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8th IEEE International Smart Cities Conference, ISC2 2022

作者： Founoun, Adnane El Ghazouani, Laila Haqiq, Abdelkrim Hayar, Aawatif Radoine, Hassan Hassan First University of Settat Faculty of Sciences and Techniques Computer Networks Mobility and Modeling Laboratory: IR2M Settat26000 Morocco School of Architecture Planning and Design Mohammed Vi Polytechnic University Benguerir Morocco Ritm Lab R&d Centre Hassan Ii University Ced ENSEM/TICDev Casablanca Morocco

ISBN: (数字)9781665485616

ISBN: (纸本)9781665485616

To provide different services to smart cities, many new approaches were used, including the strategic approach and the techno-human-centric approach. When it combines both the human aspect through its sensitivities and the technical aspect of data management to enable the city's stakeholders to act better. Indeed, a new governance framework is possible through the introduction of human intelligence to answer specific questions. It's about putting citizens at the center of the smart city issue while putting a coalition with new technologies. In this paper, we suggest validation of weather data, temperature, and wind, according to citizens' perceptions through a gaming scenario. The use of this mobile platform will assist stakeholders towards a roadmap for future urban design. This will be done by building up a database of citizens' perceptions and appreciations. Also, the wide range of sites of interest will allow an urban promotion and accompany the cultural life of the city. This will be possible by inviting subscribers to go and visit these places subject to promotions. © 2022 IEEE.

关键词： Climate change

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Sound Noise Monitoring using Wireless Sensor Networks in Annaba City

Sound Noise Monitoring using Wireless Sensor Networks in Ann...

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International Conference on Information Technology (ICIT)

作者： Mohamed Fezari Ali Al Dahoud Mohamed Arif Ahmad Al-Dahoud Hani M. Al-Mimi Laboratory of Automatic and Signals Annaba Faculty of Engineering Badji Mokhtar Annaba University Annaba Algeria Dept. of Computer Scinece Faculty of IT Al-Zaytoonah University of Jordan Amman Jordan Faculty of Architecture and Design Al-Zaytoonah University of Jordan Amman Jordan

The aim of this work is to design a sound logger system for environmental monitoring using wireless sensors network WSN. The proposed solution is to place nodes in a fixed location in the city center of Annaba. These devices collect noise levels, process the information then transmit a code containing node position, sound level, and other data concerning the environment. A central unit will process the collected information from different nodes again then a GUI program will represent the data on a map concerning the selected area of Annaba city. The improvement is done on the choice of quality/price sensors; on designing an easy-to-understand and monitor GUI.

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Prediction of Leakage from an Axial Piston Pump Slipper with Circular Dimples Using Deep Neural Networks

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Chinese Journal of Mechanical Engineering 2020年第2期33卷 111-121页

作者： Ozkan Ozmen Cem Sinanoglu Abdullah Caliskan Hasan Badem Tribology Laboratory Industrial Design EngineeringFaculty of EngineeringErciyes UniversityKayseri 38039Turkey Biomedical Engineering Faculty of Engineering and Natural SciencesIskenderun Technical UniversityHatayTurkey Computer Engineering Faculty of Engineering and ArchitectureKahramanmaraşSutcu Imam UniversityKahramanmaraşTurkey

Oil leakage between the slipper and swash plate of an axial piston pump has a significant effect on the efficiency of the ***,it is extremely important that any leakage can be *** study investigates the leakage,oil film thickness,and pocket pressure values of a slipper with circular dimples under different working *** results reveal that flat slippers suffer less leakage than those with textured ***,a deep learning-based framework is proposed for modeling the slipper *** framework is a long short-term memory-based deep neural network,which has been extremely successful in predicting time *** model is compared with four conventional machine learning *** addition,statistical analyses and comparisons confirm the superiority of the proposed model.

关键词： Slipper Leakage Circular dimpled Long short-term memory Deep neural network

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Research on Art Style Rendering Algorithm Based on computer Vision

Research on Art Style Rendering Algorithm Based on Computer ...

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Internet of Things, Robotics and Distributed Computing (ICIRDC), International Conference on

作者： Heng Wang Yanwei Zhou Zihao Zhang Tianjin Academy of Fine Arts School of Design and Art Tianjin China School of Architecture and Art Design Hebei University of Technology Tianjin China Center for Urban and Rural Renewal and Architectural Heritage Conservation Hebei University of Technology Tianjin China Hebei Key Laboratory of Healthy Living Environment Tianjin China Samueli Electrical and Computer Engineering University of California Los Angeles USA

For a long time, the art of painting has been mysterious to most ordinary people. Since ancient times, countless artists have devoted their lives to painting works, and many masters have formed their own unique painting style. With the rapid development of computer technology, we can extract and imitate the painting styles of various famous artists, and even ordinary people can pry into the mysteries of artistic style, so as to make works with master artistic style. This style rendering technology is called style style transfer. With the continuous development of stereoscopic display technology, people’s demand for more diversified stereoscopic display effects is also increasing. Chinese ink art, as one of the typical representatives of Oriental painting art, has positive significance and far-reaching influence by combining it with three-dimensional display technology. Through the study of Chinese traditional landscape painting and a large number of research on the simulation results of ink style at home and abroad, this paper focuses on the freehand ink style rendering of three-dimensional terrain, and designs a ink style rendering method based on program gray coloring, which can easily observe the effect of ink change when the terrain changes.

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ReCo: A Dataset for Residential Community Layout Planning

arXiv

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arXiv 2022年

作者： Chen, Xi Xiong, Yun Wang, Siqi Wang, Haofen Sheng, Tao Zhang, Yao Ye, Yu Shanghai Key Laboratory of Data Science School of Computer Science Fudan University Shanghai China College of Design and Innovation Tongji University Shanghai China College of Architecture and Urban Planning Tongji University Shanghai China

Layout planning is centrally important in the field of architecture and urban design. Among the various basic units carrying urban functions, residential community plays a vital part for supporting human life. Therefore, the layout planning of residential community has always been of concern, and has attracted particular attention since the advent of deep learning that facilitates the automated layout generation and spatial pattern recognition. However, the research circles generally suffer from the insufficiency of residential community layout benchmark or high-quality datasets, which hampers the future exploration of data-driven methods for residential community layout planning. The lack of datasets is largely due to the difficulties of large-scale real-world residential data acquisition and long-term expert screening. In order to address the issues and advance a benchmark dataset for various intelligent spatial design and analysis applications in the development of smart city, we introduce Residential Community Layout Planning (ReCo) Dataset, which is the first and largest open-source vector dataset related to real-world community to date. ReCo Dataset is presented in multiple data formats with 37,646 residential community layout plans, covering 598,728 residential buildings with height information. ReCo can be conveniently adapted for residential community layout related urban design tasks, e.g., generative layout design, morphological pattern recognition and spatial evaluation. To validate the utility of ReCo in automated residential community layout planning, two Generative Adversarial Network (GAN) based generative models are further applied to the dataset. We expect ReCo Dataset to inspire more creative and practical work in intelligent design and beyond. The ReCo Dataset is published at: https://***/fdudsde/reco-dataset and related code can be found at: https://***/FDUDSDE/ReCo-Dataset. © 2022, CC BY-NC-SA.

关键词： Deep learning

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A Shared Pose Regression Network for Pose Estimation of Objects from RGB Images

A Shared Pose Regression Network for Pose Estimation of Obje...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Stefan Hein Bengtson Hampus Åström Thomas B. Moeslund Elin A. Topp Volker Krueger Department of Architecture Design and Media Technology Visual Analysis and Perception (VAP) Laboratory Pioneer Centre for AI Denmark Aalborg University Aalborg Denmark Department of Computer Science Lund University Robotics and Semantic Systems Lund Sweden

In this paper we propose a shared regression network to jointly estimate the pose of multiple objects, replacing multiple object-specific solutions. We demonstrate that this shared network can outperform other similar approaches that rely on multiple object-specific models by evaluating it on the TLESS dataset using the VSD (Visible Surface Discrepancy). Our approach offers a less complex solution, with fewer parameters, lower memory consumption and less training required. Furthermore, it inherently handles symmetric objects by using a depth-based loss during training and can predict in real-time. Finally, we show how our proposed pipeline can be used for fine-tuning a feature extractor jointly on all objects while training the shared pose regression network. This fine-tuning process improves the pose estimation performance.

关键词： Training Pose estimation Memory management Pipelines Feature extraction Rendering (computer graphics) Real-time systems

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Τhe effect of artificial lighting on both biophilic and human-centric design

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Journal of Building Engineering 2023年 76卷

作者： Madias, Evangelos-Nikolaos D. Christodoulou, Konstantinos Androvitsaneas, Vasilios P. Skalkou, Aikaterini Sotiropoulou, Sophia Zervas, Efthimios Doulos, Lambros T. School of Applied Arts and Sustainable Design Hellenic Open University Parodos Aristotelous 18 Patras 26335 Greece Lighting Laboratory School of Electrical and Computer Engineering National Technical University of Athens 9 Iroon Politechniou Str. Zografou Campus AthensGR-15780 Greece High Voltage and Electrical Measurements Laboratory School of Electrical and Computer Engineering National Technical University of Athens 9 Iroon Politechniou Str. Zografou Campus AthensGR-15780 Greece Department of Electrical and Electronics Engineering School of Engineering University of West Attica 250 Thivon Ave. Ancient Olive Grove Campus Athens-Egaleo GR-12241 Greece Department of Interior Architecture University of West Attica 28 Agiou Spyridonos Egaleo Athens12243 Greece

The indoor environmental quality is very significant as humans spend more than 90% in indoor space. Biophilic design of indoor spaces has become a popular approach in the design of indoor building spaces sector using green walls, especially in offices, leisure and hospitality facilities. So far there exist neither guidelines with the proper Spectral Power Distribution (SPD) except for agricultural applications or intensity levels of lighting nor the proper spectral indices to transform the photopic illuminance to a new type of photometric quantity for biophilic design. On the other hand, for human centric lighting the Equivalent Melatonin Illuminance is already introduced. The aim of paper is to define the appropriate lighting conditions, not only for humans, but also for interior plants. A new metric was introduced for the biophilic design named Equivalent Photosynthetic Illuminance. The new metric was examined for two human-centric lighting luminaires and compared with the corresponding human centric lighting metrics in order to create a lighting design guide for energy-sustainable, biophilic and human-centered lighting. The different SPDs highlighted the counterbalancing impact(s) of such luminaires, between biophilic and human-centered design. The differences concerning their impact on interior lighting design were identified with regards to energy consumption, meaning that the compliance of the lighting conditions to both humans and plants results to higher energy consumption. Depending on the SPD and luminous efficacy of artificial lighting, the additional power density for proper planning of biophilic design can vary from 23.5W/m2 to 52.4W/m2 in the areas in which are applied. © 2023 Elsevier Ltd

关键词： Energy efficiency

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computer vision-based analysis of buildings and built environments: A systematic review of current approaches

arXiv

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arXiv 2022年

作者： Starzyńska, Malgorzata B. Roussel, Robin Jacoby, Sam Asadipour, Ali Laboratory for Design and Machine Learning Royal College of Art School of Architecture United Kingdom Kensington Gore South Kensington LondonSW7 2EU United Kingdom Computer Science Research Centre Royal College of Art Research Centres Hester Road Battersea LondonSW11 4AN United Kingdom

Analysing 88 sources published from 2011 to 2021, this paper presents a first systematic review of the computer vision-based analysis of buildings and the built environments to assess its value to architectural and urban design studies. Following a multi-stage selection process, the types of algorithms and data sources used are discussed in respect to architectural applications such as a building classification, detail classification, qualitative environmental analysis, building condition survey, and building value estimation. This reveals current research gaps and trends, and highlights two main categories of research aims. First, to use or optimise computer vision methods for architectural image data, which can then help automate time-consuming, labour-intensive, or complex tasks of visual analysis. Second, to explore the methodological benefits of machine learning approaches to investigate new questions about the built environment by finding patterns and relationships between visual, statistical, and qualitative data, which can overcome limitations of conventional manual analysis. The growing body of research offers new methods to architectural and design studies, with the paper identifying future challenges and directions of research. © 2022, CC BY-NC-ND.

关键词： Machine learning

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The “15-minutes station”: a case study to evaluate the pedestrian accessibility of railway transport in Southern Italy

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Transportation Research Procedia 2023年 69卷 536-543页

作者： Martina Fazio Fabio Borghetti Nadia Giuffrida Michela Le Pira Michela Longo Matteo Ignaccolo Giuseppe Inturri Roberto Maja University of Catania Department of Physics and Astronomy Via Santa Sofia 64 Catania 95125 Italy Politecnico di Milano Design Department Mobility and Transport Laboratory Via Candiani 72 Milano 20158 Italy Polytechnic University od Bari Via Edoardo Orabona 4 70126 Bari BA Italy University of Catania Department of Civil Engineering and Architecture Via Santa Sofia 64 Catania 95125 Italy Politecnico di Milano Department of Energy Via La Masa 36 Milano 20156 Italy University of Catania Department of Electrical Electronic and Computer Engineering Via Santa Sofia 64 Catania 95125 Italy

The recent sustainability challenges that our world is facing have raised, more than ever, the attention to the mobility of passengers and freight in the European and international agendas. The energy transition that has begun globally requires identifying and adopting safe, resilient, and increasingly sustainable mobility solutions. In this perspective, the modal split of passengers plays an essential role. One of the main encouraged policies is to promote an efficient mass rapid transit in urban and suburban areas. More in detail, when considering rail transport, it is necessary to analyze and evaluate the role of stations from at least two points of view: i) the ease of access to the station; ii) the opportunities that can be easily reached in its surroundings, following the concept of the “15-minutes” city. These two issues should be properly addressed to guarantee the role of railway stations as an access point to the transport system and an infrastructural element that can enhance a territory. Starting from these considerations, this research proposes a GIS-based methodology able to analyse railway stations from two points of view: i) walkability, considering the main functional characteristics of the transport network, and ii) impact on the territory, by identifying the services located in an area corresponding to “15-minutes” distances using active modes. For each railway station, the main activities in a 15-minute walking isochrone can be evaluated, both considering the walking distance on the pedestrian network and taking into account the current walkability of each link based on arc characteristics. This allows to study the accessibility of railway stations based on the current pedestrian network and the potential one with ideal characteristics. The method is applied to a case study located in Sicily (Italy), in the case of some urban stations. The final scope is to design a decision-support framework useful for railway station operators and local decisio

关键词： 15-minute city mass rapid transit sustainable mobility urban mobility GIS transport planning urban planning walkability Decision Support tool

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