAPID PROTOTYPING OF CYBER-PHYSICAL SYSTEM

Abstract

It is a common task to select optimal technologies for a prototype implementation. If a prototype of a cyber-physical system is developed, it is required to select suitable components, devices and software development tools, which are compatible with each other. Traditionally, the market analysis is conducted reviewing components, searching for a trade-off combination which are optimal for the prototype implementation. That is a sufficiently time consuming process. Additionally, the market changes are relatively fast. Therefore, the search must be repeated periodically. We propose the hypothesis that ChatGPT can help in market analysis to select optimal components in the rapid prototyping tasks. To evaluate our hypothesis, each author tried to find an optimal solution considering his specialization or interest field. Based on the obtained experience, the Delphi method was applied to collect expert opinions to gain consensus, which is presented in this article.