An Approach to Describe Design Pattern Structures for Sustainable Software Products
Software affects society and environment in a variety of ways. In addition to the energy and resource requirements driven by software products, social factors are to be mentioned as sustainability-relevant aspects. In order to support software developers in creating products that can be positively assessed from a sustainability point of view, the question of practically usable assistance arises in this context. With this aim, in this paper the methodological approach of design patterns is examined. It is discussed how sustainability patterns can be described in a structured way and how they can be incorporated into practical software engineering processes. Particular attention is paid to aspects of completeness and consistency of the descriptions as well as the explicit inclusion of human action. It is recommended to provide pattern descriptions with a high formalization degree in order to enable verifiability for logical plausibility and completeness and to allow further machine-assisted processing. Prospectively appropriate pattern repositories could be set up to support practical software product development processes in the future.
A Literature Review to analyze the State of the Art of Virtual Power Plants in Context of Information Security
Compared to conventional power plants, Virtual Power Plant is a new electrotechnical and information technology concept that is used for the interdisciplinary merging of electrical engineering and information technology for the central control and monitoring of decentralized renewable energy systems and components. A formal presentation of definitions and consensus building is seen as an instrument to specify the practice-oriented design of Virtual Power Plants. The present paper focuses on the Virtual Power Plants as key factor for sustainable energy - especially in its common understanding of terms. This compilation serves as a mutual knowledge base and function because of the “Shared Conceptualization” for the specialist user within the knowledge domain “Information technology” and “Electrical engineering.” An Event-driven Process Chain is created for this purpose. In order to obtain such an Event-driven Process Chain, a qualitative analysis based on semi – systematic literature review led to a selection of suitable term definitions that are contained in the scientific databases. This investigation finally leads to the compilation of entities and their mutual relations, which are required to create the model. The conception of an Event-driven Process Chain is seen in this context as a contribution to the specification and structuring of the discussion about Virtual Power Plants. A potential contribution is, the ability to map a field of research, synthesize the state of knowledge, and create an agenda for further research in context of information systems and information security research.
Microservicebased Architecture for the Integration of Data Backends and Dashboard Applications in the Energy and Environment Domains
This article presents a software architecture based on the onion architecture that uses the concept of application microservices inorder to integrate data backends with dashboard applications. Its main goal is to reduce the complexity in the architecture’s frontend and therefore to increase the performance of the application for the user. The concept of the added application layer as well as its interaction with the other parts of the architecture is described in detail. Then an evaluation of its advantages is presented which shows the benefits of the conceptregarding performance and simplicity using a real-world use case in theenergy and environmental domains.
Rebound Effects in Methods of Artificial Intelligence
Artificial intelligence (AI) is one of the pioneering driving forces of the digital revolution in terms of the areas of application that already exist and those that are emerging as potential. On the technical side, this paper deals in particular with the energy requirements of artificial intelligence processes. It also identifies efficiency approaches in this sector. Increases in productivity often lead to an increased demand for energy, which is contrary to sustainability in terms of reducing CO2 emissions. Therefore, it will be examined to what extent rebound effects can reduce the savings potential for energy in relation to methods of artificial intelligence and what the main factors of CO2 emissions are.
Chair: Hans-Knud Arndt
Towards an automated classification of Hess & Brezowsky’s atmospheric circulation patterns Tief and Trog Mitteleuropa using Deep Learning Methods
Climate Change alters the atmospheric circulation over Europe and increases the risk of heavy precipitation. 'Tief Mitteleuropa' and 'Trog Mitteleuropa' are two atmospheric circulation patterns that are associated with heavy precipitation over Central Europe. Thus the research question of how climate change influences their occurrence is of high relevance. However, the spatio-temporal data structure and the imbalanced classes demand for sophisticated modelling architectures in order to detect these circulation patterns in climate models. This paper introduces and compares deep learning algorithms that are able to tackle the problem of detecting the two atmospheric circulation classes. A ResNet18 and a Convolutional LSTM are set up and fitted to the data. The best model achieves a Matthews correlation coefficient of 0.33. Overall, both model types are generally able to detect the atmospheric circulation patterns and, moreover, carry immense potential in the way they can be set up and fitted to the data. These promising results open the gate for further research in the future.
Resilient Smart Farming (RSF) as an opportunity for sustainable, environmentally friendly and resilient digital agriculture
Since the COVID-19 pandemic, the word “resilience” is more common than ever. However, resilience can be found in many other sectors. This present work revolves around Resilient Smart Farming (RSF) as a possibility for sustainable, environmentally friendly, and resilient digital agriculture. The main focus is on the reliability and security against attacks of agricultural systems as a central component of the Critical Infrastructure Protection (KRITIS) of food. The question is not whether smart farming makes sense in agricultural practices, but whether its infrastructure meets the requirements of a fail-safe (resilient) infrastructure.
Initial results from the project GeoBox show that edge computing offers the possibility of realizing RSF. Edge computing is structured in such a way that it also functions decentrally for the end users, so that the dependency on the internet infrastructure is reduced, in comparison to other solutions. By setting up decentralized edge data centers for regional IoT sensor networks, a digital ecosystem for regional and resilient networking of smart farming is supported. Resilient Edge Computing (REC) focuses on the resilience and reliability of agricultural production, a requirement reinforced by the Agricultural Ministers' Conference. The GeoBox-Infrastructure (GBI) serves as a foundation and can be extended by features of resilient edge computing. With the open source software "Open Horizon", managed by the Linux Foundation, the GBI has an edge framework at its disposal that enables the automation of software installation and data synchronization on thousands of edge devices (e.B miniservers – also called “HofBoxes”).
Resource and Energy Efficiency Analysis in Bottle-to-Bottle Recycling Plant – Case Study
This research presents a practical approach towards resources and energy efficiency in production systems in small and medium enterprises (SMEs). The approach is based on mapping the production line using the simulation tool UMBERTO® Efficiency+ for the representation of the material and energy flows. A case study from a bottle-to-bottle recycling plant is selected. Material flow bottle-necks are spotted and energy hotspots are identified. Optimization is implemented in the model and the new values for savings in material, energy and carbon emissions are calculated. The simulated optimized model estimates yearly savings by around 8% in materials and 10% in electricity consumption and consequently in costs and CO2 emissions. The simulation tool UMBERTO Efficiency+ facilitated the simple and time efficient assessment of the production sustainability as well as the prediction of the expected savings upon implementation of the modifications which is a practical and convenient approach for the industrial field.
Vision Open Data Farm - Opportunities and Possibilities in Precision Farming
In order to utilize the full potential of smart/precision farming and sustainable agricultural practices, which lie at the heart of the EU Sustainable Development Goals, the transition from (prevalent) analog to digital methods requires supportive platforms. The German Federal Ministry of Food and Agriculture has created 14 “digital trial fields” to showcase how this transition can be reinforced, guiding the implementation and acceptance of innovative digital practices among German farmers (https://www.bmel.de/EN/topics/digitalisation/digital-trial-fields.html).
A major focus of the digital trial field “EF-Südwest” is implementing digital practices across various agricultural production areas by creating a standardized data management platform (living lab) that can be used to demonstrate, educate, and coach. This digital platform is based on data collected from various digital agricultural practices on the Hofgut Neumühle, a teaching and research institute for animal husbandry in Rhineland-Palatinate, Germany. The pilot project is to visually depict the Hofgut Neumühle as a 3D-Model, as well as visualize the data flow surrounding their daily work. This work will be performed in cooperation with additional digital trial fields as well as research groups in Rhineland-Palatinate.
The first step in implementing digital practices is displaying the value and benefits from data as well as how to integrate them seamlessly into daily operations. A main goal of the living lab Open Data Farm is demonstrating how to do this using data collected on the Hofgut Neumühle. In addition, educational material explaining the value of the data as it relates to daily agricultural operations is provided. The overall goal is developing an interactive educational platform that can integrate existing resilient smart farming infrastructures such as the GeoBox-Infrastructure, as well as serves as test platform for new, innovative ideas.
Charging heuristics of electric automated guided vehicles (e-AGVs) in the last-mile delivery
Substituting fuel-based and manual delivery for the last miles with electric automated guided vehicles (e-AGVs) promises to substantially reduce CO2 and noise emissions, and traffic congestion in urban areas. As they are battery-based vehicles, charging of these vehicles needs to be adjusted into their operation planning, in particular, that their batteries are too small for a full day of operations. However, when, where, and how many parcels should be transported is uncertain and so is the energy demand of e-AGVs. To avoid computationally expensive calculation of online optimization, we develop three recharging heuristics to ensure the energy supply for e-AGVs dealing with demand uncertainties. We propose a simulation framework that enables a grid search for the best combination of heuristics’ parameters (charging goal, state of charge, lower limit, etc.). The simulation is applied on a real-world data set to test and evaluate charging strategies regarding different key performance indicators (KPIs). Our work provides a systemic multicriteria comparison of charging heuristics for decision-makers planning to employ e-AGVs in the last-mile delivery.
Chair: Klaus Greve
Site Specific Climatic Smart Farming as an important part of Resilient Smart Farming (RSF)
The current situation in Germany as well as in other countries after natural disasters have occurred, reinforces the relevance of resilient and climatic smart farming as a crucial practice to conserve our environment.
The ongoing research project Smart Soil Information for Farmers (SoFI) delivers such geo-data based information services. Through the use of weather data from agrometeorological stations and soil information relating to field capacity and layer thickness, the potential soil moisture is modelled. This is currently being performed at an hourly rate for all agricultural sites and polygons of available soil data throughout Rhineland- Palatinate and Bavaria. The modelling results are classified into different categories, from very dry to very moist. These can then be transfomed into groups which describe the trafficability of the soil, resulting in the avoidance of soil damage through compaction. To derive the susceptibility of soils to compaction and conversely derive trafficability, several approaches have been published. Additionally, microclimate data, recorded specifically for each plot by local sensors, can be used to extend weather forecasting systems, allowing measures to be implemented with greater temporal and spatial precision. Based on LoraWAN enabled communication structures, the sensor data can be easily managed and published, i.e. using the Things Network. Building up such a resilient local network supports the implementation of resilient smart farming (RSF). The so-called GeoBox-Infrastructure (GBI) connects these innovative technologies. The GBI focuses on resilient and decentral data management. Therefore, it is crucial to reduce the strong dependency of operational data from central servers.
The combination of this location-based service and state-wide modelling in the GBI enables, for the first time, the derivation of real-time spatiotemporally high-resolution maps as a service for farmers.
An Automated, Non-Invasive Approach to Determine Bee Pollen Diversity Based on Flora Data
Bees collect pollen from a variety of plant species. This pollen diversity is both an indicator of biodiversity and a balanced diet for bees which has a positive effect on their health. Traditionally, pollen diversity is determined by invasively and manually collecting and analysing the pollen. In this paper, we present a heuristic for assessing the pollen diversity around a hive using data on flora. This data-driven approach is both efficient and non-invasive. We evaluated our approach against the results of a microscope analysis, showing that it delivers useable results, despite the lack of flora data in some places. As a next step, we will incorporate data from our AI-based video monitoring system of hives to match plants based on pollen colours that were detected in the images.
Integrating data on petroplastics to inform new plastics and promote recycling and upcycling
Global production of petroleum-based plastics has topped billions of metric tons and continues to grow. Only a small fraction is recycled or upcycled at the end of a product’s life, with most used plastics being landfilled, incinerated, or released to the environment as litter. Designed to be durable throughout their useful life, these conventional plastics likewise persist in the environment. For this reason, extensive efforts are under way to stem the environmental accumulation of waste plastics and associated fate products (notably microplastics and nanoplastics) by increasing reuse, recycling, and upcycling. A relational database has been outlined to incorporate linkages among polymer properties, suitability considerations for recycling and upcycling, and biodegradation standards relevant to used plastics that are landfilled or littered. Because literature data vary substantially, including for basic physicochemical and thermomechanical properties, meta data are particularly important in organizing the database to reveal opportunities for advancing the circular economy, with particular attention to recycling. Factors that influence reported data include instrumentation and analytical techniques as well as ambient conditions, such as relative humidity. Of further interest is how field data align with those from laboratory tests designed to mimic environmental conditions, to consider whether standard testing methods might be modified to better represent more real-world conditions. This presentation highlights how polymer properties and other data can be integrated to inform opportunities for improved recycling, including increasing the number of cycles and evaluating the role of bioplastics. The current database has more than 400 data fields spanning characteristics from molecular weight to environmental degradation for a number of conventional polymers, while limited data have been found for biopolymers – primarily polyethylene and polyethylene terephthalate. The overall aim is to integrate data that can better inform the development of bioplastics that are more biofriendly, toward reducing the environmental impacts of future plastics.
Chair: Jochen Wittmann
Human Behavior Model in Public Pedestrian-only Space Estimated using High-precision Trajectory Data
A human behavior model describing the actions of pedestrians in public pedestrian-only space was constructed on the basis of high-precision trajectory data gathered using a laser scanner sensor system. First, a route selection model that could be used to describe macroscopic trajectories was construct-ed. Next, a walking model that includes the psychological stress imposed by the presence of walls, columns, and other hindrances to motion. These models were then combined to create the human behavior model. Next, using laser scanner sensors, highly precise measurements were taken of the trajecto-ries of pedestrians in the reception area of a hospital. The observational data were employed to estimate unknown parameters in the human behavior model, and to note the characteristics (sex, patient or staff, mobility aid us-age) of the pedestrians as they varied with pedestrian attributes. Finally, we proposed a procedure for evaluating the comfort and efficiency of public pedestrian-only space. Using simulation analysis, we demonstrated that it is possible to uniquely estimate the spatial distribution of comfort and efficiency at any given location from the frequency of passages at that location.
A Taxonomy about Information Systems Complexity and Sustainability
With the increasing digitalization of all industry sectors, information systems are becoming more and more complex. At the same time, also thanks to their crucial societal role, they have the potential to help (or hinder) organizations in their ambition to contribute to sustainability goals. In our work, we aim at helping them by making explicit the important concerns that shape their information systems and that are found to influence complexity in some sustainability aspects. To this aim, we perform a study in a large bank, and build a taxonomy of concerns that emerge from real projects and experience, and blend both complexity and sustainability.
Approaches to assessing the vulnerability of large city population to natural and man-made hazards using mobile operators data (case study of Moscow, Russia)
The complex nature of threats to large cities residents requires a rethinking of the existing methods for the vulnerability assessment of the population to various kinds of them. Moscow concentrates about 9% of the Russian population, and with the Moscow oblast - about 12%. The high level of spatial concentration of the population and its active dynamics determine the increased level of natural and man-made risk in the city. The purpose of this study is to assess the vulnerability of the Moscow population to natural and man-made hazards, taking into account the actual population size and its movement in the city within different time cycles (daily and weekly-seasonal). Trying to find an appropriate solution, authors used alternative sources of statistical information – mobile operators data. The use of these data made it possible to obtain more detailed information on the state of socio-geographical systems, to overcome barriers associated with the incompleteness and ‘static’ nature of official statistical information (data provided by Rosstat). Mobile operators data allow obtaining more reliable depictions of the localization of its users at a certain point in time, which made it possible to adjust and clarify the current ideas about the distribution of the population in Moscow. As a result of the study, it was shown that for the center of Moscow and for New Moscow, the population vulnerability level is much higher than reflected in official documents. On the contrary, in the peripheral areas of Old Moscow, the potential risks are reduced because the real population density is significantly lower than it is estimated in the calculations provided by Rosstat.
Chair: Stefan Naumann
Avoiding Obsolescence – Taking Usability into Account: The Augmented Reality Glasses Example
In the context of this work, it was examined whether the integration of AR glasses in industrial processes is a useful tool to avoid obsolescence. AR is already being used in various areas such as medicine, maintenance and repair, and many other areas. For this purpose, three different models of AR glasses were then tested. When selecting the AR glasses, care was taken to cover as wide a range of properties as possible. For this reason, both lightweight AR glasses and heavier AR glasses were selected, which also differed in terms of performance. In the interest of sustainable use of this in-formation and communication technology, success criteria were defined for the trial, on the basis of which success or failure could be determined after the trial. The three AR glasses were each tested by 10 subjects, all of whom were experienced employees in an industrial environment.
Multi-model Simulation for Serious Games in Sustainability Research
One of the aims of serious role-playing games (SRPG) is to educate people by simulating the impact of their actions in various domains. Climate change is one of these domains. Such SRPGs are usually based on complex simulations of heterogeneous models. However, interfacing a SRPG with heterogeneous simulations is currently a manual and fault-prone process that requires both domain-specific and technical knowledge. This research proposes a conceptual framework that supports game designers in interfacing their SRPGs with pre-existing or custom-tailored simulation models. In addition, a first implementation of such an interface is presented that further facilitates the creation, configuration and execution of such games.
Chair: Volker Wohlgemuth
Shareable Goods and Impacts on Consumption; The Case of the Digital Sharing Economy
Digital platforms promote the shared consumption of a variety of material and immaterial goods. As they grow and appeal to more consumers, the new practices and patterns of sharing can have both desirable and undesirable impacts from a sustainability point of view. The present paper takes a closer look at the various impacts of shared consumption practiced in the digital sharing economy (DSE) with the aim to propose a guideline for assessing the DSE’s sustainability impacts. The guideline builds on a typology of shareable goods and a classification of different positive and negative environmental impacts of sharing. By considering different consumption scenarios (based on consumers’ behavioral responses, where applicable), the study develops a conceptual framework for the DSE’s impacts on the environment. This is also an extension of the general impact categories of Information and Communication Technology (ICT) which already exist in the literature. In addition to the impact of consumption, the concepts of the “impact of provision,” “impact of access,” and “impact of maintenance” are introduced as the four main evaluations comprising the sustainability assessment of sharing platforms. The considerations addressed can be helpful in delineating further evaluations of the sustainability of various instances of digital sharing systems.
A review on Key Performance Indicators for Climate Change
Climate change is one of the biggest threats to humanity in the near future. Almost all different scenarios of climate change involve large-scale disasters and hazards. In order to define goals to cities, regions and countries in regards to mitigating climatic change, we first need to understand which the important key performance indicators (KPIs) are, how they can be measured and which values they take. Then, each country can calculate its performance based on these KPIs, setting realistic goals for better performance in the near future. This paper performs a large survey to identify and list 64 relevant KPIs, together with suggested
Developing an Architectural Design for an Environmental Management Information System (EMIS)
Due to climate change and the pressing ecological crisis, companies face the urge to transform their operations in a sustainable way. In this context, environmental management information systems (EMIS) can support companies by systematically collecting, processing, and providing environmentally relevant data and information. Although various approaches for EMIS have been developed, no EMIS is able to address all requirements regarding environmental management accounting yet. Thus, this paper aims to develop an architectural design for EMIS and to create a theoretical basis for further practical analysis and developments. Therefore, this paper identifies and evaluates existing architectures. Subsequently, an architectural design is developed based on a layered architecture and the architecture patterns of service-oriented architecture, data warehouse, business intelligence, and workflow management system. The architectural design can be used as a basic structure for the implementation of EMIS.
Chair: Stefan Naumann