American Journal of Advanced Multidisciplinary Research and Innovation

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Smart Technologies and Data-Driven Decision-Making in the Era of Industry 5.0

Author(s) Yvonne C. Lui
Country United States
Abstract The emergence of Industry 5.0 marks a significant evolution beyond automation-centric industrial systems by promoting human-centric, sustainable, and resilient manufacturing and service ecosystems. Unlike Industry 4.0, which primarily focused on digitalisation and automation, Industry 5.0 integrates advanced technologies with human intelligence to create collaborative, adaptive, and sustainable production environments. The convergence of Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Big Data Analytics, Cloud Computing, Edge Computing, Digital Twin Technology, Blockchain, Cyber-Physical Systems (CPS), Collaborative Robots (Cobots), 5G/6G Communication, Explainable Artificial Intelligence (XAI), High-Performance Computing (HPC), Smart Sensors, and Business Intelligence (BI) enables intelligent, data-driven decision-making across manufacturing, healthcare, logistics, energy, agriculture, and public services.
This study presents a comprehensive analysis of Smart Technologies and Data-Driven Decision-Making in the Era of Industry 5.0. A qualitative analytical research methodology based on secondary data is employed to investigate intelligent decision-making frameworks, smart industrial ecosystems, AI-driven analytics, and multidisciplinary digital transformation. The research evaluates how smart technologies enhance operational efficiency, predictive maintenance, sustainable manufacturing, supply chain resilience, customer-centric production, and organisational competitiveness.
The findings indicate that data-driven decision-making significantly improves productivity, quality management, operational transparency, predictive capability, resource optimisation, energy efficiency, and innovation performance. Artificial Intelligence enables predictive analytics and autonomous decision support, while IoT provides continuous real-time monitoring through interconnected smart devices. Digital Twin Technology enables virtual simulation of physical assets for proactive optimisation, and Blockchain enhances secure data sharing, traceability, and trust across industrial ecosystems.
Despite these opportunities, challenges remain concerning data quality, interoperability, cybersecurity, digital infrastructure investment, workforce reskilling, algorithmic transparency, privacy protection, and ethical AI governance. Future research should investigate AI-native Industry 5.0 architectures, federated industrial intelligence, quantum-enhanced optimisation, explainable autonomous decision systems, and sustainable smart manufacturing ecosystems.
The study concludes that smart technologies and data-driven decision-making provide the technological foundation for Industry 5.0 by integrating intelligent automation, human expertise, sustainability, and multidisciplinary innovation to achieve resilient, competitive, and sustainable industrial development.
Keywords Industry 5.0, Smart Technologies, Data-Driven Decision-Making, Artificial Intelligence, Internet of Things, Digital Twin, Big Data Analytics, Smart Manufacturing, Business Intelligence, Sustainable Industry.
Field Engineering
Published In Volume 2, Issue 5, September-October 2020
Published On 2020-09-03
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