The purpose of this study is to develop and validate a System Dynamics (SD) model that illustrates how Artificial Intelligence (AI), including generative AI, alters project lifecycle behavior under a hybrid agile–predictive governance approach....
Lifecycle management of the conversational AI agent, in the case of Copilot Studio and Dataverse as enabling technologies, is discussed in this paper. After an in-depth examination of the academic literature, policy reports, and lifecycle models, the...
Artificial intelligence (AI) is rapidly transforming healthcare through applications in clinical decision support, diagnostic imaging, population health management, and workflow optimization. Despite these advances, real-world deployment continues to...
The rapid expansion of artificial intelligence (AI) systems has intensified concerns regarding their energy consumption and carbon footprint, raising questions about whether efficiency-focused strategies under the Green AI paradigm are sufficient to...
Artificial intelligence (AI) systems for biomedical diagnostics are usually evaluated on predictive performance, yet clinical adoption also depends on reliability under distribution shift, interpretability, safety behaviour, equity across subgroups,...
Healthcare AI is becoming continuous rather than episodic, and the carbon and e-waste costs of this shift are rarely priced into architectural decisions. Federated learning (FL) keeps sensitive data local but can increase infrastructure demand. We fo...
Background: Clinical artificial intelligence (AI) is rapidly moving from retrospective model development into prospective evaluation, implementation, and routine care. Existing reviews have addressed specific aspects of this transition, including mon...
Buildings significantly contribute to global energy consumption and greenhouse gas emissions. This systematic literature review explores the potential of artificial intelegence (AI) to enhance sustainability throughout a building’s lifecycle. T...
In recent years, the application of artificial intelligence (AI) technology in the construction industry has rapidly emerged, particularly in areas such as site monitoring and project management. This technology has demonstrated its great potential i...
Corrosion in infrastructure creates high-risk scenarios, and mitigation strategies are expensive, with significant annual costs globally. This paper advances the discourse of corrosion monitoring and tracking in infrastructure, emphasizing the import...
Rapidly evolving family structures have intensified the demand for residential layouts that can flexibly adapt to diverse spatial and functional needs. Conventional design approaches, whether manual or computer-aided, often fail to maintain user-cent...
The advancements in human-centered artificial intelligence (HCAI) systems for Industry 5.0 is a new phase of industrialization that places the worker at the center of the production process and uses new technologies to increase prosperity beyond jobs...
Considering the current prediction from the Food and Agriculture Organization, food production needs an increase of over 70 percent by 2050, and the agriculture sector requires a boost that is also obtained by integrating novelty technologies and met...
Despite the increasing prevalence of artificial intelligence (AI) ethics frameworks, the practical application of these frameworks in industrial settings remains limited. This limitation is further augmented in energy systems by the complexity of sys...
Background/Objectives: Clinical artificial intelligence (AI) is increasingly moving from proof-of-concept development into clinical evaluation, regulatory review, and routine care. This scoping review aimed to map and synthesise empirical evidence on...
Modern machine learning approaches for vulnerability detection achieve strong performance within specific datasets, yet their reliability degrades under domain shift, limiting their effectiveness for real-world secure software development lifecycle (...
The emerging capabilities of artificial intelligence (AI) and the systems that employ them have reached a point where they are integrated into critical decision-making processes, making it paramount to change and adjust how they are evaluated, monito...
AI is being deployed in smart-grid and smart-city energy infrastructure faster than governance frameworks can validate it. Existing instruments—NERC CIP, NIST AI RMF 1.0, and ISA/IEC 62443—address cybersecurity compliance and AI trustwort...
The emergence of effective Generative AI has sparked a revolution in video game development, enabling us to generate game assets and source code at a fraction of the cost and time needed compared to if human developers were involved. But the support...
Due to the recent rapid development of artificial intelligence (AI) and its expanding impact on the planet, green and sustainable AI research has increasingly gained attention. This systematic literature review searches main databases, including Scop...
AI technologies are becoming operational components of urban infrastructure systems, including transport networks, structural health monitoring platforms, water utilities, energy systems, and public facilities. These systems support prediction, diagn...
There are quite some machine learning (ML) models, frameworks, AI-based services or products from different IT solution providers available, which can be used as building blocks to embed and use in IT solution architectures of companies. However, the...
Agentic AI can coordinate distributed energy resources, invoke tools, revise plans, and act through multiple interacting agents. In critical energy systems, however, model-level explainable artificial intelligence (XAI) cannot reveal how goals, const...
Artificial intelligence (AI) is increasingly embedded within organizational infrastructures, yet the foundational role of data in shaping AI outcomes remains underexplored. This study positions data at the center of complexity, uncertainty, and strat...
Conventional hazard and operability (HAZOP) studies remain central to process safety management, but their periodic, document-centered implementation and dependence on expert judgment limit their ability to track dynamic operational risk across the f...
Generative artificial intelligence (GenAI) can accelerate Building Information Modeling (BIM) and digital-twin workflows, but probabilistic outputs and manipulated inputs create data-integrity risks that conventional construction-software liability r...
This research investigates using Polyether ether ketone (PEEK) in dental prosthetics, focusing on enhancing the mechanical properties, adhesion capabilities, and environmental sustainability through AI-driven data analysis and advanced surface treatm...
Public organisations are increasingly using Artificial Intelligence (AI) and Algorithmic Decision-making Systems (ADSs), but the rules and governance requirements that apply to them remain spread across different legal and risk-management frameworks....
Sustainable and resilient communities increasingly rely on interdependent, data-driven building systems where material choices, energy performance, and lifecycle impacts must be optimized jointly. This study presents a digital-twin-ready, system-of-s...
Large language models (LLMs) are increasingly relevant to Business Process Management (BPM), particularly when process knowledge is dispersed across documents, conversations, and other unstructured sources. Their probabilistic outputs, however, raise...
Background: Artificial-intelligence-based diagnostic systems increasingly influence healthcare delivery, yet strong aggregate performance can coexist with clinically meaningful disparities across demographic subgroups. Such disparities raise not only...
The software engineering landscape is undergoing a significant transformation with the advent of artificial intelligence (AI). AI technologies are poised to redefine traditional software development practices, offering innovative solutions to long-st...
Artificial intelligence is increasingly deployed where direct observation, reliable ground truth, and repeatable experimentation are structurally unavailable, and pipelines resting on an externally verifiable reference fail by design. This work intro...
Reliable schedule-risk estimation in hybrid software development lifecycles is strategically important for organizations adopting AI in software engineering. This study addresses that need by transforming routine process telemetry (CI/CD, SAST, trace...
Traditional construction safety management, reliant on manual inspections and heuristic judgments, increasingly fails to address the dynamic, multi-dimensional risks of modern projects, perpetuating fragmented safety governance and reactive hazard mi...
Under the global impetus toward carbon peak and carbon neutrality, large-scale renewable energy integration has become a key driver in transforming traditional power grids into new power systems. Meanwhile, the growing adoption of advanced artificial...
Current ML lifecycle frameworks provide limited support for continuous stakeholder alignment and infrastructure evolution, particularly in sensor-based AI systems. We present CAPTURE, a seven-phase framework (Consult, Articulate, Protocol, Terraform,...
Software supply chain vulnerabilities in Safety-Critical Cyber–Physical Systems demand more than a static Software Bill of Materials; decision makers need traceable links among build artifacts, vulnerabilities, deployment context, and remediati...
Accurate energy forecasting is essential for maintaining power system reliability, integrating renewable generation, and ensuring market stability. Although machine learning has improved forecasting accuracy, its operational deployment depends on Mac...
Manufacturing systems are undergoing a fundamental transition as efficiency-driven optimisation paradigms prove increasingly inadequate for meeting net-zero, resource-efficiency, and resilience objectives. Digital twins have emerged as a central enab...
Background: Artificial intelligence (AI) is transitioning from experimental pilots to core public health functions such as disease surveillance, resource planning, and analysis of social and structural determinants of health. Yet, health data collect...
The digital transformation of the Architecture, Engineering and Construction sector is accelerating the adoption of digital platforms as critical enablers of data integration, stakeholder collaboration and process optimization. This paper presents a...
Network slicing (NS) plays a vital role in enabling flexible and efficient resource allocation, tailored to diverse use cases and network domains. This survey paper explores the synergy between NS and Artificial Intelligence (AI), emphasizing how Mac...
Air pollution imposes a substantial economic burden globally, with estimated annual losses exceeding $8.1 trillion due to healthcare costs, lost productivity, infrastructure degradation, and agricultural damage. This review assesses the economic effe...
Modern Internet of Things (IoT) systems increasingly rely on machine learning/deep learning models deployed across edge devices and cloud infrastructure. However, many real-world IoT systems require personalized models for each user or device, making...
This research arose from the lack of methodologies that systematically integrate user experience (UX) guidelines into the requirements engineering phase of generative artificial intelligence-based solutions, especially in educational environments wit...
Academic advising is fundamental to student success, yet the rapid integration of Artificial Intelligence (AI) and Machine Learning (ML) is fundamentally transforming the delivery of academic support. While predictive models and Recommendation System...
Seawater desalination can only be sustainable if it cuts energy use, membrane fouling, brine discharge, and water cost. This review compares thermal and membrane technologies against these four challenges. RO supplies 70 to 80% of desalinated water a...
This work presents the development of an intelligent system designed to support the predictive maintenance of the Colombian Navy’s maritime vessels through the estimation of remaining useful life and unsupervised anomaly detection, within the f...
The landscape of cybercrime has undergone significant transformations over the past decade. Present-day threats include AI-generated attacks, deep fakes, 5G network vulnerabilities, cryptojacking, and supply chain attacks, among others. To remain res...
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