School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau

Permanent link for this collectionhttps://hdl.handle.net/10292/553

AUT is home to a number of renowned research institutes in engineering, and computer and mathematical sciences. The School of Engineering, Computer and Mathematical Sciences strong industry partnerships and the unique combination of engineering, computer and mathematical sciences within one school stimulates interdisciplinary research beyond traditional boundaries. Current research interests include:

Artificial Intelligence; Astronomy and Space Research;

Biomedical Technologies;

Computer Engineering; Computer Vision; Construction Management;

Data Science;

Health Informatics and eHealth;

Industrial Optimisation, Modelling & Control;

Information Security;

Mathematical Sciences Research; Materials & Manufacturing Technologies;

Networking, Instrumentation and Telecommunications;

Parallel and Distributed Systems; Power and Energy Engineering;

Software Engineering; Signal Processing; STEM Education;

Wireless Engineering;

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Now showing 1 - 20 of 1757

A Bibliographic Study of Integrating IoT and Geospatial Modelling for Sustainable Smart Agriculture in Developed Countries: Focus on Australia
(Elsevier, 2025-12-02) Mamun, Quazi; Zaman, Asaduz; Ip, Ryan HL; Haque, KM Shamsul
Integrating the Internet of Things (IoT) and geospatial modelling technologies is pivotal for advancing sustainable smart agriculture, particularly in resource-constrained environments like Australia. This systematic literature review examines the adoption and impact of these technologies in agriculture across Australia and select developed countries. Through an extensive analysis of 172 peer-reviewed articles published between 2013 and 2023, this study identifies key technological advancements such as unmanned aerial vehicles (UAVs), consumer-grade cameras (RGB cameras), and satellite platforms (Sentinel-2, LANDSAT-8) that have significantly influenced agricultural practices. The findings reveal Australia’s progress in adopting these technologies but also highlight gaps compared to countries like Germany and the USA, especially in using UAVs, Synthetic Aperture Radar (SAR) and RGB cameras. The study underscores Australia’s need to enhance its technological capabilities, particularly resource management, to foster more efficient and sustainable agricultural practices. This review provides valuable insights for policymakers, researchers, and technology providers, aiming to drive innovation and improve agricultural outcomes in the face of growing environmental challenges.
Critical Factors Influencing the Adoption of Basic and Scaled Agile Methods: A Comparative Study
(Project Management Research Office, AUT, 2025-11-27) Zhang, Yinghui (Michael); Lal, Ramesh
This paper presents a systematic literature review (SLR) of 44 primary studies to critically investigate the factors influencing the adoption of six major Agile methods, segmented into Basic (XP, Scrum, Kanban) and Scaled (SAFe, DAD, LeSS) frameworks. The analysis identifies key success factors (nine for Basic, eight for Scaled) and corresponding barriers. Findings confirm that top management support, effective communication, and training are fundamental enablers across both levels. Crucially, the study provides a comparative synthesis that distinguishes their focus: Basic Agile mitigates internal team process risks, while Scaled Agile addresses systemic coordination and enterprise governance challenges. Furthermore, we map the limitations and strengths of these methods onto Software Project Risk Quadrants, demonstrating that scaling is necessary to manage Execution and Environmental Risks effectively. This research offers crucial theoretical insights for balancing flexibility and structure in complex Agile transformations.
Adopting Data-Analytics Methods for Decision-making Processes in IT Project Portfolio Management
(Project Management Research Office, AUT, 2025-11-27) Faisal, Thafnitha; Vaipulu, Daniel
This paper investigates how data analytics can be operationalised to improve decision making in IT Project Portfolio Management (ITPPM) for large, scaled agile organisations, using the Disciplined Agile Delivery (DAD) portfolio process blade as the organising lens. Through a multivocal literature review that integrates peer-reviewed and credible grey literature, the research addresses three linked questions: 1) What challenges inhibit data-driven decision-making in ITPPM; 2) Which data analytics methods are reported for ITPPM; and 3) What are the benefits and success factors when analytics methods are integrated into portfolio practices. Findings show recurring barriers across DAD practices, led by poor data quality and integration, immature governance and PMO alignment, tooling and capability gaps, unreliable intake scoring, limited portfolio risk telemetry, and weaknesses in financial and operational measurement. To operationalise these insights, the study proposes a three-layer conceptual framework (DAD practices → analytics methods → benefits & success factors) that serves as a guide for leaders to sequence interventions: establish data and governance foundations, pilot targeted analytics, then institutionalise successful patterns. The paper concludes with practical roadmaps and research directions to validate the framework empirically.
Mapping Core Practices in Disciplined Agile Delivery (DAD) to ISO 9001:2015 Requirements
(Project Management Research Office, AUT, 2025-11-27) Kurniawan, Arie; Lal, Ramesh
Organizations adopting agile frameworks often struggle to maintain compliance with ISO 9001:2015 Quality Management Systems – Requirements, particularly during certification audits where evidence of conformance is mandatory. From an ISO 9001 auditor’s perspective, this tension reflects a fundamental challenge: agile practices prioritize flexibility, minimal documentation, and rapid iteration, while ISO 9001 enforces structured processes, documented information, and traceability. This study addresses that challenge by investigating how Disciplined Agile Delivery (DAD), a governance-oriented agile framework, can be aligned with ISO 9001 requirements without compromising agility. The research employs a Multivocal Literature Review (MLR), incorporating both academic and practitioner sources, and applies Reflexive Thematic Analysis (RTA) to synthesize insights. Guided by Process Compliance Theory, the study conceptualizes the mapping of DAD practices to ISO 9001 clauses as a hybrid governance approach, embedding compliance checkpoints and documentation enhancements within DAD’s adaptive structure. This theoretical framework explains how organizations can operationalize compliance through adaptive mechanisms rather than rigid controls. The findings identify six DAD practice pillars, namely Full Delivery Lifecycle, Focus on Process Goals, Defined Roles and Responsibilities, Agile Governance, Context-Sensitive Practice, and DevOps and Enterprise Awareness. This study also demonstrates their varying degrees of alignment with ISO 9001 clauses. Practical adaptations, such as lightweight documentation strategies and integrated compliance reviews, are proposed to bridge gaps. By combining auditor-informed insights with theoretical framing, this study contributes a structured mapping framework and actionable recommendations for organizations seeking to maintain agility while achieving ISO 9001 certification.
Addressing the Challenges of Remote Work in Scaled Agile Frameworks: Organisational and Change Management Solutions
(Project Management Research Office, AUT, 2025-11-27) Joy, Twinkle; Thorpe, Stephen
Agile methodologies have become central to contemporary software development, promoting iterative delivery, continuous feedback, and cross-functional collaboration. As organisations scale Agile adoption, the Scaled Agile Framework (SAFe) provides structured guidance for aligning multiple teams, coordinating program-level work, and maintaining portfolio oversight. Concurrently, the shift to hybrid and remote work environments introduces complexities in communication, collaboration, leadership visibility, and technological integration. This research report presents a systematic review of 32 peer-reviewed studies published between 2017 and 2024, aiming to investigate the challenges of implementing SAFe in distributed contexts and explore the application of Kotter’s 8-Step Change Model to support organizational transformation. Using Braun and Clarke’s thematic analysis, five key themes emerged: communication and collaboration, scaling framework challenges, change management and resistance, technological dependencies, and leadership and governance. Findings indicate that remote SAFe adoption requires balancing structured change management with Agile’s iterative principles, integrating digital tools effectively, and fostering leadership presence and psychological safety across distributed teams. By mapping Kotter’s model onto remote Agile practices, the presented research report provides both conceptual insights and practical guidance for practitioners navigating large-scale distributed Agile transformations. The research highlighted the relevance of combining structured change frameworks with adaptive Agile practices while suggesting avenues for future empirical validation to strengthen understanding of remote SAFe implementation.
Improving Story Points Estimation Using Ensemble Machine Learning
(Springer Science and Business Media LLC, 2025-11-13) Ahmad, Z; Kuo, MMY
Agile software development (ASD) emphasizes iterative development, continuous feedback, and team collaboration, addressing the limitations of traditional methodologies. This research explores the application of machine learning (ML) to improve story point estimation in ASD, a critical practice for planning and prioritization. Traditional methods like Planning Poker often suffer from human biases and inconsistencies, leading to unreliable estimates. This study introduces an innovative ML-based ensemble stacking technique, combining RoBERTa, a transformer model for natural language processing, with BiLSTM, a neural network adept at handling sequential data. The research involves reviewing existing ML methodologies, developing the proposed model, and evaluating its effectiveness using 21,064 data points from 14 open-source projects. The model’s performance was assessed through Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). Results show that the proposed ensemble model achieved lower MAE and MAPE, with performance improvements ranging from 4% to 32% over state-of-the-art models. While promising, the study suggests there is still room for further refinement, indicating the potential for ongoing advancements. This research contributes to the integration of ML in software engineering, offering a path toward more accurate and efficient project management.
Accumulated Performance Comparison of Solar PV and Solar Thermal Water Heating in New Zealand
(Wiley, 2025-12-01) Lu, Wei; Wang, Jay
The rising global energy demand and environmental harm caused by reliance on fossil fuels highlight the urgent need for sustainable solutions in residential water heating. This study conducts a comparative numerical analysis of solar photovoltaic (PV) and solar thermal water heaters under New Zealand's typical weather conditions. By integrating the National Institute of Water and Atmospheric Research (NIWA) meteorological data, hourly simulation results were performed to analyze energy output, water temperature profiles inside storage tank, and levelized cost of electricity (LCOE) under varying seasonal conditions, including summer, normal, and winter. The highlight of this study is the evaluation of accumulated water performance within the storage tank under real‐life operating conditions. This includes the impact of actual weather fluctuations (including ambient temperature and solar radiation), target hot water temperature, heat losses from the tank, and typical household water usage patterns along with the replenishment of cold water. Under identical weather conditions, the simulations results indicate that the solar thermal system outperforms solar PV system across key performance metrics. For solar water heating applications, the thermal system generated 5847.59 kWh of energy annually per 10 m of collector area, compared to 2780.41 kWh from the PV system. Although the thermal system required 33.7% more auxiliary energy annually (964.59 kWh) compared to the PV system (721.38 kWh), it delivered better energy utilization efficiency. This is highlighted by its produced‐to‐used energy ratio of 6.06, which is 58% higher than the PV system's ratio of 3.85. The efficiency translated to better economic advantages, with thermal achieving a 61.9% lower LCOE for produced energy at 0.0766 NZD/kWh compared to PV's 0.2013 NZD/kWh, and a 40.2% lower LCOE for used energy at 0.4641 NZD/kWh versus PV's 0.7757 NZD/kWh.
A Mobile DevOps Project Management Framework
(Project Management Research Office, AUT, 2025-11-27) Khan, Farhan; Ma, Jing
Mobile applications have become critical infrastructure in finance, healthcare, and public services, yet their development and operations pipelines remain complex and disconnected. Although DevOps practices have matured in web and cloud systems, mobile environments continue to face fragmented monitoring, weak governance visibility, and inconsistent security assurance. This study addresses the problem of limited managerial control and transparency in mobile DevOps projects, where automation lacks connection to governance and decision making. The objective was to develop a unified model that integrates automation, monitoring, and governance to strengthen project oversight. Drawing from a Multivocal Literature Review of academic and practitioner studies and examined through a demonstration linking an iOS application with Sentry and Azure DevOps, the research produced the Mobile DevOps Project Management Framework. The demonstration illustrates how real time logging, alerting, and dashboards can provide continuous visibility for project managers. It illustrates how organisations can strengthen reliability, assurance, and transparency by embedding governance within continuous delivery cycles.
Managing Academic Integrity in the AI Era: A Project Management Lens on Academic Integrity
(Project Management Research Office, AUT, 2025-11-27) Ramesh, Kavya; Nguyen, Minh
This study investigates how AI-integrity initiatives are put into practice in higher education by focusing on IT project management, governance, and the delivery of educational technology. It explores the development of the Egg & Basket Quiz prototype as an example of technology-based learning intervention, while also addressing gaps in institutional policy and integrity. The research uses a mixed methods design to collect both quantitative and qualitative data from 25 students and 3 faculty members. The results reveal that AI is frequently used, with 72% of participants using it weekly. There is also uncertainty about institutional rules, which points to project risks related to governance, ethical compliance, and stakeholder involvement. The study is framed as a project of organizational change and digital transformation, based on PMBOK principles for managing risks and stakeholders, the Technology Acceptance Model (TAM) for user engagement, and insights from academic integrity literature. The findings show that adopting AI-integrity requires careful planning, leadership, stakeholder involvement, risk management, and step-by-step solution development, which are all key elements of IT project management. This research offers a project-management perspective on implementing ethical AI-integrity initiatives in higher education.
The Effect of Digital Literacy on Digital Government Adoption in Developing Countries: A Systematic Literature Review
(Project Management Research Office, AUT, 2025-11-27) Joson, Alvin Dave Carmelo; Thorpe, Stephen
Despite significant investments in their digital government or eGovernment projects, developing countries continue to face low adoption rates of their digital public services. The study in this report explores the impact of digital literacy on the adoption of digital government platforms. Using a Systematic Literature review guided by Kitchenham and Charters protocol and thematic analysis using Braun and Clarke’s framework, the findings show digital literacy’s central role in successful eGovernment. Not only does digital literacy influence citizens’ trust, but it also contributes to long-term engagement of citizens with eGovernment systems. Socio-economic factors also come into play. Income, education and location influence how prepared citizens are to use digital government services. The study provided insights on how IT project managers can enhance adoption by influencing project rollout and offering support to the most disaffected groups. The practical guidance suggests activities and considerations for IT project based on our findings and ground them in PMBOK framework developed by the Project Management Institute. It emphasizes the importance of stakeholder management throughout the different phases of the project especially when trying to address eGovernment outcomes in developing countries by promoting digital inclusivity.
Global Knowledge Management Practices in Information Technology: A Multivocal Literature Review
(Project Management Research Office, AUT, 2025-11-27) Veerabhadrachar, Deepa; Lal, Ramesh
The rapid pace of technological advancement has created a notable readiness gap within organizations. On one side, are experienced professionals who bring invaluable expertise yet often struggle to adapt to emerging technologies; on the other are recent graduates who possess up-to-date technical skills but lack practical organizational knowledge. This imbalance is frequently reflected in cycles of layoffs and new hires triggered by technological transitions. To mitigate this challenge, knowledge management must adopt specialized strategies that support both the upskilling of new entrants and the reskilling of seasoned employees, thereby strengthening project outcomes and sustaining competitiveness in the marketplace. This study examines the frameworks required for effective knowledge capture and dissemination, with attention to both explicit and tacit forms of knowledge. It highlights the critical role of technological tools and the value of diverse learning environments in facilitating the transfer of tacit knowledge, widely recognized as a key source of competitive advantage. Furthermore, the research explores how organizations can refine their knowledge management approaches to improve workforce performance, drawing on contemporary literature at the intersection of technology and knowledge management. The findings underscore the need for organizations to continuously align their knowledge management systems with evolving business objectives and technological innovations, including cloud computing and artificial intelligence. By systematically identifying, assessing, and enhancing knowledge management practices within project management, this research seeks to bridge existing knowledge gaps and ensure that organizations remain agile and responsive to shifting market demands and technological change.
The IT Project Manager: Benefits of a Technical Skill Set
(Project Management Research Office, AUT, 2025-11-27) Krstić, Livia; Thorpe, Stephen
Internationally recognized frameworks and accreditations define the core competencies required of IT project managers. Among these, technical skills are often cited as important, particularly in IT-focused projects. However, the specific technical competencies required, and the extent to which project managers should possess them, remain unclear. The literature on this topic is limited, though existing studies indicate that technical proficiency contributes to project success in technical domains. To explore this gap, this study employed semi-structured interviews with IT project managers and key project participants to examine perceptions of the importance of technical skills. Findings reveal a clear divide: participants with technical education emphasized the necessity of technical expertise, whereas those without technical qualifications highlighted communication, motivation, and attitude as most critical. The study contributes new insights into the strategic value that technical capability adds to IT project management effectiveness.
Building the Blocks of Being: The Attributes and Qualities Required for Consciousness
(MDPI AG, 2023-06-22) Tait, I; Bensemann, J; Nguyen, Trung
For consciousness to exist, an entity must have prerequisite characteristics and attributes to give rise to it. We explore these “building blocks” of consciousness in detail in this paper, which range from perceptive to computational to meta-representational characteristics of an entity’s cognitive architecture. We show how each cognitive attribute is strictly necessary for the emergence of consciousness, and how the building blocks may be used for any entity to be classified as being conscious. The list of building blocks is not limited to human or organic consciousness and may be used to classify artificial and organisational conscious entities. We further explore a list of attributes that seem intuitively necessary for consciousness, but on further investigation, are neither required nor sufficient. The building blocks do not represent a theory of consciousness but rather a meta-theory on the emergence and classification of consciousness.
Experimental and Numerical Evaluation of Rocking Column Bases With Friction Connections and Vertical Web Plates
(Elsevier BV, 2025-10-24) Zhang, HT; Zhang, R; Yan, Zhenduo; Xie, JY; Liu, J; Xiang, P; Zhao, X; MacRae, GA; Clifton, GC; Dhakal, RP; Ramhormozian, Shahab; Rodgers, G; Quenneville, P; Jia, LJ
This paper investigates seismic performance of a low-damage steel rocking column base through experimental and numerical approaches. Asymmetric friction connections (AFCs) were designed at the column base with friction sliding parallel to the column flange. A pair of vertical web plates, which were shop welded to the shear keys then bolted into the foundation, were sandwiched the column web to restrain ultimate uplift and enhance the weak-axis performance. Quasi-static cyclic tests were conducted to investigate the as-built (INITIAL case), post-earthquake (AFTERSHOCK case) and immediate repaired (REPAIR case) performances in both strong and weak axes. It was found that with the presence of the vertical web plate, the moment resistance was increased by 10 % and 8 % for the strong and weak axes, respectively. The prying effect of vertical web plates well ameliorated the initial stiffness loss in the weak axis and can be more easily repaired to the as-built condition. A finite element (FE) model, verified by experimental results, was developed to quantitatively evaluate local plasticity, loss of AFC bolt pre-tension, and energy dissipation. Further analysis revealed the effect of the time-varying axial force on the hysteresis of rocking column base. In addition, in the weak axis, the axial shortening due to localized plastic deformation at flange tips led to a rocking interface with an arc edge and shifted the rocking pivot toward the column's neutral axis, thereby reducing rocking threshold and seismic performance.
Navigating Urban Hydrology: A Comprehensive Exploration of Impervious Area Reduction Techniques in New Zealand's Residential Landscapes
(Emerald, 2025-11-21) Rotimi, Funmilayo Ebun; Kalatehjari, Roohollah; Dokyi, George Okyere; Moshood, Taofeeq Durojaye; Ira, Sue
Purpose: Impervious surfaces have emerged as a critical indicator for assessing the impacts of urbanization on water resources, with recent flood events in New Zealand (NZ) highlighting their significance in urban water management. While traditional stormwater control measures rely on total impervious area calculations, this study examines the effectiveness of impervious area reduction techniques in residential areas across NZ, with particular attention to implementation challenges and policy frameworks. Design/methodology/approach: The research conducts through semi-structured interviews with 18 experts, including government officials, consultants and developers. This qualitative approach allows for an in-depth exploration of various perspectives on urban water management strategies and their effectiveness. Findings: The study reveals several key findings: (1) current strategies exhibit varying effectiveness depending on scale, with catchment-level solutions being more successful than site-specific interventions, (2) significant challenges to implementation exist, such as resource constraints, limited monitoring capabilities and coordination issues among stakeholders and (3) there is a need for stronger national-level guidance and better integration in regulatory frameworks between district and regional plans. Originality/value: This research contributes to the existing knowledge on urban flood resilience by identifying promising opportunities for improvement in urban water management practices in New Zealand. It emphasizes the importance of enhanced public education, innovative technical solutions and market-based incentives as practical recommendations for policymakers and practitioners.
Dynamic Integration of Solar-powered Hydrogen Systems With Fuel Cells and District Heating for Green Data Centers
(Elsevier, 2025-11-16) Pabon, Juan Jose Garcia; Wang, Jay; Chamanehpour, Elham; Salami, Dariush; Khosravi, Ali
The data center sector is rapidly expanding due to the growing demand for cloud storage services, artificial intelligence applications, and other digital technologies. The electricity consumption required to power servers, and their cooling systems are significantly high. Consequently, data centers must align with global carbon reduction goals by adopting renewable energy sources. However, the intermittency of renewable energy sources conflicts with one of the core requirements of data centers: continuous and reliable 24/7 operation. To address this challenge, energy storage systems are essential. While batteries represent the most mature technology, larger-scale systems require complementary storage solutions. This paper presents a transient model developed in Simscape of Matlab of a green data center (1 MW size) powered entirely by renewable energy, integrating both battery storage and green hydrogen. An alkaline electrolyzer is used to convert excess photovoltaic solar energy into hydrogen, which is stored in a tank at a maximum pressure of 30 bar. During periods without solar availability, a PEM fuel cell utilizes the stored hydrogen to generate electricity, working in tandem with the battery system to ensure uninterrupted operation of the data center. Furthermore, the heat extracted from the data center by a heat pump, along with the heat generated by the electrolyzer and fuel cell, is recovered and integrated into a district water heating system. This strategy enhances the overall energy efficiency of the system. The results show that the data center consumes 24 MWh/day, with an additional 12 MWh/day required for the heat pump. The PV panels supply 64 MWh/day, allowing the electrolyzer to consume 18.4 MWh/day for hydrogen production, while the fuel cell provides 7.6 MWh/day to cover nighttime demand. Despite the hydrogen system's lower electrical efficiency (40.6 %), integration of waste heat recovery increases its effective energy efficiency to 82.3 %, approaching battery efficiency (85.9 %). It is noted that the system's useful Total Energy Utilization Factor exceeds 115 %, primarily due to the recovered heat being effectively utilized in the district heating network.
Optimal Energy Storage Management in Grid-Connected PV-Battery Systems Based on GWO-PSO
(MDPI AG, 2025-11-19) Alshdaifat, Yaser Ibrahim Rashed; Prasad, Krishnamachar; Al-Tameemi, Zaid Hamid Abdulabbas; Kilby, Jeff; Lie, Tek Tjing
Grid-connected photovoltaic (PV)–battery systems require advanced control to maintain stable operation, efficient energy exchange, and minimal conversion losses under variable generation and load conditions. This study proposes a dual-loop Energy Management System (EMS) integrated with a Hybrid Grey Wolf Optimizer–Particle Swarm Optimization (GWO–PSO) algorithm for coordinated control of a low-voltage PV–battery–grid system (380 V AC, ≈800 V DC bus). The hybrid optimizer was chosen due to the limitations of standalone GWO and PSO methods, which frequently experience slow convergence and local stagnation; the integrated GWO–PSO strategy enhances both exploration and exploitation during the real-time adjustment of PI controller gains. The rapid inner loop effectively balances instantaneous power among the PV, battery, and grid, while the outer optimization loop aims to minimize the ITAE criterion to enhance transient response. Simulation outcomes validate stable DC-bus voltage regulation, quicker transitions between power import and export, and prompt power balance with deviations maintained below 2.5%, signifying reduced converter losses and improved power-sharing efficiency. The battery’s state of charge is sustained within the range of 20–80%, ensuring safe operational conditions. The proposed hybrid EMS offers faster convergence, smoother power regulation, and enhanced dynamic stability compared to standalone metaheuristic controllers, establishing it as an effective and reliable solution for grid-connected PV–battery systems.
Towards a Closer Collaboration Between Practice and Research in Agile Software Development Workshop: A Summary and Research Agenda
(Springer Nature Switzerland, 2025-10-30) Neumann, Michael; Schön, Eva-Maria; Senapathi, Mali; Rauschenberger, Maria; Silva da Silva, Tiago
Agile software development principles and values have been widely adopted across various industries, influencing products and services globally. Despite its increasing popularity, a significant gap remains between research and practical implementation. This paper presents the findings of the first international workshop designed to foster collaboration between research and practice in agile software development. We discuss the main themes and factors identified by the workshop participants that contribute to this gap, strategies to bridge it, and the challenges that require further research attention.
The Role of Graph Neural Networks, Transformers, and Reinforcement Learning in Network Threat Detection: A Systematic Literature Review
(MDPI AG, 2025-10-24) Doremure Gamage, TP; Gutierrez, JA; Ray, SK
Traditional network threat detection based on signatures is becoming increasingly inadequate as network threats and attacks continue to grow in their novelty and sophistication. Such advanced network threats are better handled by anomaly detection based on Machine Learning (ML) models. However, conventional anomaly-based network threat detection with traditional ML and Deep Learning (DL) faces fundamental limitations. Graph Neural Networks (GNNs) and Transformers are recent deep learning models with innovative architectures, capable of addressing these challenges. Reinforcement learning (RL) can facilitate adaptive learning strategies for GNN- and Transformer-based Intrusion Detection Systems (IDS). However, no systematic literature review (SLR) has jointly analyzed and synthesized these three powerful modeling algorithms in network threat detection. To address this gap, this SLR analyzed 36 peer-reviewed studies published between 2017 and 2025, collectively identifying 56 distinct network threats via the proposed threat classification framework by systematically mapping them to Enterprise MITRE ATT&CK tactics and their corresponding Cyber Kill Chain stages. The reviewed literature consists of 23 GNN-based studies implementing 19 GNN model types, 9 Transformer-based studies implementing 13 Transformer architectures, and 4 RL-based studies with 5 different RL algorithms, evaluated across 50 distinct datasets, demonstrating their overall effectiveness in network threat detection.
Digital Twin Prospects in IoT-based Human Movement Monitoring Model
(MDPI AG, 2025-11-01) Parween, G; Al-Anbuky, A; Mawston, G; Lowe, A
Prehabilitation programs for abdominal pre-operative patients are increasingly recognized for improving surgical outcomes, reducing post-operative complications, and enhancing recovery. Internet of Things (IoT)-enabled human movement monitoring systems offer promising support in mixed-mode settings that combine clinical supervision with home-based independence. These systems enhance accessibility, reduce pressure on healthcare infrastructure, and address geographical isolation. However, current implementations often lack personalized movement analysis, adaptive intervention mechanisms, and real-time clinical integration, frequently requiring manual oversight and limiting functional outcomes. This review-based paper proposes a conceptual framework informed by the existing literature, integrating Digital Twin (DT) technology, and machine learning/Artificial Intelligence (ML/AI) to enhance IoT-based mixed-mode prehabilitation programs. The framework employs inertial sensors embedded in wearable devices and smartphones to continuously collect movement data during prehabilitation exercises for pre-operative patients. These data are processed at the edge or in the cloud. Advanced ML/AI algorithms classify activity types and intensities with high precision, overcoming limitations of traditional Fast Fourier Transform (FFT)-based recognition methods, such as frequency overlap and amplitude distortion. The Digital Twin continuously monitors IoT behavior and provides timely interventions to fine-tune personalized patient monitoring. It simulates patient-specific movement profiles and supports dynamic, automated adjustments based on real-time analysis. This facilitates adaptive interventions and fosters bidirectional communication between patients and clinicians, enabling dynamic and remote supervision. By combining IoT, Digital Twin, and ML/AI technologies, the proposed framework offers a novel, scalable approach to personalized pre-operative care, addressing current limitations and enhancing outcomes.

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