The advent of Industry 5.0 represents a transformative shift towards integrating advanced computational technologies—such as AI, IoT, robotics, and big data—with human-centric collaboration to achieve sustainable fo...
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The advent of Industry 5.0 represents a transformative shift towards integrating advanced computational technologies—such as AI, IoT, robotics, and big data—with human-centric collaboration to achieve sustainable food production systems. This systematic review examines the link between Industry 5.0 and sustainability, focusing on computational innovations, resource management, and eco-friendly practices within food industries. The study addresses the pressing challenge of balancing industrial growth with environmental stewardship and identifies the untapped potential of Industry 5.0 to enhance food safety, reduce waste, and enable personalized food solutions. Using a qualitative methodology, the review synthesizes findings from scholarly articles, industry reports, and case studies to analyze applications of smart sensors, blockchain, and robotics in optimizing supply chains, precision farming, and vertical agriculture. Results indicate that Industry 5.0 facilitates real-time monitoring, predictive analytics, and adaptive production, improving resource efficiency and minimizing environmental impacts. Smart packaging, digital twins, and AR are highlighted as emerging tools for enhancing traceability, quality control, and consumer engagement. However, high implementation costs, data management challenges, and the need for policy frameworks emerge as critical barriers. The discussion emphasizes how these challenges can be mitigated through multidisciplinary research, cross-sector collaboration, and government incentives. Overall, Industry 5.0 offers a pathway to sustainable, efficient, and personalized food systems by leveraging cutting-edge technologies while fostering human-machine collaboration. Future research should focus on scalable applications, cost-effective solutions, and regulatory alignment to accelerate Industry 5.0 adoption in food sectors. This study underscores the urgency of advancing computational technologies to shape resilient and sustainable food p
This paper presents a comprehensive review of the latest developments in fuzzy logic (FL) applications across critical domains which include energy harvesting (EH), ambient conditioning systems (ACS), and robotics and...
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This paper presents a comprehensive review of the latest developments in fuzzy logic (FL) applications across critical domains which include energy harvesting (EH), ambient conditioning systems (ACS), and robotics and autonomous systems (RAS), highlighting FL's capability to address nonlinearities and uncertainties in diverse technological environments. Through a detailed comparative analysis of research trends over the past decade, it underscores the increasing significance of FL in EH and RAS, contrasting with the sustained interest in ACS. Furthermore, the evaluation of different fuzzy inference systems across domains provides valuable insights into their specific strengths and limitations, aiding researchers and practitioners in making informed decisions aligned with their application needs. Additionally, the paper explores advanced modifications and hybridizations of FL, such as swarm intelligence and integrations with other control strategies, emphasizing the necessity for robust and adaptive FL systems. The review also identifies key open problems and potential research directions, such as the demand for adaptive FL systems in EH and advanced optimization techniques in ACS and RAS. Overall, this state-of-the-art review not only summarizes the current state of FL applications but also outlines a roadmap for future research, offering valuable insights for advancing FL's role in handling uncertainties and nonlinearities in complex systems.
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