Understanding Human Behaviors in Earthquakes to Improve Safety in Built Environment: A State of the Art on Sustainable and Validated Investigation Tools

2020 ◽  
pp. 297-307
Author(s):  
Enrico Quagliarini ◽  
M. Lucesoli ◽  
Gabriele Bernardini
Keyword(s):  
Built Environment ◽  
State Of The Art ◽  
Human Behaviors

scholarly journals Big Building Data 2.0 - a Big Data Platform for Smart Buildings

2021 ◽  
Vol 2042 (1) ◽  
pp. 012016
Author(s):  
Lucy Linder ◽  
Frédéric Montet ◽  
Jean Hennebert ◽  
Jean-Philippe Bacher
Keyword(s):  
Big Data ◽  
Built Environment ◽  
Simple Proof ◽  
Applied Research ◽  
State Of The Art ◽  
Scale Up ◽  
Heterogeneous Environment ◽  
Data Platform ◽  
Single Data ◽  
Data Location

Abstract The modern built environment is now connected. Multiple software and protocols are used in buildings of many kinds, thus creating a fascinating and heterogeneous environment. Within this context, applied research can be complicated and would benefit from a single data location across projects and users. The first version of BBData tried to solve this problem, BBData v2.0 is an update with a better-defined scope and a new codebase. The solution has been open sourced and simplified with a full software rewrite. Its components are now state-of-the-art and proven to be stable in industrial settings. The achieved performances have been thoroughly tested. Together with its new architecture, BBData v2.0 now accommodates the needs of modern experiments; efficient for simple proof of concepts while keeping the possibility to scale up to city-level projects. This flexibility makes BBData a good candidate for research while being able to scale in production settings.

scholarly journals Behavior-Interior-Aware User Preference Analysis Based on Social Networks

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Can Wang ◽  
Tao Bo ◽  
Yun Wei Zhao ◽  
Chi-Hung Chi ◽  
Kwok-Yan Lam ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
State Of The Art ◽  
Threshold Model ◽  
User Preference ◽  
Human Behaviors ◽  
State Dependent ◽  
Linear Threshold ◽  
Temporal Features ◽  
Linear Threshold Model ◽  
Joint Consideration

There is a growing trend recently in big data analysis that focuses on behavior interiors, which concern the semantic meanings (e.g., sentiment, controversy, and other state-dependent factors) in explaining the human behaviors from psychology, sociology, cognitive science, and so on, rather than the data per se as in the case of exterior dimensions. It is more intuitive and much easier to understand human behaviors with less redundancy in concept by exploring the behavior interior dimensions, compared with directly using behavior exteriors. However, they usually approach from a unidimensional perspective with a lack of a sense of interrelatedness. Thus, integrating multiple behavior dimensions together into some numerical measures to form a more comprehensive view for subsequent prediction processes becomes a pivotal issue. Moreover, these studies usually focus on the magnitude but neglect the associated temporal features. In this paper, we propose a behavior interior dimension-based neighborhood collaborative filtering method for the top-N hashtag adoption frequency prediction that takes into account the interdependence in temporal dynamics. Our proposed approach couples the similarity in user preference and their impact propagation, by integrating the linear threshold model and the enhanced CF model based on behavior interiors. Experiments on Twitter demonstrate that the behavior-interior-aware CF models achieve better adoption prediction results than the state-of-the-art methods, and the joint consideration of similarity in user preference and their impact propagation results in a significant improvement than treating them separately.

scholarly journals ON INCLUSION, DIVERSITY, EQUITY, AND ACCESSIBILITY IN CIVIL ENGINEERING AND ARCHITECTURAL DESIGN. A REVIEW OF ASSESSMENT TOOLS.

2021 ◽  
Vol 1 ◽  
pp. 2297-2306
Author(s):  
Matteo Zallio ◽  
P. John Clarkson
Keyword(s):  
Literature Review ◽  
Built Environment ◽  
20Th Century ◽  
Systematic Literature Review ◽  
Architectural Design ◽  
Civil Engineering ◽  
State Of The Art ◽  
Assessment Tools ◽  
Built Environments ◽  
Holistic Assessment

AbstractSince the mid-20th century, assessing the performance of the built environment was recognized as an instrument to improve the efficiency in the design and construction processes. However, it appears difficult to identify assessment tools that currently include a holistic assessment of inclusion, diversity, equity and accessibility criteria for the built environments.A systematic literature review was performed to define the state of the art of assessment tools in the domain of civil engineering and architectural design, and to identify gaps in the criteria of inclusion, diversity, equity, and accessibility.The review highlighted three fundamental aspects. First, how the binomial relationship between regulations and assessment tools is not mutually exclusive. Second, how the process of assessing buildings is shifting towards mixed evaluation methods. Third, how assessment tools have been developed with a perceivable evolutionary latency from when standards were released.With this work, we produced a state-of-the-art overview about inclusion, diversity, equity and accessibility (IDEA) in the built environment, to inform the development of tools that will foster the design of future inclusive environments.

scholarly journals Research Challenges and Advancements in the field of Sustainable Energy Technologies in the Built Environment

2020 ◽  
Vol 12 (20) ◽  
pp. 8417 ◽  
Author(s):  
Paris A. Fokaides ◽  
Rasa Apanaviciene ◽  
Jurgita Černeckiene ◽  
Andrius Jurelionis ◽  
Egle Klumbyte ◽  
...  
Keyword(s):  
Built Environment ◽  
Construction Industry ◽  
State Of The Art ◽  
Sustainable Energy ◽  
Sustainable Construction ◽  
Low Carbon ◽  
Building Sector ◽  
The Sustainable Development ◽  
Scientific Discussion ◽  
Energy Assessment

Inevitably, the 21st century has initiated a series of developments in the construction industry, leading to its digitalization and resulting in a series of innovative approaches and practices. At the same time, the construction industry, being one of the main global environment polluters, should fulfil well-established, as well as novel, sustainability requirements in order to evolve in harmony with the rising concerns on the availability of natural resources. This overview study aims to present the main developments, research, and scientific challenges in the field of sustainable construction, emphasizing the field of energy. The study aims to present a state-of-the-art scientific discussion on the sustainable built environment topic by analyzing cutting edge topics in the fields of building elements and whole building energy assessment, of indoor air quality and low carbon buildings, as well as on sustainable energy systems and smart buildings. The study also presents the state-of-the-art in existing tools which are adopted for the assessment of the sustainable built environment, including the use of digital tools and building information modelling for the energy assessment of the built environment, as well as the application of Life Cycle Assessment on building-related processes. Cross cutting issues related to the analysis of the building sector in the Industry 4.0 era, such as sustainability management topics and environmental geomatics are also discussed. The study concludes in those fields which will be of interest of the scientific community in the following years, towards achieving the goals of the sustainable development of the building sector.

Probabilistic Modeling of Driver Behaviors at Urban Crossroad Interactions

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Yuan-Cheng Liu ◽  
Kuei-Yuan Chan
Keyword(s):  
Virtual Environments ◽  
Autonomous Vehicles ◽  
State Of The Art ◽  
Autonomous Vehicle ◽  
Vehicle Speed ◽  
Crash Analysis ◽  
Characteristic Parameters ◽  
Human Behaviors ◽  
Simulated Environments ◽  
Traffic Characteristic

Abstract The interactions with human drivers is one of the major challenges for autonomous vehicles. In this study, we consider urban crossroads without signals where driver interactions are indispensable. Crossroads are parameterized to be used in studying how drivers pass the crossroad while maintaining a desired speed without collision. We define a probability of yielding for each car as a function of vehicle speed and the distance-to-intersection for both vehicles, while the interactions between vehicles are characterized by a point of action for incoming vehicles from different directions. Driver behaviors in terms of acceleration/deceleration given current circumstances are also modeled probabilistically. The method is then analyzed and validated by data collected from human drivers in the simulated environments. The result shows comparable prediction accuracy to the state-of-the-art method, where characteristic parameters of drivers are also shown to be critical for the behavior predictions. We also extend our model to two real-world urban crossroads applications : crash analysis and traffic characteristic parameters identification. In both cases, our prediction results are analogous to those acquired in virtual environments. For autonomous vehicle, our method can help building a computer-driving logic that matches human behaviors, such that interactions between different drivers will be more intuitive.

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