IET Smart Cities最新文献

Deep CNN Models for Weather Monitoring in Smart Agriculture Within Smart Cities 智能城市中智能农业天气监测的深度CNN模型

IF 2.3

IET Smart Cities Pub Date : 2026-03-29 DOI: 10.1049/smc2.70026

Maria Tariq, Asghar Ali Shah, Sagheer Abbas, Muhammad Adnan Khan

{"title":"Deep CNN Models for Weather Monitoring in Smart Agriculture Within Smart Cities","authors":"Maria Tariq, Asghar Ali Shah, Sagheer Abbas, Muhammad Adnan Khan","doi":"10.1049/smc2.70026","DOIUrl":"https://doi.org/10.1049/smc2.70026","url":null,"abstract":"Weather monitoring in agriculture is complex, as it requires predicting future atmospheric states that directly affect farming activities. In smart cities, farmers rely on accurate, up-to-date weather information to make informed decisions. Increasing climate variability has made temperature prediction more challenging than ever. Deep learning has recently emerged as a powerful approach for weather forecasting due to its superior performance over conventional methods and its ability to extract and classify features within a single architecture. This study explores the use of deep Convolutional Neural Network (CNN) models, specifically Visual Geometry Group 16 (VGG16) and MobileNet, with transfer learning for intelligent weather monitoring. The combination of MobileNet and VGG16 leverages transfer learning for accuracy-driven and efficient operations. MobileNet is optimised for mobile and edge devices by delivering high-performance results with lower computational and energy costs, while the deep architecture of VGG16 effectively identifies complex visual features across multiple tasks. Trained on a dataset of weather images, the proposed models accurately detect and classify different weather conditions, enabling farmers to make improved field decisions. Experimental results demonstrate strong performance, with VGG16 achieving 96.95% accuracy and MobileNet achieving 96.19% accuracy.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147585076","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}

引用次数: 0

Text Chunking in Human-AI Teaming of Document Classification for Urban Systems Management Using Large Language Models 基于大型语言模型的城市系统管理文档分类人机协作中的文本组块

IF 2.3

IET Smart Cities Pub Date : 2026-02-28 DOI: 10.1049/smc2.70023

Joshua Rodriguez, Om Sanan, Guillermo Vizarreta-Luna, Steven A. Conrad

{"title":"Text Chunking in Human-AI Teaming of Document Classification for Urban Systems Management Using Large Language Models","authors":"Joshua Rodriguez, Om Sanan, Guillermo Vizarreta-Luna, Steven A. Conrad","doi":"10.1049/smc2.70023","DOIUrl":"10.1049/smc2.70023","url":null,"abstract":"Urban systems management requires analysing complex textual documentation that necessitates coding and analysis to set requirements and evaluate built environment performance. This study contributes to the research of applying large language models (LLMs) to qualitative coding activities, aiming to reduce resources while maintaining comparable reliability performing like humans. Qualitative coding faces challenges such as resource limitations, bias and consistency between evaluators. We report the application of LLMs to deductively code 10 case documents for 17 common characteristics for the management of urban systems. We utilise whole-text analysis and text-chunk analysis to compare the processing of LLMs with human coding efforts using three OpenAI models. Results indicate that LLMs may perform similarly to human coders when initialised with specific deductive coding contexts. GPT-4o, o1-mini and GPT-4o-mini showed significant agreement with human raters when using a chunking method. The application of GPT-4o and GPT-4o-mini as additional raters with humans showed statistically significant agreement, indicating that the analysis of textual documents benefits from LLMs addition. The novel contribution of this paper is the domain-specific evaluation of a chunk-based prompting approach for deductive coding in urban systems management, validating human–AI teaming performance.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147569807","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}

引用次数: 0

Dynamic Traffic Routing for Air Quality Enhancement During Urban Environmental Crises 城市环境危机下改善空气质量的动态交通路径

IF 2.3

IET Smart Cities Pub Date : 2026-02-23 DOI: 10.1049/smc2.70025

José D. Padrón, Carlos T. Calafate, Juan-Carlos Cano, Pietro Manzoni

{"title":"Dynamic Traffic Routing for Air Quality Enhancement During Urban Environmental Crises","authors":"José D. Padrón, Carlos T. Calafate, Juan-Carlos Cano, Pietro Manzoni","doi":"10.1049/smc2.70025","DOIUrl":"10.1049/smc2.70025","url":null,"abstract":"This study introduces an air quality-aware traffic re-routing scheme designed to minimise vehicle emissions in highly polluted urban areas during environmental crises. Tested in two scenarios, a building fire and a smog episode near a train station, the scheme employs an ‘emission sensitivity factor’ (<math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>Δ</mi>\u0000 </mrow>\u0000 <annotation> ${Delta }$</annotation>\u0000 </semantics></math>) to adjust re-routing costs based on normalised air quality index (AQI) data and vehicle emission profiles. Results indicate that selecting an optimal <math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>Δ</mi>\u0000 </mrow>\u0000 <annotation> ${Delta }$</annotation>\u0000 </semantics></math> can reduce <math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>NO</mtext>\u0000 <mi>x</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${text{NO}}_{x}$</annotation>\u0000 </semantics></math> concentrations by 15% and improve AQI by 10% in targeted areas without adversely affecting traffic performance. Key traffic metrics such as average vehicle duration, waiting time, and speed remained largely unchanged (under 2% variation), demonstrating a balance between traffic efficiency and air quality improvement. The findings highlight the potential for integrating dynamic AQI data into urban traffic management systems, offering valuable insights for urban planners and policymakers aiming to reduce pollution exposure while maintaining optimal traffic flow.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147567968","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}

引用次数: 0

Deep Learning-Driven Intrusion Prediction System Using Ground-Plane Homography in Smart City Dynamic Zones 基于地平面单应性的深度学习驱动的智慧城市动态区域入侵预测系统

IF 2.3

IET Smart Cities Pub Date : 2026-02-20 DOI: 10.1049/smc2.70024

Cho Nilar Phyo, Thi Thi Zin, Pyke Tin

{"title":"Deep Learning-Driven Intrusion Prediction System Using Ground-Plane Homography in Smart City Dynamic Zones","authors":"Cho Nilar Phyo, Thi Thi Zin, Pyke Tin","doi":"10.1049/smc2.70024","DOIUrl":"https://doi.org/10.1049/smc2.70024","url":null,"abstract":"In smart city environments, public safety increasingly depends on intelligent surveillance systems that can be capable of adapting to dynamic and context-dependent access restrictions. Traditional systems often rely on static and predefined boundaries that fail to respond to rapidly changing environments such as construction sites, public gatherings or emergency situations. This paper introduces a novel deep learning-driven framework using ground-plane homography for real-time proactive intrusion prediction within these dynamically restricted zones (DRZs). Our method first employs deep learning to accurately detect and localise physical restriction markers (e.g., traffic cones). We then utilise ground-plane homography estimation to accurately map these markers into two-dimensional ground-plane perspective, precisely defining the spatial boundaries of the DRZ in real-time. After the reactive detection of restriction markers region, intrusion prediction is achieved through sophisticated human trajectory analysis and future path extrapolation. By forecasting a person's path and identifying projected future presence within the dynamic ground-plane zone, the system assists proactive alerts and adaptive security responses before an actual violation. To the best of our knowledge, this is the first system capable of predicting intrusions into areas dynamically demarcated by visual restriction markers. The experimental results on real-world surveillance datasets demonstrate the system's effectiveness in identifying the presence of humans in DRZ, validating its potential for deployment in smart cities and critical infrastructure.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147299981","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}

引用次数: 0

An Application of Smart City to Achieve Sustainable Development: A Case Study in Dubai, United Arab Emirates 智慧城市在实现可持续发展中的应用——以阿拉伯联合酋长国迪拜为例

IF 2.3

IET Smart Cities Pub Date : 2026-01-12 DOI: 10.1049/smc2.70018

Abdulla Almheiri, Jorge F. Montenegro, Amare Gebrie, Midhun Mohan, Muhamad Khairulbahri

{"title":"An Application of Smart City to Achieve Sustainable Development: A Case Study in Dubai, United Arab Emirates","authors":"Abdulla Almheiri, Jorge F. Montenegro, Amare Gebrie, Midhun Mohan, Muhamad Khairulbahri","doi":"10.1049/smc2.70018","DOIUrl":"https://doi.org/10.1049/smc2.70018","url":null,"abstract":"Understanding associations between sustainable development and the smart city is essential to achieve sustainable smart cities. Dubai has emerged as an example in the Middle East for adopting smart technologies to enhance urban living, with initiatives ranging from digital governance to intelligent transportation systems. However, the associations between sustainable development and smart city implementation in Dubai is limited. This study aims to investigate the application of the smart city in Dubai, assessing the smart city implementation in terms of sustainable development by applying the system archetypes to assess the implementation of the smart city in Dubai in terms of sustainable development issues. After the identification of the system archetypes, it is found that the implementation of smart city initiatives such as e-government and clean transportation are in line with sustainable development issues such as low-carbon emissions and less air pollution. Moreover, this study shows that the structure of the Limits to Growth archetypes has dominated the smart city development in Dubai. This means that the development of Dubai has had critical issues such as persistent traffic congestion and a polluted atmosphere. The findings stress that the smart city application in Dubai is a good exemplar that the smart city can be a sustainable smart city altogether. The second point is although the smart city enables us to achieve a sustainable smart city, the implementation of the smart city should be monitored regularly, especially if reinforcing loops dominate balancing loops as seen in the case of traffic congestion. This study contributes to enhancing the decision-making process of policymakers, industry stakeholders, government authorities and business managers regarding the implementation of smart initiatives as well as for city planners to achieve a sustainable smart city in other regions.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145969904","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}

引用次数: 0

Trajectory Optimisation for UAV Data Collection in IoT-Based WSN: A Lévy Flight-Based Approach 基于物联网WSN的无人机数据采集轨迹优化：一种基于lsamvy飞行的方法

IF 2.3

IET Smart Cities Pub Date : 2026-01-09 DOI: 10.1049/smc2.70022

Hamayadji Abdoul Aziz, Ado Adamou Abba Ari, Emmanuel Baba, Khouloud Boukadi, Alidou Mohamadou, Zibouda Aliouat, Abdelhak Mourad Gueroui

{"title":"Trajectory Optimisation for UAV Data Collection in IoT-Based WSN: A Lévy Flight-Based Approach","authors":"Hamayadji Abdoul Aziz, Ado Adamou Abba Ari, Emmanuel Baba, Khouloud Boukadi, Alidou Mohamadou, Zibouda Aliouat, Abdelhak Mourad Gueroui","doi":"10.1049/smc2.70022","DOIUrl":"https://doi.org/10.1049/smc2.70022","url":null,"abstract":"In large-scale deployments, the Internet of things (IoT) and wireless sensor networks (WSNs) often face challenges in transmitting collected data to the base station due to limited network coverage. Unmanned aerial vehicles (UAVs) can extend this coverage by flying to remote WSN areas and communicating with aggregator nodes (CH-nodes) to retrieve data. Designing UAV-assisted data collection systems therefore requires a careful consideration of both UAV and WSN constraints. This article proposes an energy-efficient approach for UAV-based data collection in IoT/WSNs. The problem is formulated to jointly optimise system cost and energy consumption while accounting for communication power, mission duration, and data importance. The solution proceeds in two steps. First, aggregator nodes are selected using clustering based on residual energy and inter-node distances to minimise system costs. Second, the UAV trajectory is generated using a Lévy flight strategy that follows the positions of the selected aggregators. Although this trajectory may be slightly longer than that produced by a deterministic TSP route, it increases the amount of collected data and prolongs both UAV and WSN lifetime by ensuring timely visits to distant cluster heads. Simulation results confirm the efficiency and robustness of the proposed method compared with existing solutions.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145983623","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}

引用次数: 0

Automating City Accessibility Constraints Mapping Through AI-Assisted Scanning of Street View Imagery 通过人工智能辅助街景图像扫描实现城市可达性约束映射自动化

IF 2.3

IET Smart Cities Pub Date : 2025-12-13 DOI: 10.1049/smc2.70020

Rui S. Moreira, Sérgio Moita, José Manuel Torres, Feliz Gouveia, Maria Alzira P. Dinis, Diogo Ferreira, Madalena Araújo, Maria João S. Guerreiro

{"title":"Automating City Accessibility Constraints Mapping Through AI-Assisted Scanning of Street View Imagery","authors":"Rui S. Moreira, Sérgio Moita, José Manuel Torres, Feliz Gouveia, Maria Alzira P. Dinis, Diogo Ferreira, Madalena Araújo, Maria João S. Guerreiro","doi":"10.1049/smc2.70020","DOIUrl":"10.1049/smc2.70020","url":null,"abstract":"Urban environments often pose challenges for individuals with mobility impairments due to inadequate pedestrian infrastructure. In addition, the lack of accurate mapping of accessibility features limits the ability to monitor and address these constraints effectively. This paper introduces a framework for Automating City Accessibility Mapping using AI (ACAMAI), that is, provides an AI-assisted pipeline for the automated identification and geolocation of urban accessibility constraints using Google Street View (GSV) panoramas. The ACAMAI pipeline comprises two main stages: (i) training a YOLOv8 object detector to recognise accessibility-related features, such as curb ramps, missing ramps, obstacles and surface problems, in 2D sidewalk images; and (ii) scanning 360° GSV panoramas by extracting multiple perspective views to be analysed by the trained model. The model was trained on a combination of international (Project Sidewalk Dataset—PSD) and local (Porto Dataset—PTD) datasets, achieving high performance across classes, including 91% recall and 85% precision for curb ramps. In the panorama scanning stage, using a fine angular iterative step (2°) maximised the recall, reaching 90% for curb ramps and 93% for obstacles in a locally annotated dataset (GSV Panorama Porto Dataset—GSV-PPD). Although this improved detection coverage, it also led to a high number of redundant predictions, which contributed to a reduced overall precision. Finally, identified constraints are georeferenced and mapped onto OpenStreetMap (OSM), supporting scalable and inclusive urban planning.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"7 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145824642","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}

引用次数: 0

A Decentralised Framework for Peer-to-Peer Energy Interactions in a Smart Residential Microgrid 智能住宅微电网中点对点能源交互的分散框架

IF 2.3

IET Smart Cities Pub Date : 2025-11-15 DOI: 10.1049/smc2.70019

Saif Mohanad Maher, Tohid Ghanizadeh Bolandi, Sajjad Golshannavaz

{"title":"A Decentralised Framework for Peer-to-Peer Energy Interactions in a Smart Residential Microgrid","authors":"Saif Mohanad Maher, Tohid Ghanizadeh Bolandi, Sajjad Golshannavaz","doi":"10.1049/smc2.70019","DOIUrl":"10.1049/smc2.70019","url":null,"abstract":"The emergence of advanced home technology and the incorporation of distributed energy resources (DERs) have markedly heightened the necessity for energy management solutions that balance technical performance with economic efficiency in smart residential microgrid (SRMG). In the absence of effective collaboration and energy interactions among smart homes, imbalances in the SRMG load profile may occur, risking violations of technical standards. This study introduces a decentralised framework for SRMG that includes diverse smart homes engaged in peer-to-peer (P2P) energy interactions. The framework is designed to minimise variations in the SRMG load profile while also reducing expenses for smart homes, all while ensuring resident comfort through P2P interactions. The home energy management (HEM) system seeks to optimise energy costs by utilising DER capabilities to facilitate P2P interactions and maintain bidirectional communication with the SRMG operator (SRMGO). Continuous data sharing between the SRMGO and HEM systems is crucial for optimising the load profile in a decentralised framework. This enables about a 4.25% reduction in load profile deviations without raising energy costs, showing that decentralised P2P energy interactions improve load management in SRMG and cost stability in smart homes. Simulation results generated using general algebraic modelling system (GAMS) software demonstrate that integrating P2P energy strategies within a decentralised framework can effectively fulfil both the technical requirements of the SRMG and the financial goals of individual smart homes.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"7 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145522251","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}

引用次数: 0

100 European Cities' Path to Climate Neutrality by 2030 100个欧洲城市到2030年实现气候中和之路

IF 2.3

IET Smart Cities Pub Date : 2025-11-08 DOI: 10.1049/smc2.70017

Aapo Huovila, Mari Hukkalainen

引用次数: 0

A Framework for Mapping Socio-Ecological Dynamics to Support Sustainable Post-Mining Regional Transitions 社会生态动态绘图框架以支持可持续的采矿后区域转型

IF 2.3

IET Smart Cities Pub Date : 2025-10-22 DOI: 10.1049/smc2.70016

Yuliang Jiang, Elisa Palazzo, Simit Raval

{"title":"A Framework for Mapping Socio-Ecological Dynamics to Support Sustainable Post-Mining Regional Transitions","authors":"Yuliang Jiang, Elisa Palazzo, Simit Raval","doi":"10.1049/smc2.70016","DOIUrl":"10.1049/smc2.70016","url":null,"abstract":"Mapping socio-ecological dynamics reveals how human and natural systems interact over time, supporting informed planning and balanced regional development. By detecting patterns in these interactions, mapping supports policymakers in navigating complex transitions and guiding sustainable regional planning. These transitions are particularly evident in regions experiencing synchronised coal mine and coal-fired power plant closures. Despite ongoing rehabilitation efforts worldwide, few studies explore how socio-ecological factors interact and evolve or employ mapping as an integrative tool. Directly addressing this gap, this study innovatively introduces a framework that treats coal mines and power plants as a connected nexus, analysing their regional impacts through an integrated mapping approach. This framework combines geospatial mapping with exploratory, causal, and predictive modelling to analyse spatiotemporal shifts in post-mining landscapes. Applied to the Latrobe Valley in Australia, the framework reveals the closure caused sharp declines in income and nighttime light intensity, with no immediate recovery in native vegetation. Projections indicate that without early intervention, the Valley risks deepening regional socioeconomic decline. Translating multifaceted data into an analytical format enables stakeholders to see through complexity, understand interconnected socio-ecological dynamics across phases, and coordinate governance to manage regional changes for balanced development strategies.","PeriodicalId":34740,"journal":{"name":"IET Smart Cities","volume":"7 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/smc2.70016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366499","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}

引用次数: 0