bluuebunny/crossref_metadata_2025_split huggingface dataset:
How Innovative Mobility Can Drive Sustainable Development: Conceptual Foundations and Use Cases Using the Example of the iCity Ecosystem for Innovation
Authors: Popovic Tobias , Bäumer Thomas , Gökdemir Ezgi , Silberer Jan 
Published: October 2022

AbstractEconomy and society today face a multitude of complex challenges (“grand challenges”) like climate change, demographic change, urbanization, or digitalization, which create a constant demand for new technologies, services, business models, and consequently innovative solutions. In this light, the mobility sector has undergone a great change over the past few years, which is formed by digital technologies on a large scale. Against this background, this article will demonstrate, based on the example of the iCity research project, to what extent the research design of transdisciplinary living labs can serve as a basis for the development of innovative and sustainable mobility solutions. At the same time, the influence of digitalization which plays a major role in developing real implementable solutions for such challenges will be examined.
Case Study of a Hydrogen-Based District Heating in a Rural Area: Modeling and Evaluation of Prediction and Optimization Methodologies
Authors: Lust Daniel , Brennenstuhl Marcus , Otto Robert , Erhart Tobias , Schneider Dietrich , Pietruschka Dirk 
Published: October 2022

AbstractBuildings are accountable for about one third of the greenhouse gas emissions in Germany. An important step toward the reduction of greenhouse gases is to decarbonize the power productions and heating systems. However, in an energy system with a high share of renewable energy sources, large shares of energy have to be stored in summer for the winter season. Chemical energy storages, in this case hydrogen, can provide these qualities and offer diverse opportunities for coupling different sectors.In this work, a simulation model is introduced which combines a PEM electrolyzer, a hydrogen compression, a high-pressure storage, and a PEM fuel cell for power and heat production. Applied on a building cluster in a rural area with existing PV modules, this system is optimized for operation as a district heating system based on measured and forecasted data. Evolutionary algorithms were used to determine the optimized system parameters.The investigated system achieves an overall heat demand coverage of 63%. However, the local hydrogen production is not sufficient to meet the fuel cell demand. Several refills of the storage tanks with delivered hydrogen would be necessary within the year studied.
Parking and Charging: New Concepts for the Use of Intelligent Charging Infrastructure in Car Parks
Authors: Herrlich Esther , Schaich Elisabeth , Wagner Stephanie , Uckelmann Dieter 
Published: October 2022

AbstractA reliable charging infrastructure for electric vehicles used in individual transport including availability and accessibility is necessary because it contributes highly to the decision of purchasing a BEV (battery electric vehicle). In Germany, charging is mainly done at home; however, parking spots in car parks have the potential to densify charging infrastructure in semi-public spaces. Intelligent car parks represent further developments which add a variety of technologies, energy management tools and value-added services to parking in general. The article addresses the question of technical maturity of charging infrastructures used in intelligent car parks and their marketability. Examples are charging methods such as conductive and inductive charging or various payment options. Pilot projects are described, and possible concepts of charging in intelligent car parks are explained, thereby addressing a growing interest in the subject.
ARaaS: Context-Aware Optimal Charging Distribution Using Deep Reinforcement Learning
Authors: Sharif Muddsair , Heendeniya Charitha Buddhika , Lückemeyer Gero 
Published: October 2022

AbstractElectromobility has profound economic and ecological impacts on human society. Much of the mobility sector’s transformation is catalyzed by digitalization, enabling many stakeholders, such as vehicle users and infrastructure owners, to interact with each other in real time. This article presents a new concept based on deep reinforcement learning to optimize agent interactions and decision-making in a smart mobility ecosystem. The algorithm performs context-aware, constrained optimization that fulfills on-demand requests from each agent. The algorithm can learn from the surrounding environment until the agent interactions reach an optimal equilibrium point in a given context. The methodology implements an automatic template-based approach via a continuous integration and delivery (CI/CD) framework using a GitLab runner and transfers highly computationally intensive tasks over a high-performance computing cluster automatically without manual intervention.
A Multi-camera Mobile System for Tunnel Inspection
Authors: Alidoost Fatemeh , Austen Gerrit , Hahn Michael 
Published: October 2022

AbstractThe safety, proper maintenance, and renovation of tunnel structures have become a critical problem for urban management in view of the aging of tunnels. Tunnel inspection and inventory are regulated by construction laws and must be carried out at regular intervals. Advances in digitalization and machine vision technologies enable the development of an automated and BIM-based system to collect data from tunnel surfaces. In this study, a tunnel inspection system using vision-based systems and the related principles are introduced to measure the tunnel surfaces efficiently. In addition, the main components and requirements for subsystems are presented, and different challenges in data acquisition and point cloud generation are explained based on investigations during initial experiments.
Augmented Reality for Windy Cities: 3D Visualization of Future Wind Nature Analysis in City Planning
Authors: Harbola Shubhi , Storz Martin , Coors Volker 
Published: October 2022

AbstractEffective government management, convenient public services, and sustainable industrial development are achieved by the thorough utilization and management of green, renewable resources. The research and the study of meteorological data and its effect on devising renewable solutions as a replacement for nonrenewable ones is the motive of researchers and city planners. Sources of energy like wind and solar are free, green, and popularly being integrated into sustainable development and city planning to preserve environmental quality. Sensor networks have become a convenient tool for environmental monitoring. Wind energy generated through the use and maintenance of wind turbines requires knowledge of wind parameters such as speed and direction for proper maintenance. An augmented reality (AR) tool for interactive visualization and exploration of future wind nature analyses for experts is still missing. Existing solutions are limited to graphs, tabular data, two-dimensional space (2D) maps, globe view, and GIS tool designed for the desktop and not adapted with AR for easy, interactive mobile use. This work aims to provide a novel AR-based mobile supported application (App) that serves as a bridge between three-dimensional space (3D) temporal wind dataset visualization and predictive analysis through machine learning (ML). The proposed development is a dynamic application of AR supported with ML. It provides a user interactive designed approach, presenting a multilayered infrastructure process accessed through a mobile AR platform that supports 3D visualization of temporal wind data through future wind analysis. Thus, a novel AR visualization App with the prediction of wind nature using ML algorithms would provide city planners with advanced knowledge of wind conditions and help in easy decision-making with interactive 3D visualization.
Storing and Visualising Dynamic Data in the Context of Energy Analysis in the Smart Cities
Authors: Santhanavanich Thunyathep , Sihombing Rosanny , Kabiro Pithon Macharia , Würstle Patrick , Sini Sabo Kwado 
Published: October 2022

AbstractThere is increased activity in developing workflows and implementations in the context of urban energy analysis simulation based on 3D city models in smart cities. At the University of Applied Sciences Stuttgart (HFT Stuttgart), an urban energy simulation platform called ‘SimStadt’ has successfully been developed. It uses the CityGML 3D city model to simulate the heat demand, photovoltaic potential, and other scenarios that provide dynamic simulation results in both space and time dimensions. Accordingly, a tool for managing dynamic data of the CityGML models is required. Earlier, the CityGML Application Domain Extension (ADE) had been proposed to support additional attributes of the CityGML model; however, there is still a lack of open-source tools and platforms to manage and distribute the CityGML ADE data efficiently. This article evaluates and compares alternative methods to manage dynamic simulation results of the 3D city model and visualise these data on the 3D web-based smart city application, including the use of SimStadt web services, databases, and OGC SensorThings API standard.
Deep Learning Methods for Extracting Object-Oriented Models of Building Interiors from Images
Authors: Obrock Lars , Gülch Eberhard 
Published: October 2022

AbstractIn this chapter, we present an approach of enriching photogrammetric point clouds with semantic information extracted from images of digital cameras or smartphones to enable a later automation of BIM modelling with object-oriented models. Based on the DeepLabv3+ architecture, we extract building components and objects of interiors in full 3D. During the photogrammetric reconstruction, we project the segmented categories derived from the images into the point cloud. Based on the semantic information, we align the point cloud, correct the scale and extract further information. The combined extraction of geometric and semantic information yields a high potential for automated BIM model reconstruction.
On the Prospects of the Building Envelope in the Context of Smart Sustainable Cities: A Brief Review
Authors: Liebhart Heiko , Cremers Jan 
Published: October 2022

AbstractAccording to the World Urbanization Prospects of the United Nations (United Nations, Department of Economic and Social Affairs 2018), about 68% of the overall expected world population is going to live in urban areas and cities by the year 2050. The task of transforming modern cities towards a more sustainable and ecological as well as socially likeable environment touches a plethora of disciplines like transportation, energy infrastructure, architecture, building physics, etc. and poses an intricate challenge for architects, engineers, urban planners and social scientist alike. Thanks to the technological evolution, the realization of smart city concepts and solutions has become a viable option to contribute to this goal in a significant manner. The building envelope as an indispensable part of human dwellings and working space has historically mostly taken the classic functionalities of resembling aesthetic expression and providing physical protection. Recent and upcoming technological developments will enable a shift in the role of the building envelope from its mere classical functionalities towards additional contributions to the sustainability and livability of the environment. The prospects of these contributions range from increasing the thermal and visual comfort of the inhabitants and the surrounding environment by adaptive architectural measures towards potential energy saving by energy harvesting devices and synergetic processing and treatment of material flows of the building to provide conditioned air, preprocessed water and even food. In this short essay, we will elaborate on the phenomenon of smart city in general and the role of the building envelope in the context of modern smart city development and its potential on the improvement on different aspects of life and urban environment.
Interests of (In)frequent Bike Users: Analysis of Differing Target Groups’ Needs Concerning the RouteMeSafe Application
Authors: Silberer Jan , Dangel Greta , Bäumer Thomas , Müller Patrick , Kotziabassis Georgios 
Published: October 2022

AbstractCycling is an emission-free and healthy mode of transportation. However, the share of cycling in the modal split is still low. Perceived safety during cycling could be a reason for that. The RouteMeSafe application is developed at Stuttgart University of Applied Sciences with the aim of tackling this issue. A safety routing function is supposed to increase the short-term safety of cycling by showing safe paths for cyclists. Long-term safety is supposed to be increased with the feedback function enabling cyclists to share their evaluation of the cycling infrastructure with the city administration. The safety routing function is currently in the design phase and the feedback function in prototype phase. To develop the application user-friendly, target groups for both functions need to be defined and their expectations considered in the development process. Two studies with infrequent and frequent cyclists have been conducted to do so. Study 1, a user experience study based on a student sample, showed that infrequent cyclists could be a target group for the safety routing function and frequent cyclists could be a target group for the feedback function. The latter was confirmed in study 2, a technology acceptance study based on a sample with frequent cyclists of Stuttgart. Future studies on the application should investigate the long-term technology acceptance of the two groups. This could help to find out whether both groups can serve as target groups on the long run.
Monitoring Tool for Improving Indoor Environment Quality and Performance Based on IoT Sensors: State of the Art and Concept
Authors: Traboulsi Salam , Knauth Stefan 
Published: October 2022

AbstractIndoor temperature is one of the fundamental features of the indoor environment. It can be controlled with distributed IoT sensors, through wireless networks. It affects human indoor environment such as human thermal sensation, productivity at work, buildings’ quality, and several syndrome symptoms. In this study, we focus on the effects of the indoor temperature on the human work productivity and thermal sensation. Our research aims to develop an IoT monitoring tool to manage the challenges in smart buildings by extracting and processing relevant data. It proposes data analysis periodically and integrates newly generated data into the analytical cycle that allows improving human indoor environment.
Box-Type Windows as Means for Better Air Quality and Acoustic Comfort in Urban Areas
Authors: Offtermatt David , Lust Daniel , Erhart Tobias 
Published: October 2022

AbstractControlled natural ventilation in office buildings can ensure the indoor thermal comfort while reducing the life cycle energy consumption for ventilation, compared to mechanical ventilation systems (e.g. HVAC). Natural ventilation is mostly used in moderate climate zones where air conditioning is not a standard. During intermediate seasons, buildings with HVAC systems can additionally use natural ventilation to reduce energy consumption. However, in dense urban areas, natural ventilation can be problematic in terms of acoustic comfort. Here, a box-type window can serve as a compromise between thermal and acoustic comfort. Due to the more complex handling of the box-type window, an automated (electric driven) novel box-type window approach was developed within the imaF project, a part of the iCity initiative. The following article describes the basics of automated natural ventilation, acoustic characterization as well as architectural integration of this window type and the optimization of the airflow through box-type windows. The results show that the proposed geometry can provide sound insulation while providing an appropriate air exchange rate.
Airborne Sound Insulation of Sustainable Building Facades
Authors: Drechsler Andreas , Reinhold Steffi , Ruff Andreas , Schneider Martin , Zeitler Berndt 
Published: October 2022

AbstractTwo trends are currently leading to an increased risk of indoor noise pollution. Firstly, urban densification causes traffic noise sources to be closer to the building facades which makes them louder at the facades. Secondly, airtightness of buildings, due to energy regulations, leads to the need of natural or mechanical ventilation to ensure a “healthy” indoor air quality, thereby allowing noise to easily pass from outdoors to indoors. In the case of mechanical ventilation, an additional noise source is also created. This study investigates the risk reduction of an indoor noise problem by optimizing the facade elements regarding sound insulation. Noise levels of different transportation noise sources (cars, trucks, trains) are used to calculate the resulting indoor noise levels after passing through the facade elements. The amount of noise transmitted into the indoors is dependent on the frequency spectra of the sources and of the sound reduction properties of the facade elements. Facade elements such as masonry walls, open windows, and ventilators are investigated and modified regarding their sound insulation properties. Through passive means, the weighted sound reduction index of an open window and an open ventilator was increased by 12 dB and 3 dB, respectively. Also, the indoor self-noise of the ventilator was investigated and reduced for different airflow rates.
Impact Sound Insulation of Thermally Insulated Balconies
Authors: Heidemann Lucas , Scheck Jochen , Zeitler Berndt 
Published: October 2022

AbstractWith the increasing urban densification, balconies are gaining in popularity as they improve the living quality in homes. From a technical point of view, the thermal insulation between balconies and the building’s façade is state of the art. In Germany, the most popular balcony construction is a reinforced concrete balcony, separated from the building by a thermal insulation element (TIE), which is meant to reduce the thermal energy loss and thus ensure the sustainability of intelligent buildings. The impact sound transmission from balconies, however, is a problem that has not been addressed enough to date. The paper is based on a project of the same name within the iCity research with the main goal of providing acoustic quantities, e.g. an impact sound pressure level difference, for a TIE that can be used to compare the acoustical quality of products and used to predict the impact sound pressure levels within the building using the standard EN ISO 12354-2. Experimental and numerical studies have been carried out on various ceiling-balcony mock-ups without and with TIEs, e.g. by means of experimental modal analysis and validated finite element models, respectively. These studies showed that even doubling the width of the ceiling-balcony mock-up does not change the results significantly, suggesting that the proposed test set-up is suitable for standard testing. The analysis method and results presented here are for only one test set-up with and without a TIE that underwent constructive modifications during the tests. The selected TIE shows an effective sound insulation above 400 Hz and achieves a single-number rated impact sound level difference of $$ \Delta {L}_{\mathrm{w}}^{\ast}\approx 10\ \mathrm{dB} $$
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Artificial Intelligence Supporting Sustainable and Individual Mobility: Development of an Algorithm for Mobility Planning and Choice of Means of Transport
Authors: Heckmann Rebecca , Kock Sören , Gaspers Lutz 
Published: October 2022

AbstractMobility planning is rarely individually tailored. Instead people have to make an active effort to adapt standard solutions to their requirements. Routing apps like Google Maps allow for personalization only by saving important places like home and a workplace but do not allow the user to influence the routing suggestions or choice of mode of transport based on preferences, limitations, or situation. It becomes even more difficult when different means of transport are to interact since most routing applications offer very little multimodal optimization aside from the last mile. Thus, the objective of this article is to present a concept for the utilization of artificial intelligence and regression models in order to enable individual and sustainable mobility planning. To achieve this objective, initially existing routing and mobility planning applications are examined and are conceptually expanded in order to outlay the benefits of personalized route planning. The concrete objective alongside with a method for the development of a new solution is summarized. An algorithm fulfilling these objectives based on multiple linear regression is conceptualized. Relevant factors with coefficient are identified, as well as necessary data sources and interfaces. This algorithm is then implemented in a limited prototype as a proof of concept. Finally, this prototype is tested based on a set of mobility scenarios in order to validate the achievement of the defined objective.
Positioning of Pedelecs for a Pedelec Sharing System with Free-Floating Bikes
Authors: Rawiel Paul 
Published: October 2022

AbstractFor intelligent mobility concepts in growing urban environments, positioning of transportation vehicles and generally moving objects is a fundamental prerequisite. Global Navigation Satellite Systems (GNSS) are commonly used for this purpose, but especially in urban environments under certain conditions, they offer limited accuracy due to buildings, tunnels, etc. that can deviate or mask the satellite signals. The use of existing built-in sensors of the vehicle and the installation of additional sensors can be utilized to describe the movement of the vehicle independently of GNSS. This conforms to the concept of dead reckoning (DR). Both systems (GNSS and DR) can be integrated and prepared to work together since they compensate their respective weaknesses efficiently. In this study, a method to integrate different inertial sensors (gyroscope and accelerometer) and GNSS is investigated. Pedelecs usually do not have many inbuilt additional sensors like it is the case in cars; therefore, additional low-cost sensors have to be used. An extended Kalman filter (EKF) is the base of calculations to perform data integration. Driving tests are realized to check the performance of the integration model. The results show that positioning in situations where GNSS data is not available can be done through dead reckoning for a short period of time. The weak point hereby is the calibration of the accelerometer. Inaccurate accelerometer data cause increasing inaccuracy of the position due to the double integration of the acceleration over time.
Behavioural Development of University Graduates in the Area of Work-Related Mobility: A Study Conducted for the University of Applied Sciences, Stuttgart
Authors: Weißbeck Joschua , Gaspers Lutz 
Published: October 2022

AbstractWork-related mobility currently makes up the biggest share of the total transport volume in passenger transport and is dominated by private motorized vehicles. The paper is based on research about environmentally friendly modes of transportation performed by students on their way to the University of Applied Sciences, Stuttgart, and whether it has an influence on the mobility behaviour of graduates in work and business traffic or not. Another goal was to find out whether or not one’s sustainable mobility behaviour would be maintained throughout the rest of one’s professional life. For this, an online survey was conducted with graduates of the University of Applied Sciences, Stuttgart. The results of the survey confirm a very high sustainability in the field of work-related mobility. Previous studies have only looked at education- and work-related mobility behaviour separately and did not research how or if the former has effects on the latter. The comparison of results from those studies with the information provided by the graduates on their behaviour in occupational mobility also confirms an above-average sustainability.