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P328 - EnviroInfo 2022

https://dl.gi.de/handle/20.500.12116/39388
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Auflistung P328 - EnviroInfo 2022 nach Autor:in "Behrens, Grit"

1 - 10 von 25
  • Konferenzbeitrag
    Analysis and evaluation of mobile apps with regard to resource efficiency and data volumes - Methodologies and tools
    (EnviroInfo 2022, 2022) Obergöker, Kira
    The impact of software on energy and resource consumption is receiving more and more attention. While the examination of desktop software already provides initial sresults and criteria for its evaluation, the consideration of mobile apps is not quite as advanced. This paper is a first step to get an overview of which methods and tools can be used to analyse the resource and data consumption of mobile apps and to evaluate their sustainability. First, I present the previous criteria for desktop software products. In the next step, I present an existing measurement environment for determining the data volume of mobile apps. I created simple environments to identify and test components that can be used to build new measurement environments. I evaluate and compare the measurement environments based on their results. This showed variations between the environments, but an internally equal proportionality. Finally, I used the results obtained to consider how mobile apps can be analysed in terms of their resource consumption, as well as
  • Konferenzbeitrag
    The application of image recognition methods to improve the performance of waste-to-energy plantsplants
    (EnviroInfo 2022, 2022) Schwark, Fenja; Garmatter, Henriette; Davila, Maria; Dawel, Lisa; Pehlken, Alexandra; Cyris, Fabian; Scharf, Roland
    In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.
  • Konferenzbeitrag
    Architecting for Sustainability
    (EnviroInfo 2022, 2022) Lago, Patricia; Greefhorst, Danny; Woods, Eoin
    Sustainability is becoming an increasingly important topic. Information Technology (IT) is an important factor for sustainability; it consumes a substantial, and growing, part of the world supply of energy, but it can also enable significant insights and improvements related to sustainability. These factors need to be taken into account in the design of IT systems, meaning that we need to architect for sustainability. This paper provides insights into the experience and beliefs of IT practitioners and researchers into current and desired practices of architecting for sustainability. It reports on the results of three workshop sessions with practitioners and researchers, providing insight into the state of research and practice.
  • Konferenzbeitrag
    An Artificial Intelligence of Things based Method for Early Detection of Bark Beetle Infested Trees
    (EnviroInfo 2022, 2022) Knebel, Peter; Appold, Christian; Guldner, Achim; Horbach, Marius; Juncker, Yasmin; Müller, Simon; Matheis, Alfons
    Bark beetles, like the European Spruce Bark Beetle (Ips typographus), are inherent partsof a forest ecosystem. However, with favorable conditions, they can multiply quickly and infest vastamounts of trees and cause their extinction. Therefore, it is important for forest officials and rangers ofe. g. a national park, to monitor the population of the beetles and the infested trees. There are severalways to approach this, but they are often costly and time-consuming. Therefore, we design and test abark beetle early warning system with AI-based data analysis: Audio data, data on pheromones andinformation for a drought stress assessment of the affected trees are to be collected and used as a basisfor the analysis. The aim is to devise a micro-controller-based sensor system that detects the infestationof a tree as early as possible and warns the forest officials, e. g. via a message on their cell phone.
  • Konferenzbeitrag
    BITS: A Key Performance Indicators (KPIs) supported approach to assess traffic safety for cyclists at intersections in the Netherlands
    (EnviroInfo 2022, 2022) Schering, Johannes; Gómez, Jorge Marx
    Traffic safety is an important factor in the decision process whether people decide to use the bicycle or not. Critical situations that do not lead to an accident are often not reported to the police. To fill this knowledge gap, several regions as the city of Zwolle and the Province of Friesland (Netherlands) have started to detect near accidents at intersections among vehicles and bicycles by 3D camera data to evaluate traffic safety. Four intersections in Friesland and Zwolle were monitored. Different types of intersections (e.g. shared space concept) were considered. Near accidents can be divided into different conflict categories depending on vehicle speed and time to collision (Post-Encroachment Time PET). The preprocessed data including Key Performance Indicators (KPIs) to make cycling safety at the intersections measurable and comparable are provided. Based on the numbers and visualizations, it will be discussed which of the discussed intersections show critical profiles regarding numbers of near accidents, distribution and amount of very critical situations. With the results the intersections can be adjusted to increase traffic safety.Encroachment Time PET). The pre-processed data including relevant Key Performance Indicators (KPIs) to make cycling safety at the intersections measurable and comparable are provided. Based on the numbers and visualizations, it will be discussed which of the dis-cussed intersections show critical profiles regarding the total numbers of near accidents, its distribution and the amount of very critical situations. Based on the results the intersections can be adjusted to increase the safety situation in a city.
  • Konferenzbeitrag
    Cloud-based Processing of data from Non-Target-Analysis for Tracking Micropollutants in Surface Water
    (EnviroInfo 2022, 2022) Pauw, Viktoria; Hayek Mohamad; Shojaei, Elham; Hachinger, Stephan; Müller, Uwe; Bader, Tobias
    Tens of thousands of chemicals used by consumers, agriculture and industry enter the aquatic environment as micropollutants every day. Using targeted analysis we are so far only able to detect a small subset of the chemicals that are present. Therefore so called non-target screening (NTS) using liquid chromatography in combination with high-resolution mass spectrometry (LCHRMS) is increasingly used by labs to perform more comprehensive monitoring. However, a high degree of variance in measurements and processing workflows results in low comparability of data from separate laboratories. On one hand this is caused by differences in processing techniques which are due to stationary laboratory equipment and on the other hand by differing priorities in the detection strategy and evaluation workflow. The K2I project funded by BMBF aims at fostering collaboration between laboratories by providing a joint platform for uploading and processing LCHRMS data. A cloud based datalake and processing pipeline is being developed. A standardized processing workflow can then be executed which is enhanced by data mining tools including machine learning techniques. An indexing and searching software is employed to create a web based access to the processed data for participants.
  • Konferenzbeitrag
    Conception and test of a measuring station for the analysisof the resource and energy consumption of material floworiented environmental management information systems (EMIS)
    (EnviroInfo 2022, 2022) Junger, Dennis; Wohlgemuth, Volker; Kammer, Eike
    The aim of this work is to design a measurement setting that enables the analysis of the resource and energy consumption of material flow oriented corporate environmental information systems (BUIS). For this purpose, the focus is put on the Life Cycle Assessment (LCA) software. LCA software supports LCA mainly in Life Cycle Inventory (LCI) and in Life Cycle Impact Analysis (LCIA). For the impact assessments, through which potential impacts on the environment are calculated, the LCA software requires many substance-specific life cycle impact data sets, which are stored in databases. In this work, we mainly refer to LCA software that runs in the form of desktop applications. In order to create a measurement configuration suitable for LCA software, the software to be tested and the necessary methodology for desktop solutions are searched. The found solution for sustainable evaluation of software products is adapted to the goal of comparing the efficiency LCA software. The determined measurement standard will be applied, modified and extended. The measurement configuration will be built and tested. Problems of a theoretical nature and problems in setting up the tests are addressed. Any problems of the comparability basis that may arise when performing tests on the selected LCA in the software in the future will be addressed, and a possible solution path will be shown. An outlook on the further course of the measurements is given.
  • Konferenzbeitrag
    Detection of snow-coverage on PV-modules with images based on CNN-techniques
    (EnviroInfo 2022, 2022) Hepp, Dennis; Hempelmann, Sebastian; Behrens, Grit; Friedrich, Werner
    The transition from fossil fuels to renewable energy is considered as very meaningful to mitigate climate change. To integrate weather-dependent energies firmly into the power grid, a forecast of the energy yield is very important. This paper is about renewable energy generation by photovoltaic (PV) systems. The yield of PV-systems depends not only on weather conditions, but in wintertime also on the additional factor “snow cover”. The aim of this work is to detect snow cover on photovoltaic plants to support the energy yield forecast. For this purpose, images of a PV-plant with and without snow cover are used for feature extraction and then analyzed by using a convolutional neural network (CNN).
  • Konferenzbeitrag
    Development of a framework for decision support in the context of climate adaptation
    (EnviroInfo 2022, 2022) Wetzel, Simeon; Mäs, Stephan
    Implementing effective adaptation data that enable this knowledge transfer. For this purpose, this article presents a framework that shall simplify the development of these tools and the measures to climate change impacts concerns policymakers worldwide. At the local scale, there is a gap between scientific findings and a translation of these into concrete measures. It requires a network of tools and access to climate data. The underlying data management concept is intended to provide an infrastructure that requires only a few interventions in the operating process for both data suppliers and system administrators. Most of the infrastructure components have already been realised in the context of the ongoing research project KlimaKonform. In addition, there is an outlook on future implementations.
  • Konferenzbeitrag
    Digital Mobility Services for Communities: Flexible boarding points for campus ridesharing
    (EnviroInfo 2022, 2022) Gieza, Moritz; Schuster, Thomas; Waidelich, Lukas; Kölmel, Bernhard
    Mobility is still characterized by individual transport. Despite changes in recent years, it still influences infrastructure development and results in car-friendly cities. As a result, traffic congestion reveals weaknesses in efficiency and sustainability of this model. This is exacerbated in metropolitan areas with high growth rates and in areas with below-average public transport services. Besides congestion, emission such as pollution and noise are a major problem. In this article, we give explain how this affects communities in general and transport from and to our university campus particularly. We will examine how digital mobility services can extend public and individual transport. We will explore how digital services can promote intermodal transport and lead to more sustainability in mobility. Within that discussion, we present a ridesharing platform and study its influence on directions to and from our campus.