Search Results (1,659)

Transforming a conventional university campus into a smart campus by leveraging modern technologies aims to deliver university services efficiently, effectively, and at low cost. Modern technologies enhance campus life by providing services, such as smart classrooms and campus security, on demand. Seamless service delivery requires reliable and efficient access to the services that take into consideration the dynamic contextual attributes related to, e.g., end-device mobility, latency sensitivity, and resource constraints. University staff, students, and visitors frequently submit different types of service requests on the move, which requires a robust orchestration framework capable of managing these requests across edge-cloud environments. The orchestration framework needs to intelligently distribute the workload, taking into consideration the latency sensitivity requirements and contextual conditions, including resource constraints. Therefore, a fuzzy-logic orchestration framework for smart-campus environments in edge-cloud architecture is proposed. The framework incorporates key factors, including user speed, resource utilization, and request delay sensitivity, in the decision-making process to satisfy both service consumers and service providers. It prioritizes latency-sensitive requests while simultaneously enhancing resource utilization efficiency. Simulation-based experimental results demonstrate the effectiveness of the proposed framework compared with benchmark approaches in orchestrating incoming workloads under several user and contextual conditions. Additionally, the results show that the proposed framework improves the execution rate by 30% compared to benchmark models and achieves more than double resource utilization efficiency. Full article

Yam is a tuberous crop with great potential for enhancing food security and rural development thus contributing significantly to the lives of people in production areas. Despite its importance, productivity is low, with poor adoption rates of released commercial varieties. Yam exhibits complex growth patterns, including tuberization and dormancy. The yield, food quality and consumer preferences differ by variety. Understanding the dynamics of yam production system and best practices is critical for its improvement. Our review delved into the flowering dynamics as well as yield determinants. We dissected the phenomena of dormancy, photosynthesis, photoperiodism and food quality with a view to adding values on crop improvement efforts. Yam production systems can be repositioned to play a greater role in sustainable food security and poverty alleviation through the development and deployment of more productive, profitable and resilient yam varieties and sustainable technologies that will improve the current yam cropping system and value chain. Future research perspectives focusing on yield improvement, climate-smart adaptations/cultivation practices, and value chain development to ensure sustainable yam production and utilization are thus highlighted. Full article

The fashion industry’s business is becoming increasingly complicated and active. This industry is expected to be highly competitive, particularly in the retail sector. Therefore, this research aims to examine the impact of supply chain information sharing and quality management on firm performance, with supply chain agility as a mediating variable, in the Asian fashion industry. A total of 169 participants from the fashion sector in a developing country were surveyed. The proposed hypotheses were examined using a quantitative approach, employing Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS to assess and validate the measurement model. The results indicate that supply chain information sharing and quality management have a significant impact on a firm’s performance. Similarly, the sharing of supply chain information and quality management has a significant impact on firm performance by mediating supply chain agility. The study offers actionable insights for managers in volatile fashion supply chains. Firms can enhance performance by sharing real-time demand and inventory information, strengthening key quality practices, and adopting flexible, data-driven production processes. Integrating information sharing, quality management, and agility enables faster responses to shifting consumer trends, thereby improving overall competitiveness in fast-fashion environments. This study offers valuable guidance for supply chain professionals seeking to enhance practices within their networks. The results underscore the strategic importance of information sharing and quality management in promoting agility, an essential capability for achieving a competitive advantage. Additionally, the insights generated are relevant to practitioners, policymakers, and industry leaders aiming to strengthen supply chain responsiveness and resilience. Full article

HRC is increasingly adopted in industrial and logistics environments, while workforce preparation often remains constrained by instructional approaches that provide limited embodied understanding of safety and ergonomics. This study examines the architectural design and system integration of a modular, human-centred XR platform intended to support safe and ergonomics-aware collaboration within smart logistics contexts. The proposed system integrates XR training scenarios deployed on consumer-grade hardware and follows a structured pedagogical progression from conceptual familiarisation through experiential task execution to reflective ergonomic evaluation. Multimodal feedback mechanisms based on posture-oriented guidance, attention-aware interaction design, and context-sensitive safety cues are incorporated without reliance on intrusive sensing technologies. A structured evaluation framework is defined to examine usability, task performance, and ergonomics-aligned posture indicators using standardised instruments and system-generated telemetry. The architectural design indicates that the framework supports scalable deployment, consistent interaction fidelity, and privacy-conscious data handling across educational and vocational settings. The proposed framework suggests that human-centred XR architectures can strengthen safety-oriented and ergonomically informed HRC within Industry 4.0 logistics environments. Full article

The increasing penetration of intermittent renewable energy demands innovative solutions to maintain grid stability, resilience, and security in the body of smart cities. This paper presents a novel framework that redefines Bitcoin mining as a form of virtual energy storage, a flexible and controllable load capable of delivering large-scale demand response services, positioning it as a competitive alternative to traditional energy storage systems, including electrical, mechanical, thermal, chemical, and electrochemical storage solutions. By strategically aligning mining activities with grid conditions, Bitcoin mining can absorb excess electricity during periods of oversupply, converting it into digital assets, and reduce operations during times of scarcity, effectively emulating the behavior of conventional energy storage systems without the associated capital expenditures and material requirements. Beyond its operational flexibility, this paper explores the cyber–physical benefits of integrating Bitcoin mining into the power transmission systems as a defensive mechanism against false data injection (FDI) cyberattacks in smart city infrastructure. To achieve this goal, a decentralized and adaptive control strategy is proposed, in which mining loads dynamically adjust based on authenticated grid-state information, thereby improving system observability and hindering adversarial efforts to disrupt state estimation. In addition, to handle the proposed approach, this paper introduces a high-performance algorithm, a combination of quantum-augmented particle swarm optimization and wavelet-oriented whale optimization (QAPSO-WOWO). Simulation results confirm that strategic deployment of mining loads improves grid sustainability by utilizing curtailed renewables, enhances resilience by mitigating load-generation imbalances, and bolsters cybersecurity by reducing the impacts of FDI attacks. This work lays the foundation for a transdisciplinary paradigm shift, positioning Bitcoin mining not as a passive energy consumer but as an active participant in securing and stabilizing the future power grid in smart cities. Full article

Remote photoplethysmography (rPPG) enables non-contact vital sign measurements using standard smart device cameras, opening up the potential of scalable health applications on consumer smart devices. However, rPPG signal quality is highly sensitive to camera sensor characteristics and image processing pipelines, which can vary between devices. This variation limits reproducibility and generalisation of rPPG-based algorithms beyond specific hardware platforms. This work presents a reproducible test environment for the validation of the camera sensor response in the context of rPPG signals. A microcontroller-driven illumination system and mechanically constrained setup are used to generate controlled, repeatable optical signals. Two characterisation tests are introduced: a time domain morphology analysis and a frequency domain attenuation analysis. Pulse timing consistency, pulse waveform morphology and normalised frequency responses are compared to assess sensor similarity. This method is applied to selected consumer devices and demonstrates consistent camera response patterns under the controlled test conditions. By explicitly addressing validation of the camera sensor and image processing pipeline, this work supports the development of more robust and transferable rPPG-based vital sign applications across a wider range of consumer devices. Full article

The increasing diffusion of plant-based milk alternatives poses new challenges at the intersection of food safety and consumer experience, particularly regarding allergen cross-contamination and beverage performance during preparation. Traditional quality control strategies are typically confined to upstream production stages and are unable to address individualized risks and sensory variability at the point of consumption. In this study, we propose an embedded volatilomic sensing approach that combines metal oxide semiconductor (MOX) sensor arrays with lightweight artificial intelligence algorithms to enable real-time, on-device decision-making. The volatilome of four commercially available plant-based milk beverages (oat, almond, soy, and coconut) was characterized using GC–MS/SPME as a reference method, while a MOX-based electronic nose provided rapid, non-destructive sensing of volatile fingerprints. Linear Discriminant Analysis demonstrated clear discrimination among beverage types based on their volatile signatures, supporting the use of MOX sensor arrays as functional descriptors of compositional identity and process-related variability. Beyond beverage classification, the proposed framework is designed to support future implementation of (i) screening for anomalous volatilomic patterns potentially compatible with accidental cow’s milk carryover in shared preparation settings and (ii) adaptive tuning of preparation parameters (e.g., foaming-related settings) in smart beverage systems. The results highlight the role of embedded volatilomic intelligence as a unifying layer between personalized risk-aware screening and sensory-oriented process control, paving the way for intelligent food-processing appliances capable of autonomous, real-time adaptation at the point of consumption. Full article

This study investigates how innovative social media marketing activities influence consumer inspiration, food pleasure, and behavioral intentions in the context of hedonic food consumption and digital marketing innovation. Data collected from 425 consumers who had tried Dubai chocolate products in Türkiye were analyzed using the partial least squares structural equation modeling (PLS-SEM) method with SmartPLS 4 software. The results indicate that personalization, trendiness, and advertisement dimensions significantly enhance consumer inspiration, whereas entertainment and interaction dimensions show no significant effects. Consumer inspiration positively influences repurchase intention, recommendation intention, willingness to pay more, and food pleasure. Furthermore, food pleasure exerts a significant positive effect on recommendations and willingness to pay more but not on repurchase intention. Mediation analysis revealed that food pleasure partially mediates the relationships between consumer inspiration, recommendation intention, and willingness to pay more, whereas no mediating effect was found for repurchase intention. These findings contribute to innovation and knowledge literature by demonstrating how digital marketing activities foster emotional engagement, enhance consumer experiences, and promote sustainable behavioral intentions in the hedonic food sector. Full article

Present-day artificial intelligence systems (AI), virtual assistants, and devices connected to the Internet of Things (IoT) are playing an increasingly important role in decision-making processes in the everyday lives of individuals and daily operations of organizations. In this respect, the users’ trust is a key factor determining their acceptance and effective use. In contemporary digital ecosystems, this trust increasingly becomes a component of sustainable digital marketing, in which transparent data practices and responsible communication shape long-term consumer–technology relationships. This paper analyzes the halo effect as a psychological mechanism affecting the perception of competences, reliability, and ethics in the case of technologies based on AI. Based on the literature on behavioral economics, it was shown how positive associations with the interface, brand, or previous experience of the user may lead to excessive trust in technology. Such mechanisms also play a significant role in shaping sustainable consumption patterns, as users—guided by cognitive shortcuts—can adopt technologies in ways that either strengthen or weaken responsible digital behaviors. Moreover, the potential risks associated with this phenomenon were also indicated. The aim of this paper was to present how the utilization of the halo effect influences the generation of trust in smart systems and the formulation of implication for management practices and technology design. These implications are increasingly important in the context of sustainable digital marketing policy, where organizations must align persuasive communication with ethical standards and with rising expectations regarding sustainable digital transformation. Relationships between variables were analyzed using structural equation modeling (SEM), making it possible to verify complex dependencies between the perceived image of technology, the halo effect, and the users’ trust. This study tested three core hypotheses regarding the halo effect’s role, the foundational importance of security, and the mediating function of trust in technology adoption. The results of these analyses indicate that the halo effect significantly affects the level of trust in each of the investigated areas, with the strongest effect observed in the case of virtual assistants, where perception of the human-like characteristics of the interface considerably strengthened trust in the competences and reliability of the system. This finding has particular relevance for AI-driven personalization mechanisms, which increasingly guide consumer decision-making and shape their long-term behavioral patterns in online environments, with direct implications for sustainable consumption. This paper provides contribution to innovation management and technical marketing, stressing the importance of cognitive and emotional factors in the acceptance of new technologies. At the same time, it highlights the theoretical need to integrate responsible AI design with sustainable digital marketing strategies The findings suggest that ensuring trust, once established, has the potential to support not only technological innovation but broader societal goals related to responsible consumption, environmental stewardship, and long-term digital well-being aligned with sustainable development principles. However, this study stops short of empirically measuring sustainable consumption behaviors, offering instead a conceptual link that requires further empirical validation. Full article

At present, the global logistics sector faces critical challenges, including rising energy costs and pressure to reduce CO₂ emissions. Traditional linear supply chains are becoming inefficient, necessitating a transition toward shared logistics based on the principles of the sharing economy. This paper presents a progressive three-layer architecture that transforms conventional reactive data collection into an autonomous, proactive management system for the distribution of consumable materials. While previous research established foundations in IoT connectivity for smart vending machines, this study advances the process by integrating an intelligent layer of artificial intelligence (AI) algorithms. The framework utilizes Long Short-Term Memory (LSTM) neural networks for demand forecasting, dynamic route optimization (VRP/ACO) for replenishment, and Isolation Forest/DBSCAN algorithms for real-time anomaly detection. To evaluate the framework, a numerical simulation was conducted using representative pilot scenarios. The results indicate that within the simulated environment, the system achieves over 95% accuracy in inventory depletion prediction (MAPE = 4.02%). In these analyzed instances, this leads to a 25–30% reduction in stock-out risks and a 25% reduction in replenishment distance. These findings demonstrate the significant potential for reducing operational costs and carbon footprints in green logistics. The study confirms that the synergy between IoT infrastructure and AI-driven analysis provides a robust foundation for transitioning from static methodologies to resilient, collaborative logistics ecosystems. Full article

Integrating third-party Machine Learning (ML) models into industrial Operational Technology (OT) creates a procurement deadlock: operators cannot verify vendor performance claims without sharing representative evaluation data with vendors, while vendors refuse to reveal proprietary model weights before purchase, rendering traditional safeguards such as Non-Disclosure Agreements technically unenforceable. This paper introduces a framework combining Zero-Knowledge Proofs (ZKPs) with smart contracts to enable trust-minimized, cryptographically verifiable competitive model procurement in Industrial Cyber-Physical Systems (ICPS). Vendors cryptographically prove that their model outperforms a legacy baseline without disclosing proprietary weights, a process we term cryptographic performance attestation, while the on-chain workflow automates escrow, proof verification, and best-vendor selection with arbiter-based dispute resolution. ZKP privacy is scoped to vendor model weights; operator-side evaluation-data confidentiality is managed separately via synthetic, de-identified, or public benchmark data. We analyze three ZKP workflow variations and evaluate them on consumer-grade hardware, achieving proving times of approximately three seconds and sub-dollar on-chain verification costs under Layer-2 fee assumptions for the recommended single-proof variation, while identifying computational trade-offs of recursive proof aggregation. The entire verification phase operates offline with no impact on real-time OT control paths, bridging the IT/OT pre-transaction trust gap while deferring artifact deployment to existing OT tooling. Full article

This study examines whether moral identity, perceived environmental responsibility, and locus of control predict green consumption behaviour among young consumers. Adopting a quantitative approach, the study follows an explanatory research design grounded in the positivist paradigm. Primary data were collected through a self-administered questionnaire delivered to respondents aged 18–35 years. Descriptive statistics were analysed using the Statistical Package for the Social Sciences (SPSS) version 30, while inferential analysis was conducted using Structural Equation Modelling (SEM) via SmartPLS 4. The findings suggest that moral identity and perceived responsibility for environmental damage are significant predictors of green consumption among youth. In contrast, locus of control shows a weak, statistically insignificant association with green consumption behaviour. After controlling for demographic variables, including gender, age, race, education, occupation, and income, the results indicate that only education level and race make significant contributions to the model. Notably, the effect of moral identity becomes insignificant once demographic factors are considered, while locus of control remains insignificant. However, perceived environmental responsibility not only retains its significance but also demonstrates a strengthened effect on green consumption behaviour. These findings highlight the persistence of the attitude–behaviour gap in sustainable consumption among young consumers, particularly in rural contexts. The study contributes to the literature by extending the Theory of Planned Behaviour through the incorporation of moral and psychological constructs within a rural African setting. Practically, the study offers insights for policymakers, educators, and marketers, emphasising the importance of environmental education, moral reinforcement, and targeted behavioural interventions to enhance youth participation in sustainable consumption practices. Full article

The incorporation of probiotic bacteria into active packaging systems represents an innovative strategy to enhance food preservation while delivering health benefits to consumers. This review discusses the selection criteria for probiotic strains focusing on their resistance to environmental stressors, antimicrobial activity, and viability in different food matrices and their integration into edible films and coatings. Polysaccharides, proteins, and hydrocolloids are widely used as biopolymeric matrices due to their biocompatibility and functional properties. The efficiency of probiotic packaging largely depends on three factors: the choice of strain, the encapsulation technique (such as spray drying, emulsification, or electrospinning), and the properties of the matrix material. These packaging systems demonstrate strong antimicrobial activity through multiple mechanisms, including bacteriocin production, competition for adhesion sites, and acidification. Applications in dairy, meat, fish, and fresh produce reveal the potential of these technologies to delay spoilage, reduce pathogenic microorganisms, inhibit lipid oxidation, and maintain nutritional and sensory qualities. Moreover, studies emphasize that combining probiotics with prebiotic compounds can improve both microbial stability and functional performance. Despite promising results, challenges remain regarding the industrial scalability and long-term stability of these systems under varied storage conditions. Future research should focus on optimizing formulation parameters, expanding applications across diverse food categories, and integrating smart packaging technologies. Altogether, probiotic-based edible packaging aligns with current demands for sustainable, health-oriented food solutions. Full article

Due to environmental challenges, the global luxury hospitality industry faces increasing pressure to reduce its consumption of natural resources while maintaining service quality. In this paper a conceptual study is conducted to identify three primary problems of the tourism industry and highlight their impact on sustainable water resources and ecosystems: excessive water, electricity and towel/linen consumption in luxury hotels and resorts. This paper proposes a solution that uses a digital smart meter system linked to guest rooms. It is activated upon check-in, and guest participation is optional. It uses tangible or intangible incentives—such as discounts upon departure for future stays or for hotel laundry/meals/beverages—that rationalize consumption without affecting the quality of basic services. This approach may be implemented either independently by a single hotel or collaboratively through strategic alliances among multiple hotels, thus enabling customers to redeem their incentives/credits at any participating property. Guests are grouped into three consumption levels: high-saving guests (high incentives), average-saving guests (average incentives) and third-level guests (low/below-average incentives). Adopting this approach helps luxury hotels/resorts reduce their operational costs and enhance their image by applying green marketing in practice. Moreover, this conceptual paper proposes the provision of badges, including international environmental certifications, to hotels that adopt this responsible approach. This mechanism is a modern model that directly benefits all involved parties: service providers, customers/guests, environmental organizations and the environment. Full article

Facial cosmetics are undergoing a significant transformation driven by scientific innovation, consumer awareness, and a growing demand for personalized and sustainable solutions. This article explores the latest developments in active ingredients, such as exosomes, growth factors and cosmeceuticals, alongside the rise of smart skincare technologies, including AI-based diagnostics and connected beauty devices. It also examines evolving consumer preferences, with a focus on transparency, skin health, and environmentally conscious formulations. Together, these trends are shaping a new era in facial cosmetic care, where efficacy, safety, and sustainability converge. Full article