Artificial intelligence, machine learning, and deep learning applications in smart and sustainable industry transformation

Abstract

Continued integration of artificial intelligence (AI), machine learning (ML), and deep learning (DL) with modern, smart and sustainable industry domain provide a springboard to the Industry 4.0, Industry 5.0, and Society 5.0. These technologies revolutionize operational efficiency, sustainability, and innovation in many industries. Predictive maintenance scheduling powered by AI lowers downtime and reduces operation expenses. ML algorithms help effective demand forecasting and inventory management to make better use of available resources. Through the use of DL practices, robust quality control and defect identification for example are possible all due to the advancement in manufacturing product quality. In addition, AI-powered automation in manufacturing has the ability to scale and flex fuelling an agile industrial world. A smart grid with AI integration helps in bringing energy sustainability and efficiency by optimizing the energy distribution and pattern of consumption. AI and ML powered autonomous systems reinforce the systems that analyse data in real-time, that improve delivery performance and reduce carbon footprints in logistics and supply chain management. Moreover, the AI applications in the environmental monitoring, supports sustainability, which provides the actionable results in controlling the pollution and managing the resources. We see them working along with human individuals such as cobots which shows AI is supporting the human-centric design in Industry 5.0. The AI, ML and DL convergence has played a key role in the transformation towards the smart and sustainable industry and paved way for innovative as well as sustainable solution in the contemporary industrial scenario.