Sustainable industrial systems within kernel density analysis of artificial intelligence and industry 4.0

Abstract

Abstract This paper conveys the theoretical perspectives of sustainable industrial systems of On board Unit (OBU) in Electronic Toll and its transportation industry. It proposes kernel density analysis of artificial intelligence approach to industry 4.0. Regulation for technology developments in artificial intelligence and robotics are deemed as one of beneficial yet structurally neglected domain. This domain refers to human perspective on augmenting automation. This regulation was emphasized in 2017 by the European Parliament report level. The mentioned regulation comprises attention in Indonesia transportation industry indicating positive innovation domains in term of safeguards and regulations are needed. Prior, current and posterior trends of the Internet of Things, Industry 4.0, and Physical Internet constitutes the results of the data development and understanding. Therefore, the topical framework of automation and robotics are triggered by these developments. The mention triggers has impacted the most important wide range implementation of industries in the future. Electronic Toll Collection (ETC) system is 40% higher in cost efficiency than Manual Toll Collection (MTC) system. In this situation, Indonesian government has already issued full swing policy implementation on non-contact freeway toll collection system by the end of 2018. Structural Equation Modelling (SEM) is capitalized to proceed to data processing. Result of this research shown the driver's characteristics that significantly affect willingness to pay an on-board unit are education expenses, distance and frequency. The average value of driver willing to pay an on-board unit was 225.781 IDR and factors that affecting values of the willingness to pay an on-board unit are expenses and distance.