2022 IEEE International Smart Cities Conference (ISC2)最新文献_第3页

Matching Traffic Lights to Routes for Real-World Deployments of Mobile GLOSA Apps 将交通灯与实际部署的移动GLOSA应用程序的路线相匹配

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9922560

Philipp Matthes, T. Springer

{"title":"Matching Traffic Lights to Routes for Real-World Deployments of Mobile GLOSA Apps","authors":"Philipp Matthes, T. Springer","doi":"10.1109/ISC255366.2022.9922560","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922560","url":null,"abstract":"Green Light Optimized Speed Advisory (GLOSA) apps provide speed recommendations for drivers to pass traffic lights during their green phases. In this way, the comfort and efficiency of traveling can be significantly improved. Thus, GLOSA apps are a valuable contribution to smart mobility. Mobile GLOSA apps provide an attractive alternative to static info signs, but they need to anticipate upcoming traffic lights that the vehicle will pass. While this imposes no challenge for predominating research within simulation or test track environments, real-world deployments need to correctly match a few from thousands of traffic lights to a route. In this paper, we discuss in a novel approach that MAP topologies, an international ETSI standard for turn geometries of traffic lights, can be used to perform this matching. However, routing is usually performed on public map data, which is not aligned with the MAP topologies. We explore two computational methods, specifically map-matching as preprocessing for adjacency lookup and topologic feature matching, that account for discrepancies between the MAP topologies and the route. We show that the core problem can be addressed using these algorithms to enable large-area deployments of real-world mobile GLOSA apps. In a comparative evaluation, the topologic feature matching technique achieved an F1 score of 89.5%, while the map-matched adjacency lookup method only achieved an F1 score of 48.3%. We analyze this performance gap and conclude further research directions.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"124 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124267478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards a Methodology for the Characterization of IoT Data Sets of the Smart Building Sector 智能建筑领域物联网数据集表征方法研究

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9921984

Louis Closson, C. Cérin, D. Donsez, D. Trystram

{"title":"Towards a Methodology for the Characterization of IoT Data Sets of the Smart Building Sector","authors":"Louis Closson, C. Cérin, D. Donsez, D. Trystram","doi":"10.1109/ISC255366.2022.9921984","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9921984","url":null,"abstract":"The long-term objective of the paper aims to provide decision aid support to a technical smart buildings manager to potentially reduce the emission of data produced by sensors inside a building and, more generally, to acquire knowledge on the data produced in the facility. As the first step, the paper proposes to characterize the smart-building ecosystem's Internet-of-things (IoT) data sets. The description and the construction of learning models over data sets are crucial in engineering studies to advance critical analysis and serve diverse researchers' communities, such as architects or data scientists. We examine two data sets deployed in one location in the Grenoble area in France. We assume that the building is an autonomic computing system. Thus, the underlying model we deal with is the well-known MAPE-K methodology introduced by IBM. The paper mainly addresses the analysis component and the adjacent connector component of the MAPE-K model. The content of this layer, and its organization, constitutes the methodological point we put forward. Consequently, we automatically provide a complete set of practices and methods to pass to the planning component of the MAPE-K model. We also sketch a semi-automatic way of reducing the number of measures done by sensors. In the background of our study, we aim to reduce the operational cost of making measures with a much more sober approach than the current one. We also discuss in profound the main findings of our work. Finally, we provide insights and open questions for future outcomes based on our experience.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129477692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reduction of the Cost Needed for Converting a Conventional Building to a Nearly Zero Energy Building 降低将传统建筑转换为几乎零能耗建筑所需的成本

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9922223

C. Mademlis, N. Jabbour, E. Tsioumas, Markos Kosseoglou, D. Papagiannis

{"title":"Reduction of the Cost Needed for Converting a Conventional Building to a Nearly Zero Energy Building","authors":"C. Mademlis, N. Jabbour, E. Tsioumas, Markos Kosseoglou, D. Papagiannis","doi":"10.1109/ISC255366.2022.9922223","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922223","url":null,"abstract":"This paper investigates the challenging problem of reducing the cost needed for converting a conventional building to a nearly-zero energy building (nZEB). This can be at-tained by properly selecting the sizing of the domestic renewable energy sources (DRES) and battery storage system (BSS), and improving the performance of the building electric microgrid. Thus, on the one side, a new methodology based on the genetic algorithm (GA) is proposed to properly determine the correct size of the DRES and BSS. On the other side, an integrated control method based on the GA technique too for the energy man-agement in the home microgrid is suggested that is accomplished through a correct balance between the maximum exploitation of the DRES and BSS, comfort of the building residents, and en-ergy saving. Therefore, the problem of reducing the cost for de-veloping an nZEB is addressed by reducing the two cost components, i.e. installation and operating cost. Moreover, the influ-ence of the one cost on the other is considered, and therefore an integrated calculation method is developed that provides a ho-listic solution for the nZEB's cost problem. The proposed calcu-lation strategy has been experimentally validated in a pilot building and several experimental results are presented in this paper to demonstrate the effectiveness, practicality, and functionality of the suggested methodology.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128574076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Edge-based Situ-aware Reinforcement Learning for Traffic Congestion Mitigation 基于边缘的态势感知强化学习缓解交通拥堵

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9922461

Chen-Yeou Yu, Wensheng Zhang, Carl K. Chang

引用次数: 0

An Experiment Orchestration Platform to Support Smart City Experiential Learning 支持智慧城市体验式学习的实验编排平台

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9922559

Nathan Puryear, Patrick J. Martin, M. Kuzlu, Özgür Güler, V. Jovanovic, S. Abdelwahed

引用次数: 2

Estimated Time of Arrival in Autonomous Vehicles Using Gradient Boosting: Real-life case study in public transportation 使用梯度提升的自动驾驶车辆估计到达时间:公共交通的现实案例研究

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9921853

Evangelos Antypas, Georgios Spanos, Antonios Lalas, K. Votis, D. Tzovaras

{"title":"Estimated Time of Arrival in Autonomous Vehicles Using Gradient Boosting: Real-life case study in public transportation","authors":"Evangelos Antypas, Georgios Spanos, Antonios Lalas, K. Votis, D. Tzovaras","doi":"10.1109/ISC255366.2022.9921853","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9921853","url":null,"abstract":"Autonomous Vehicles (AVs) are expected to revolutionise the methods of transportation. Research and innovation in this field is making huge leaps in the last few years, whether it considers vehicles used for private or public transport. Predicting the Estimated Time of Arrival (ETA) is a very important attribute associated with Public Transport (PT). Especially with the rise of AVs' adoption, PT is expected to follow this trend. Therefore, ETA prediction is deemed to be a service that interests the majority of PT stakeholders. PT is a field that automation benefits both stakeholders and commuters, and this research aims to provide a benchmark considering AVs in PT. Within this work, Gradient Boosting (GB) techniques for ETA prediction were employed, namely eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost) and Light Gradient Boosting Machines (LightGBM). This study proposes competitive ETA prediction methods in Autonomous Buses, while the results of this research are very encouraging and aim to contribute to the overall investigations in the field of autonomous and automated PT.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"80 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133391723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigation of Shared-Bike Demand Using Data Analytics 基于数据分析的共享单车需求调查

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9921867

Madiha Bencekri, Adnane Founoun, A. Haqiq, A. Hayar

{"title":"Investigation of Shared-Bike Demand Using Data Analytics","authors":"Madiha Bencekri, Adnane Founoun, A. Haqiq, A. Hayar","doi":"10.1109/ISC255366.2022.9921867","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9921867","url":null,"abstract":"Sustainable development commitments are of concern to the city's decision-makers as well as significantly impacting the existing transportation systems. The concept of the smart city and precisely the component of smart mobility centered on the user and soft transport comes to support this approach of transformation which aims at the low carbon city. Similarly, reducing carbon emissions is one of the main objectives of a smart city, thereby comes the focus on enhancing eco-friendly and active transportation means, for instance, the shared-bike system. The mode benefits from the technology implemented within the smart city concept. Seoul Government has implemented a shared-bike program “Ttareungyi” in 2015, within the big vision of “low carbon green growth”. However, the program struggles to achieve the targeted demand. Therefore, this study is using data analytics to help enlighten decision-makers about the shared-bike system and provide insights for future development. The research was conducted to investigate the influence of the built environment, including slope, land use mix, and centrality parameters, the influence of transport infrastructure, including bike and transit infrastructure, and the influence of the socio-economic characteristics, including population, retail number, car ownership, and job offers on bike demand. And to predict bike demand based on the mentioned variables using the ridge regression method. Results revealed that dock number, population density, and car ownership have a significant positive impact on biking demand, while slope has a significant negative impact. In contradiction to the research hypothesis, land use mix revealed a weak impact on biking demand using random forest, and a negative influence using ridge regression.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131786237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data Cleaning to fine-tune a Transfer Learning approach for Air Quality Prediction 数据清洗微调空气质量预测的迁移学习方法

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9921836

Marie Njaime, Fahed Abdallah Olivier, H. Snoussi, Judy Akl, C. Chahla, H. Omrani

引用次数: 1

Collectively Sharing Human Eyes and Ears as Smart City Digital Platforms 共享人的眼睛和耳朵作为智慧城市数字平台

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9922038

Risa Kimura, Tatsuoki Nakajima

引用次数: 1

Divide and Survey: Observability Through Multi-Drone City Roadway Coverage 分测:多无人机城市道路覆盖的可观测性

2022 IEEE International Smart Cities Conference (ISC2) Pub Date : 2022-09-26 DOI: 10.1109/ISC255366.2022.9922207

Huzeyfe Kocabas, Christopher Allred, Mario Harper

引用次数: 1