IET Smart Cities最新文献_第3页

IF 2.3

IET Smart Cities Pub Date : 2026-02-23

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

IF 2.3

IET Smart Cities Pub Date : 2026-02-20

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

IF 2.3

IET Smart Cities Pub Date : 2026-01-12

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

IF 2.3

IET Smart Cities Pub Date : 2026-01-09

引用次数: 0

IF 2.3

IET Smart Cities Pub Date : 2025-12-29

引用次数: 0

IF 2.3

IET Smart Cities Pub Date : 2025-12-13

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