IET Smart Cities最新文献

{"title":"An Attention-Based Gated Recurrent Unit for Intrusion Detection in MQTT-Enabled IoT","authors":"Rizwana Nazir,&nbsp;Saba Noureen,&nbsp;Muhammad Hassan Jamal,&nbsp;Muazzam A. Khan,&nbsp;Faneela Faneela","doi":"10.1049/smc2.70038","DOIUrl":"https://doi.org/10.1049/smc2.70038","url":null,"abstract":"<p>IoT devices are revolutionising various sectors by facilitating effortless communication and the sharing of data. Unfortunately, the proliferation of interconnected devices increases the potential for security threats, which is why intrusion detection systems are essential for protecting these networks. Among the many IoT communication protocols available, the Message Queuing Telemetry Transport (MQTT) is known for its fast and efficient data transfer. Therefore, this research aims to improve Intrusion detection systems for IoT environments operating under the MQTT protocol, concentrating on the innovative use of machine learning (ML). In particular, we introduce a new and inventive approach to intrusion detection using the attention-gated recurrent unit (AGRU) architecture. Because gated recurrent units (GRUs) are superb at predicting sequential data, the attention mechanism allows the model to concentrate on the most critical elements of the data at any moment. The main objective of the AGRU is to learn the most complex and advanced intrusion techniques that traditional methods fail to capture. The AGRU is capable of identifying and securely authenticating access request communications on IoT devices using a secure MQTT communication network. The attention mechanism improves anomaly detection in communication processes of the IoT devices, which enhances the detection efficiency with precise intrusion detection and monitoring systems. The conducted simulation test on the attack detection systems shows that the AGRU model is more efficient compared to already existing systems in terms of its capability to address the arising issues with the help of sophisticated ML algorithms.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70038","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Smart, Sustainable, and Optimal Parking Allocation Scheme for Vehicles in Smart Cities","authors":"Md Abdus Samad Kamal,&nbsp;Nazmus Sakib,&nbsp;A. S. M. Bakibillah,&nbsp;Kou Yamada,&nbsp;Jun-ichi Imura","doi":"10.1049/smc2.70033","DOIUrl":"https://doi.org/10.1049/smc2.70033","url":null,"abstract":"<p>Unregulated parking search is a major source of urban inefficiency, leading to unnecessary cruising, wasted time, driver frustration and increased emissions. Moreover, when drivers select spots solely based on immediate self-interest, ignoring others' dynamic needs and preferences, this behaviour exacerbates congestion, conflict and overall discomfort. To address these challenges and advance towards a smart, sustainable and user-centric mobility system, this paper proposes an Optimal Parking Allocation Scheme (OPAS). By intelligently integrating user behaviour and real-time demand, OPAS dynamically assigns parking spaces that enhance overall system efficiency while flexibly providing each user with an optimal spot, balancing collective sustainability with individual comfort. The proposed OPAS wirelessly receives the user information upon arrival at the entrance and determines the best-suited spot by solving an adaptive optimisation problem considering the travel and parking behaviour in terms of the number of passengers in the car, their walking and driving distances, the priority level of users, in addition to trends of the occupation ratio. The proposed OPAS dynamically tunes its objective parameters to align with overarching system goals, yielding successive, situation-adaptive decisions. The performance of the proposed scheme is evaluated using data from an indoor parking model of a shopping centre in Gunma City, Japan. The results demonstrate that OPAS achieves a significant reduction in both individual walking distance and vehicular travel distance within the parking facility. Consequently, this efficiency directly translates to a decrease in total fuel consumption and associated emissions. Specifically, the proposed strategy achieves a daily reduction of 23 kg in <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>CO</mtext>\u0000 <mn>2</mn>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${text{CO}}_{2}$</annotation>\u0000 </semantics></math> emissions and 10 L in fuel consumption, highlighting the practical significance of the proposed approach.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PoAD-Lite: A Lightweight, Activity-Aware Consensus Protocol for Scalable and Energy-Efficient IoT Blockchains","authors":"Kofi Sarpong Adu-Manu,&nbsp;Pachomius Kweku Lawson,&nbsp;Prince Samuel Kyeremanteng,&nbsp;Eugene Cobbah,&nbsp;Prince Ofori,&nbsp;Charles Adjetey","doi":"10.1049/smc2.70034","DOIUrl":"https://doi.org/10.1049/smc2.70034","url":null,"abstract":"<p>The growth of Internet of Things (IoT) applications requires blockchain consensus mechanisms that are efficient, fair and resilient under constrained and intermittently connected operating conditions. This study presents the Proof-of-Activity and Delegation-Lite (PoAD-Lite), a lightweight consensus protocol that combines activity-aware eligibility scoring, verifiable randomness, minimal-state delegation and quorum-based finality. A Python-based simulation evaluated PoAD-Lite against PoW-Lite, PoS and PBFT-Lite in committee-scale IoT/edge settings with 10–100 validators. In addition to assessing scalability, the revised evaluation examines validator churn and adversarial behaviours, including delayed participation, equivocation, invalid block proposals and delegation concentration. The results show that PoAD-Lite maintains finality under moderate churn of up to 20% with no observed safety violations or unsafe fork events in the tested scenarios. Under severe 30% churn, the finality success rate declines to 77.8%, indicating liveness degradation, whereas safety is preserved. Adversarial tests similarly show that invalid or conflicting proposals are detected and rejected, although stronger Byzantine participation reduces the progress. These findings demonstrate that PoAD-Lite provides a promising, safety-preserving and resource-conscious consensus approach for committee-scale IoT/edge blockchain deployments, which is evaluated with up to 100 validators.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Infrastructure to Digital Skills: A PRISMA Systematic Review of Digital Capability in Smart City Transformation","authors":"Ioannis Zervas,&nbsp;Emmanouil Stiakakis","doi":"10.1049/smc2.70035","DOIUrl":"https://doi.org/10.1049/smc2.70035","url":null,"abstract":"<p>Smart city research has largely focused on infrastructure, digital systems and technological performance, while giving less attention to the human and organisational conditions that make urban transformation feasible and durable in practice. This study examines how digital capability shapes smart city transformation beyond infrastructure-led perspectives. A PRISMA-based systematic review was conducted using Scopus and Web of Science Core Collection to identify studies linking smart city or urban digital transformation to human capital, workforce capability, organisational capability and governance capacity. The review indicates that transformation outcomes are not sufficiently explained by infrastructure alone. Digital skills, workforce readiness and training emerged as important foundations of change, but their influence depended strongly on organisational support, leadership capacity, internal coordination and governance arrangements that enable digital initiatives to be embedded, maintained and scaled. The findings suggest that smart city transformation is better understood as a multi-level capability process in which individual, organisational and governance capabilities interact rather than operate independently. The synthesis also indicates that technologically ambitious urban strategies often generate uneven results when capability development remains fragmented or weakly institutionalised. On this basis, the review supports a capability-based interpretation of smart city transformation that shifts attention from technology as an end in itself to the conditions that sustain its effective and inclusive use. The study contributes to a more human-centred and institutionally grounded understanding of smart city transformation and highlights capability alignment as a key condition for resilient and sustainable urban change.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dirichlet-Enhanced Transformer for Reliable WiFi RSSI Power Fingerprinting-Based Indoor Positioning in Smart Energy Buildings","authors":"Phuong Anh Nguyen,&nbsp;Tung Vu,&nbsp;Do-Hyeun Kim,&nbsp;Ngoc Le","doi":"10.1049/smc2.70031","DOIUrl":"https://doi.org/10.1049/smc2.70031","url":null,"abstract":"<p>Accurate indoor positioning is a key enabler of smart building intelligence, supporting applications such as occupant localisation, asset tracking, emergency response and energy optimisation. In GPS-denied environments, WiFi fingerprinting has emerged as a cost-effective and infrastructure-ready solution that leverages ubiquitous access points without additional hardware. However, traditional fingerprinting methods face challenges of temporal instability, signal fluctuation and the absence of uncertainty quantification, leading to unreliable performance in dynamic indoor environments. Recent Transformer-based models have improved feature extraction through attention mechanisms but still struggle to handle noisy or unreliable access points and typically produce overconfident predictions. To address these issues, this paper proposes a Dirichlet-Enhanced Transformer (DE-Transformer) architecture that integrates Dirichlet distributions into multi-head attention to assess the reliability of individual access points whilst generating confidence-aware position predictions. The proposed framework consists of three modules: WiFi RSSI preprocessing and embedding, a Dirichlet-enhanced Transformer encoder and an uncertainty-aware regression decoder. Experimental evaluation demonstrates substantial performance gains—achieving a mean positioning error of 0.90 m and 92.5% accuracy within 1.5 m, outperforming baseline Transformers by 21% in mean error and 53% in worst-case bounds. Statistical analysis confirms significant improvements <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mrow>\u0000 <mo>(</mo>\u0000 <mrow>\u0000 <mi>p</mi>\u0000 <mo>&lt;</mo>\u0000 <mn>0.001</mn>\u0000 </mrow>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 </mrow>\u0000 <annotation> $(p&lt; 0.001)$</annotation>\u0000 </semantics></math> with enhanced temporal stability, reduced error variance and calibrated uncertainty estimates. Owing to its robustness, scalability and confidence-aware inference, the proposed DE-Transformer represents a promising solution for real-time, safety-critical indoor navigation in smart building environments.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148616264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ALFA: A Software Architecture for Bounded Incremental Firmware Updates in Energy-Constrained LoRa-Based IoT Systems","authors":"Aya Taghian,&nbsp;Koji Inoue","doi":"10.1049/smc2.70029","DOIUrl":"https://doi.org/10.1049/smc2.70029","url":null,"abstract":"<p>Battery-powered and energy-harvesting IoT systems increasingly depend on Firmware Update Over-The-Air (FUOTA) to remain secure and functional after deployment. In LoRaWAN networks, however, FUOTA is constrained by strict duty-cycle regulations (e.g., 1% in EU868), small payload sizes and long packet airtime, frequently stretching updates into multihour or multiday operations. Such prolonged latency can be problematic: Devices become temporarily desynchronised, sensing gaps degrade monitoring quality (e.g., for AI-assisted analytics) and energy-harvesting nodes may miss update windows and remain outdated. Although differential updates reduce transmitted data size, their effectiveness is often undermined by build-induced structural volatility, whereby minor code changes trigger widespread binary reorganisation and inflate patch size. This paper identifies structural volatility as a root cause of FUOTA latency and proposes ALFA, a linker-enforced software architecture for bounded firmware evolution that establishes architectural spatial organisation of the firmware image together with explicit intercomponent interaction isolation prior to differential update generation. Experiments on MCU-class firmware demonstrate up to a 7.4<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>×</mo>\u0000 </mrow>\u0000 <annotation> ${times} $</annotation>\u0000 </semantics></math> reduction in differential patch size, reducing airtime by 86.3% and restoring update feasibility under duty-cycle and energy-harvesting constraints.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148466611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating AI Tools and Drone Photogrammetry for Urban Planning and Analysis: Implications for Sociocultural Dynamics, Sustainability, and Pedagogy","authors":"Jordi Rabago,&nbsp;Antonio Juárez,&nbsp;Lesly Pliego,&nbsp;Kingsley Okoye","doi":"10.1049/smc2.70032","DOIUrl":"10.1049/smc2.70032","url":null,"abstract":"<p>This study proposes an integrated interdisciplinary framework that combines AI tools with drone photogrammetry to address technical, theoretical and pedagogical dimensions of urban analysis. It uses high-precision geospatial data (<i>n</i> = 737) to validate urban complexity theories and professional competencies. The methodology involves orthomosaic generation, point clouds and 3D models using photogrammetry techniques. AI core methods, such as machine learning and computer vision, specifically automated feature detection, Structure from Motion (SfM) and Multi-View Stereo (MVS) algorithms embedded in commercial photogrammetry pipelines, supported spatial analysis, improving data quality and analytical capacity. The results demonstrate that automated semantic segmentation facilitates classification of point clouds for urban modelling. Automated feature-matching and lighting normalisation achieved a mean reprojection error of 0.102 pixels, yielding a high-fidelity dataset capable of capturing informal urban morphologies that remain unresolved in standard, publicly available satellite imagery. Beyond technical outcomes, a motivation survey of participating students revealed strong intrinsic and extrinsic engagement, while fostering competencies to address complex urban challenges. The study contributes to a technical workflow for AI-enhanced spatial reconstruction, empirical validation of urban complexity and fractal theories and organisation, and an exploratory pedagogical study on emerging technologies. Overall, the framework improves spatial precision, supports evidence-based urban governance and contributes to the UN's SDG goal 11.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148381082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Energy-Conscious, Regulation-Ready and Formally Verified Security Protocol for Low-Power Medical and Safety Devices","authors":"Sidra Anwar,&nbsp;Mouaz Hendi,&nbsp;Jonathan Anderson","doi":"10.1049/smc2.70028","DOIUrl":"https://doi.org/10.1049/smc2.70028","url":null,"abstract":"<p>This paper presents a formally verified, lightweight security protocol for energy-constrained IoT devices operating in regulated environments, with a primary focus on wearable medical systems. The protocol is designed to meet emerging cybersecurity requirements from HIPAA, GDPR and Health Canada and combines Ed25519-based mutual authentication, ephemeral Curve25519 key exchange and ChaCha20-Poly1305 authenticated encryption to provide secure, in-transit protection across heterogeneous nodes with minimal computational and energy overhead. Formal verification using ProVerif and Scyther establishes resilience against key compromise, replay and session confusion, with guarantees of end-to-end authentication, forward secrecy, nonce freshness and key integrity in multi-node settings. Practical feasibility is evaluated through a dual-phase methodology. A Python-based simulation framework examines runtime behaviour under adversarial and fault-prone conditions, enabling analysis of implementation-level state transitions and recovery behaviour beyond symbolic models. The protocol is then deployed on an STM32L431-based ECG wearable relayed through a mobile gateway to a cloud server, representing a CPU-bound short-range IoT platform. Energy profiling using Nordic PPK2 shows a daily protocol overhead of approximately 7.91 mWh, under 16% of the system energy budget, supporting over 30 days of secure operation per charge. Complementary evaluation on a cellular IoT platform with hardware-backed security further demonstrates that regulation-ready secure communication is feasible across heterogeneous low-power IoT deployments without compromising runtime efficiency.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Evaluation of YOLO Architectures for Automated Detection of Buried Manhole Covers in GPR Radargrams","authors":"Jantana Panyavaraporn,&nbsp;Sitthiphat Eua-apiwatch","doi":"10.1049/smc2.70027","DOIUrl":"https://doi.org/10.1049/smc2.70027","url":null,"abstract":"<p>Urban paving and resurfacing operations frequently bury utility access points, complicating infrastructure maintenance and emergency response. Although ground-penetrating radar (GPR) can be used to locate buried manholes, manual radargram interpretation requires specialised expertise and is time-consuming and subjective. This paper introduces a systematic comparative evaluation of three YOLO (You Only Look Once) variants of different architectural generations, including YOLOv5s (anchor-based), YOLOv8s (anchor-free with decoupled heads), and YOLOv11s (transformer-enhanced). We trained and validated these models using 9-fold cross-validation on 54 controlled radargrams obtained at 1000 MHz under systematically varied conditions: three surface types (asphalt, concrete, sand), six burial depths (0.05–0.75 m), and three compaction levels (C0, C5, C10). The results show that YOLOv5s showed the best performance under sparse data conditions, with accuracy = 0.7865, precision = 0.8198, recall = 0.7533, [email protected] = 0.7950 and the lowest cross-fold variability (RMSE = 0.0725). YOLOv8s achieved higher [email protected]:0.95 (0.3711), indicating good generalisation on strict IoU thresholds, but YOLOv11s showed high instability (RMSE = 0.2200), indicating overfitting. Paired t-tests showed no statistically significant difference between architectures at <i>α</i> = 0.05, but practical stability differences that are deployment-relevant were prominent. Detection accuracy degraded systematically at high compaction (C10) and at greater burial depths, consistent with electromagnetic attenuation in dense media. YOLOv5s also offered the shortest inference time, which supports near-real-time deployment scenarios. A prototype of the interface based on the LINE is used to demonstrate the technical feasibility of field workflows. These results suggest that the lighter YOLO architecture provides better stability and efficiency for GPR-based utility detection when training data is limited. This can guide the model selection for infrastructure inspection applications.</p>","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148085783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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