Impact of green technology innovation based on IoT and industrial supply chain on the promotion of enterprise digital economy

• Published in: PeerJ. Computer science 2023-05, Vol.9, p.e1416-e1416
• Main Authors: Song, Ruilin, Hu, Hui
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Data mining and machine learning; Digital economy; Economic aspects; Forecasts and trends; Green innovation; Green technology; Industrial suppliers; Innovations; Internet of Things; IoT; Logistics; PSO-SVM; Supply chain management; Warehouses
• ISSN: 2376-5992; 2376-5992
• DOI: 10.7717/peerj-cs.1416

With the gradual deterioration of the natural environment, a green economy has become a competing goal for all countries. As a trend of green innovation development, the digital economy has become a research hotspot for scientists. In this article, we study the supply chain management of enterprises in green innovation and digital economy development and complete the identification and demand prediction of warehouse goods through the Internet of Things (IoT) and artificial intelligence (AI). As the stuff meets the goods detection and storage, we employ an intelligent method to detect and classify the goods. The demand prediction analysis is carried out based on historical data on goods demand in the enterprise. The absolute error between the prediction result and the actual demand within 1 week is less than 30 goods by the particle swarm optimization-support vector machine (PSO-SVM) method used in this article. First, the goods identification task is completed based on video surveillance data using YOLOv4, and the recognition rate is as high as 98.3%. This article realises enterprises' intelligent supply chain management through the intelligent identification of goods and the demand forecasting analysis of goods in the warehouse, which provides new ideas for green innovation and digital economy development.