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Item Open Access Designing nickel coatings for water erosion performance: optimisation of grain size and thickness(Elsevier, 2025-06-15) Gaddavalasa, Nithin Chandra; Lodh, Arijit; Cini, Andrea; Saaran, Vinodhen; Mehmanparast, Ali; Starr, Andrew; Castelluccio, Gustavo M.Metallic coatings are gaining interest as an alternative to classical polymeric layers for erosion damage prevention due to their extended durability and sustainability. However, their implementation requires a thorough understanding of protective potential and reliability. This study explores the use of brush-plated nickel coatings on carbon-fibre reinforced composites to enhance their performance against water erosion. A combination of experimental analysis and computational modeling explores the effect of different coating thickness and properties to withstand water droplet erosion damage. Findings reveal a minimum critical coating thickness around 40 μ m can significantly improve the erosion resistance.Item Open Access High foot traffic power harvesting technologies and challenges: a review and possible sustainable solutions for Al-Haram Mosque(MDPI, 2025-04-11) Alotibi, Fatimah; Khan, MuhammadThe growing global demand for sustainable energy solutions has led to increased interest in kinetic energy harvesting as a viable alternative to traditional power sources. High-foot-traffic environments, such as public spaces and religious sites, generate significant mechanical energy that often remains untapped. This study explores energy-harvesting technologies applicable to public areas with heavy foot traffic, focusing on Al-Haram Mosque in Saudi Arabia—one of the most densely populated religious sites in the world. The research investigates the potential of piezoelectric, triboelectric, and hybrid systems to convert pedestrian foot traffic into electrical energy, addressing challenges such as efficiency, durability, scalability, and integration with existing infrastructure. Piezoelectric materials, including PVDF and BaTiO3, effectively convert mechanical stress from footsteps into electricity, while triboelectric nanogenerators (TENGs) utilize contact electrification for lightweight, flexible energy capture. In addition, this study examines material innovations such as 3D-printed biomimetic structures, MXene-based composites (MXene is a two-dimensional material made from transition metal carbides, nitrides, and carbonitrides), and hybrid nanogenerators to improve the longevity and scalability of energy-harvesting systems in high-density footfall environments. Proposed applications for Al-Haram Mosque include energy-harvesting mats embedded with piezoelectric and triboelectric elements to power IoT devices, LED lighting, and environmental sensors. While challenges remain in material degradation, scalability, and cost, emerging hybrid systems and advanced composites present a promising pathway toward sustainable, self-powered infrastructure in large-scale, high-foot-traffic settings. These findings offer a transformative approach to energy sustainability, reducing reliance on traditional energy sources and contributing to Saudi Arabia’s Vision 2030 for renewable energy adoption.Item Open Access Analysis of key challenges to implementation of FEFO in perishable food supply chain(Elsevier, 2025-06) Kandasamy, Jayakrishna; Vimal, K. E. K.; Singh, Aditya Pratap; Magnani, Aaryan; Gokhale, Ameya; Jagtap, SandeepImplementing FEFO practices has become essential for organizations globally to minimize spoilage, enhance inventory turnover, and ensure compliance with health and safety standards. To aid stakeholders in effectively adopting FEFO, it is crucial to identify and address the challenges involved in its implementation. Through an extensive literature review using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology and insights from industry experts, this study identifies thirteen core challenges that hinder FEFO adoption. PRISMA methodology was used to systematically organize the existing literature for the purpose of this study. Using tools like Decision Making Trial and Evaluation Laboratory (DEMATEL) and Total Interpretive Structural Modelling (TISM), the challenges were examined and ranked according to their interdependencies, providing insights into the cause-effect relationships among them. After applying DEMATEL, an alpha threshold value of 0.368 revealed that challenges in effective storage management are the primary barrier in implementing FEFO practices. With level partitioning, this challenge emerged as the most significant, forming the foundation for a roadmap designed to assist stakeholders. The findings from this study offer managers actionable insights for implementing effective FEFO techniques within their organizations. The study's novelty lies in its combination of DEMATEL and TISM methodologies, along with a roadmap that highlights strategic and policy-focused recommendations to support efficient FEFO adoption and the systematic study of challenges preventing effective FEFO adoption. This paper aids implementation of FEFO for better inventory control and management, reduced wastage and greater efficiency. The paper also effectively outlines and analyses the order of importance of challenges in FEFO implementation and their interdependence.Item Open Access Applications of large language models and multimodal large models in autonomous driving: a comprehensive review(MDPI, 2025-04-01) Li, Jing; Li, Jingyuan; Yang, Guo; Yang, Lie; Chi, Haozhuang; Yang, LichaoThe rapid development of large language models (LLMs) and multimodal large models (MLMs) has introduced transformative opportunities for autonomous driving systems. These advanced models provide robust support for the realization of more intelligent, safer, and efficient autonomous driving. In this paper, we present a systematic review on the integration of LLMs and MLMs in autonomous driving systems. First, we provide an overview of the evolution of LLMs and MLMs, along with a detailed analysis of the architecture of autonomous driving systems. Next, we explore the applications of LLMs and MLMs in key components such as perception, prediction, decision making, planning, multitask processing, and human–machine interaction. Additionally, this paper reviews the core technologies involved in integrating LLMs and MLMs with autonomous driving systems, including multimodal fusion, knowledge distillation, prompt engineering, and supervised fine tuning. Finally, we provide an in-depth analysis of the major challenges faced by autonomous driving systems powered by large models, offering new perspectives for future research. Compared to existing review articles, this paper not only systematically examines the specific applications of LLMs and MLMs in autonomous driving systems but also delves into the key technologies and potential challenges involved in their integration. By comprehensively organizing and analyzing the current literature, this review highlights the application potential of large models in autonomous driving and offers insights and recommendations for improving system safety and efficiency.Item Open Access Exploring circular economy in the United Kingdom based on LinkedIn data from company profiles(Elsevier, 2025-04-25) Tsironis, Georgios; Cox, Rylan; Jolly, Mark; Salonitis, Konstantinos; Tsagarakis, Konstantinos P.This work explores the landscape of Circular Economy within the business domain through an innovative approach to topic modelling applied to 1396 LinkedIn company profiles in the UK. We explore thematic structures within a dataset curated through the LinkedIn search engine prompt for companies related to the Circular Economy. Leveraging Latent Dirichlet Allocation models, we identify topics that encapsulate the essence of circular and sustainable business practices. Our findings unveil key thematic clusters, including “Waste Management and Environmental Impact,” highlighting companies at the forefront of waste reduction and eco-conscious industry practices. Another significant cluster, “Sustainable Solutions and Customer-Centric Approach,” delves into businesses seamlessly integrating sustainability across product design and customer interactions. Lastly, “Green Technology and Community Building” sheds light on companies excelling in green technology and actively contributing to environmentally responsible global networks. Topic modelling is employed as a powerful tool for unravelling complex business narratives and fostering a holistic approach to sustainable practices.Item Open Access Mapping research frontiers in gender and sustainability in agricultural development: a bibliometric review(Springer, 2025-01-01) Kumari, Anshu; Tiwari, Manish; Mor, Rahul; Jagtap, SandeepGender and sustainability are crucial in agriculture, which remains a significant source of global employment. However, urbanization, industrialization, and technological advancements have reshaped the sector, impacting labor dynamics and gender roles. Traditional agricultural labor faces challenges due to low wages, physically demanding tasks, and unfavorable working conditions. Addressing gender disparities and promoting inclusive work environments is essential for achieving sustainability. According to the ILO (International Labour Office) decent work encompasses productivity and equal employment opportunities for both genders. This study aims to review the literature on gender, sustainability and agricultural development using a bibliometric analysis of Scopus-indexed articles. The findings identify five main research domains: gender dynamics and roles, agriculture and climate change, sustainability and development, human and labor dynamics, and environmental and technological aspects. Additionally, four key scientific communities led the research: Gender studies, agricultural economics, environmental management, and rural sociology. Emerging research trends focus on gender roles in sustainable farming, environmental innovation, and labor governance in agriculture. Spain, the United Kingdom, United States, and Canada lead in knowledge production, contributing significantly to these research domains. This review highlights the importance of interdisciplinary approaches to address the complex issues of gender and sustainability in agriculture. It also specifies a target for expectations research, highlighting that the ILO’s definition of appropriate employment can guide efforts to improve gender equity and labor conditions, ultimately supporting sustainable development in the agricultural sector.Item Open Access Cyclic thermal treatment parameters of bagasse particle reinforced epoxy bio-composites for sustainable applications(Springer, 2025-03-13) Oladele, Isiaka Oluwole; Falana, Samuel Olumide; Ilesanmi; Akinbamiyorin, Michael; Onuh, Linus Nnabuike; Taiwo, Anuoluwapo Samuel; Adelani, Samson Oluwagbenga; Olajesu, Olanrewaju FavorThe demand for sustainable, high-performance materials has led to increased interest in bio-based composites. However, optimizing the mechanical properties of such materials for engineering applications remains a challenge. This study addresses this gap by developing and characterizing an epoxy-based biocomposite reinforced with sugarcane bagasse particles, focusing on the influence of cyclic thermal treatment on its properties. The bagasse particles were chemically treated with 1 M NaOH to remove impurities, improve interfacial bonding with the epoxy matrix, and enhance the overall composite performance. The treated particles j were pulverized to 470 µm and incorporated into the epoxy matrix (0–20 wt%) using the hand layup method. The composites were divided into untreated and thermally treated groups, with the latter subjected to cyclic thermal treatment (100 °C for 3 h over 7 days). Mechanical, wear, and water absorption properties were evaluated, while fractured surface morphologies were analyzed using SEM. Results revealed that cyclic thermal treatment significantly enhanced the composites’ performance, with the 15 wt% heat-treated composite showing optimal properties: density of 1.102 g/cm3, flexural strength of 29.13 MPa, ultimate tensile strength of 103.50 MPa, impact strength of 3.49 kJ/m2, hardness of 64.70 HS, and wear indices of 0.034 mg. These findings demonstrate that alkali treatment and cyclic thermal treatment synergistically enhance the performance of bio-composites, making them suitable for diverse applications, including automotive, aerospace, and other engineering fields.Item Open Access What drives Generation Z to choose green apparel? Unraveling the impact of environmental knowledge, altruism and perceived innovativeness(Taylor and Francis, 2025-01-01) Vishnoi, Sushant Kumar; Mathur, Smriti; Agarwal, Vaishali; Virmani, Naveen; Jagtap, SandeepThis study proposes to determine the influence of ‘Environmental Knowledge’ (EK), ‘Altruism’ (Atr), ‘Consumer Confidence’ (CC) and constructs of ‘Theory of Planned Behaviour’ (TPB) like Attitude” (Atd), ‘Subjective Norm’ (Sub) and ‘Perceived behavioural control’ (Pbhc) on consumers’ intention to purchase ‘Green Apparel Products’ (GAPI). Moreover, the moderating effect of ‘Perceived Innovativeness’ (PInn) on the relationship between ‘Attitude’ (Atd), ‘Subjective Norm’ (Sub), ‘Perceived behavioural control’ (Pbhc), ‘EK’, ‘Atr’ and ‘CC’ was studied. To test the research model and hypothesis, a survey of 349 Generation Z consumers (18–26 years) was conducted. Cronbach’s alpha and a ‘Confirmatory Factor Analysis’ (CFA) were used to determine the scale’s reliability and validity. ‘Structural Equation Modelling’ (SEM) validated the given model and hypotheses. In this research, six hypotheses were tested, and it was found that three hypotheses showed a direct relationship. Specifically, the result of SEM showed that ‘Atd’, ‘Sub’ and ‘CC’ were positively related to GAPI. Also, six hypotheses were formulated testing the moderating role of ‘PInn’. The results established that ‘PInn’ moderated the relationship between ‘Atd’, ‘Sub’, ‘CC’ and ‘GAPI’ significantly. This research provides a novel framework to explore the relationship between the ‘EK’, ‘Atr’ and ‘CC’ and Generation Z consumer’s ‘GAPI’.Item Open Access ROSE+ : A robustness-optimized security scheme against cascading failures in multipath TCP under LDDoS attack streams(IEEE, 2024-12-17) Nie, Jinquan; Ji, Lejun; Jiang, Yirui; Ma, Young; Cao, YuanlongMultipath TCP leverages parallel data transmission across multiple paths to improve transmission rates, reliability, and resource utilization. However, Multipath TCP faces severe network security and communication reliability challenges when exposed to low-rate distributed denial-of-service (LDDoS) attacks. In this paper, we propose a robustness optimization security scheme against cascading failures in Multipath TCP (ROSE+) to tackle the challenges posed by Low-rate Distributed Denial of Service (LDDoS) attacks on network security and communication reliability. The scheme integrates the intricate network load-capacity cascading failures model and leverages the unique characteristics of multipath TCP to facilitate the redistribution of load traffic at ineffectiveness nodes, thereby alleviating the cascading failures induced by LDDoS attack streams. Additionally, we optimize the robustness of communication transmission systems by devising a load-capacity cascading failures model. The experimental results demonstrate that the scheme reduces the probability of cascading failures by 20.07%. This research provides new ideas and methods to improve the robustness and destruction resistance of multipath TCP transmission.Item Open Access Multisensory design in memory research: the £1 coin case in the digital era(IOS Press, 2025-03-31) Ji, Yijing; Lin, Qianqian; Liu, Zhenghong; Tran, Trung Hieu; Williams, Leon; Simon, Jude; Fan, YilinThis study explores the effects of multisensory memory on memory for everyday objects, with a particular focus on memory for £1 coins. The study delves into the intersection of sensory anthropology, sensory history, and sensory sociology to examine how multisensory experiences affect memory persistence. The study used a dual-task paradigm and cross-modal stimuli to investigate the effectiveness of different sensory combinations in enhancing memory. Post-epidemic era, unlike offline experiences, this experiment utilised an online survey and a variety of media formats including text, images, video, audio and physical objects. The results showed that multisensory interactions significantly improved short-term memory recall over single-sensory modalities, while visual elements such as colours and shapes had a lasting effect on long-term memory. The study also highlights the potential of multisensory engagement in educational environments and museum experiences, gathering reliable data for future projects in which computers simulate human behaviour.Item Open Access In-situ monitoring the structural pathway of a Ti-based alloy from metallic liquid to metallic glass(Elsevier, 2025-04-25) Georgarakis, Konstantinos; Stiehler, Martin E.; Hennet, Louis; Guo, Yaofeng; Antonowicz, Jerzy; Louzguine-Luzgin, Dmitri V.; Jolly, Mark R.; Andrieux, Jérôme; Vaughan, Gavin B. M.; Greer, A. LindsayA metallic glass is formed when a molten metallic alloy is cooled rapidly enough that crystallisation is avoided. However, the way the atomic structure of the liquid converts to that of the glass is generally unknown. The main challenge is the sufficiently fast experimental acquisition of structural data in the undercooled liquid regime necessitated by the high cooling rates needed to avoid crystallisation. In the present study, using aerodynamic levitation, the Ni-free Ti-based alloy Ti40Zr10Cu34Pd14Sn2 was vitrified in-situ in a high-energy synchrotron X-ray beam while diffraction data were acquired during cooling from above the liquidus temperature Tliq to well below the glass-transition temperature Tg. The structure in the undercooled liquid regime shows an accelerated evolution. Both the local order in the short (SRO) and medium range (MRO) increases rapidly as the undercooled liquid approaches Tg, below which the amorphous structure “freezes”. Nevertheless, distinct differences between the evolution of SRO and MRO were observed. The structural rearrangements in the undercooled liquid are found to be correlated with a rapid increase in viscosity of the metallic liquid upon cooling. The new findings shed light on the evolution of the atomic structure of metallic liquids during vitrification and the structural origins of the sluggish kinetics that suppress nucleation and growth of crystalline phases.Item Open Access A comparative analysis of circular economy practices in Saudi Arabia(MDPI, 2025-04-08) Alsaud, Khalid; Assad, Fadi; Patsavellas, John; Salonitis, KonstantinosThe rise in urbanisation and resource consumption has highlighted the urgent need for sustainable economic models. The traditional linear economy, which relies heavily on non-renewable resources, exceeds the Earth’s capacity and poses significant sustainability challenges. As a result, there is an increasing necessity to transition towards a circular economy (CE) as a more sustainable alternative. Saudi Arabia, one of the world’s largest economies, is striving to implement this shift due to considerable environmental and economic challenges. However, the country currently lacks a dedicated circular economy strategy, which hinders its efforts to address issues such as waste management and excessive consumption. To bridge this gap, a comprehensive framework was developed to assess and compare Saudi Arabia’s circular economy initiatives, strategies, and policies with those of China, Japan, and Europe. Data were collected and analysed using thematic analysis, allowing for the identification of key similarities and differences between these regions. The study revealed notable variations in policies and practices, highlighting best practices that Saudi Arabia could adopt to strengthen its sustainability efforts. The findings underscore the importance of incorporating global best practices while tailoring strategies to the Kingdom’s specific needs. Policymakers and researchers in Saudi Arabia can utilise these insights to support a more effective transition towards a circular economy. Future research could adopt a quantitative approach, using indicators and metrics to enhance the impact of these findings.Item Open Access Numerical modelling on metallic materials(MDPI, 2025-04-09) Wen, Shuwen; Sun, Yongle; Chen, XinNumerical modelling of metallic materials has emerged as a pivotal research area in modern materials science and engineering [...]Item Open Access Safety evaluation of fermented and nonfermented Moringa oleifera seeds in healthy albino rats: biochemical, haematological, and histological studies(Wiley, 2025-03-24) Adetuyi, Foluso Olutope; Akintimehin, Emmanuel Sina; Karigidi, Kayode Olayele; Orisawayi, Abimbola OluwatayoFermentation preserves and enhances food properties, but consuming locally fermented foods can cause health issues like flatulence, gastrointestinal disorders, kidney stones, and sometimes death. This study evaluated the biochemical, haematological, and histological effects of supplementing diets with fermented Moringa oleifera seed (FMS) and nonfermented Moringa oleifera seed (NFMS) in healthy albino rats. Male rats were fed diets containing 10%, 20%, and 30% FMS and NFMS for 14 days. No significant changes were observed in body weight or organ/body weight ratios. However, platelet count increased significantly (p < 0.05) at higher supplementation levels, suggesting enhanced haemostatic activity. While haematological parameters remained stable, NFMS at 20% and 30% increased urea and creatinine levels, indicating potential renal stress. Histological analysis showed mild alterations at higher supplementation levels, more pronounced in NFMS‐fed rats. Fermentation mitigated antinutrient effects, enhancing safety. FMS and NFMS are safe up to 20% inclusion, with potential applications in human nutrition and functional food development.Item Open Access Assessment of fatigue crack initiation after overloads with substructure-sensitive crystal plasticity(Elsevier, 2025-09) Dindarlou, Shahram; Castelluccio, Gustavo M.Microstructure-sensitive fatigue initiation prognosis approaches typically assume uniform periodic loading and often overlook in-service overloads, which increase uncertainty and reduce life prediction accuracy. Similarly, certification efforts rarely evaluate experimentally the impact of different overloads due to the prohibitive costs. Therefore, predictive models that estimate overload effects on fatigue initiation damage without extensive experimental data are valuable to improve prognosis approaches. However, the literature lacks microstructure-sensitive approaches capable of assessing overload effects with models that simultaneously predict monotonic and cyclic responses without recalibration. This work presents a novel strategy to predict the effects of overloads on early cyclic damage by evaluating the refinement dislocation structures. A substructure-based crystal plasticity approach relies on independent parameterizations from monotonic and cyclic loading to predict overload responses, without requiring additional experiments. The model agreement with macroscale experiments was further validated by comparing dominant mesoscale structures after overloads in single- and poly-crystals for metals and alloys. The analysis also identified overload-resistant crystal orientations and demonstrated that overloads increase the likelihood of initiating fatigue cracks in low apparent Schmid factor grains under low-amplitude fatigue. We conclude by discussing the value of material-invariant mesoscale parameters to rank overloads effect for materials and loading conditions for which no experiments are available.Item Open Access Optimizing industrial etching processes for PCB manufacturing: real-time temperature control using VGG-based transfer learning(Springer, 2025-04-01) Luo, Yang; Jagtap, Sandeep; Trollman, Hana; Garcia-Garcia, Guillermo; Liu, Xiaoyan; Abdul Majeed, Anwar P. P.Accurate temperature control in Printed Circuit Board (PCB) manufacturing is essential for maintaining high-quality etching results. Automated monitoring using machine vision and deep learning offers an effective approach for this task. This study investigated a feature-based transfer learning technique for classifying temperature readiness in infrared images of the etching process. The captured dataset containing 470 ‘Production-Ready’ and 480 ‘Not-Ready’ infrared images of the etchant tank was utilized. Pre-trained Visual Geometry Group (VGG) Convolutional Neural Network (CNN) models, specifically VGG16 and VGG19, were employed to extract discriminative features from these images. Logistic Regression (LR) classifiers were then trained on these features to classify the infrared images. The performance of the VGG16-LR and VGG19-LR pipelines was evaluated on training, validation, and test sets using a 60:20:20 split. While both pipelines achieved 100% accuracy on the training sets, the VGG19 pipeline showed exceptional performance, achieving a validation accuracy of 95%, and a test accuracy of 99%. The VGG16 pipeline also demonstrated robust performance, achieving 96% accuracy on both the validation and test sets. Considering the dimensions and the overall efficiency of the pipeline, it was determined that the VGG19-LR model was appropriate for the captured dataset. The high accuracy indicates that transfer learning is suitable for categorizing temperature fluctuation in infrared thermography, as opposed to training a deep neural network from scratch. Computer vision and deep learning provide automated and precise temperature management during the etching process, leading to enhanced efficiency in PCB manufacturing.Item Open Access “In-situ” x-ray imaging technology for material and manufacturing science: a review(Elsevier, 2025-05-15) Nguyen, Van Anh; Le, Duy Han; Damian, Dilen; Tran, The Bach; Le, Quang Hung; Nguyen, Nhu Tung“In-situ” X-ray imaging has become a powerful tool in materials and manufacturing science, enabling real-time observation of critical processes. However, access to X-ray facilities remains highly competitive due to limited availability, high operational costs, and technical complexity, restricting its use to a few research groups worldwide. This review addresses this challenge by providing a comprehensive analysis of X-ray imaging technologies, their historical development, and recent advancements in “in-situ” X-ray imaging. It explores applications across various materials and manufacturing processes, including welding, additive manufacturing (AM), casting, high-temperature furnaces, and novel materials. Key topics such as heat transfer, melt pool dynamics, solidification, microstructure evolution, and defect formation in manufacturing processes are systematically examined. Additionally, the review highlights the potential of “in-situ” X-ray imaging for discovering novel materials and advancing manufacturing technologies. It discusses current limitations, particularly the constraints of existing X-ray facilities, and outlines future directions for enhancing this technology. Expanding access to high-resolution X-ray imaging is crucial for accelerating advancements in materials and manufacturing. Integrating artificial intelligence and simulation models will further enhance its capabilities. Achieving these improvements requires upgrading existing X-ray facilities and developing new systems capable of capturing high-resolution, real-time imaging of complex material processes.Item Open Access Impact of cold-wire gas metal arc welding (CW-GMAW) parameters on microstructure and microhardness characteristics in repairing S275JR structural steel(Springer, 2025-03-23) Musa, Zahraddeen; Ganguly, Supriyo; Suder, Wojciech; Igwemezie, Victor; Rajamudili, KuladeepThis study investigates the influence of adding a cold wire during gas metal arc welding (CW-GMAW) for repair of S275JR structural steel. The research is aimed at improving repair productivity through increased deposition rates with enhanced performance. During weld repair, multiple passes induce large number of thermal cycles and a huge thermal gradient on the material which has an adverse effect on the material’s properties. This is largely due to the microstructural changes that occur during the process. In this work, a systematic approach has been adopted to explore the effects of varying gas metal arc welding (GMAW) parameters, including wire feed rate, welding current, voltage, travel speed, and specifically cold-wire feed speed on the heat affected zone (HAZ) microstructure and hardness. Macrostructural examination highlights significant alterations in the heat affected zone (HAZ) region, with marked microhardness changes in both WM and HAZ. Cold-wire addition led to a reduction in the HAZ area, depth of weld metal penetration, and significantly reduced the impact of imposing thermal cycles on the HAZ of the welded samples. Additionally, microstructural analysis was conducted using a standard optical microscope to correlate the observed hardness variations with microstructural transformations in the weld metal and heat affected zone (HAZ). The findings reveal that specific combinations of CW-GMAW parameters can significantly influence the microstructure and thereby hardness, suggesting that with careful control of these parameters, it would be possible to do faster repair with minimal loss of integrity for critical structural steels.Item Open Access Food loss and waste reduction by using Industry 4.0 technologies: examples of promising strategies(Oxford University Press (OUP), 2025-01-06) Arshad, Rai Naveed; Abdul-Malek, Zulkurnain; Parra-López, Carlos; Hassoun, Abdo; Qureshi, Muhammad Imran; Sultan, Aysha; Carmona-Torres, Carmen; de Waal, Jennifer Mignonne; Jagtap, Sandeep; Garcia-Garcia, GuillermoFood loss and waste (FLW) represent a significant global issue, posing a threat to food sustainability on a worldwide scale. However, the growing awareness among consumers and the development of emerging technologies driven by the Fourth Industrial Revolution (Industry 4.0) present numerous opportunities to reduce FLW. This article provides a comprehensive examination of recently developed strategies for reducing FLW. The role of Industry 4.0 technologies, such as the Internet of Things, artificial intelligence, cloud computing, blockchain, and big data, is highlighted through examples of various promising initiatives. The results of this analysis show that the application of digital technologies to address the issue of FLW is on the rise globally, with Industry 4.0 technologies revolutionising many sectors, including the food sector. Further research is necessary, and closer collaboration between producers, distributors, consumers, and other actors involved in the food supply chain is still required to reduce FLW further.