8,478 research outputs found

    Challenges in the Design and Implementation of IoT Testbeds in Smart-Cities : A Systematic Review

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    Advancements in wireless communication and the increased accessibility to low-cost sensing and data processing IoT technologies have increased the research and development of urban monitoring systems. Most smart city research projects rely on deploying proprietary IoT testbeds for indoor and outdoor data collection. Such testbeds typically rely on a three-tier architecture composed of the Endpoint, the Edge, and the Cloud. Managing the system's operation whilst considering the security and privacy challenges that emerge, such as data privacy controls, network security, and security updates on the devices, is challenging. This work presents a systematic study of the challenges of developing, deploying and managing urban monitoring testbeds, as experienced in a series of urban monitoring research projects, followed by an analysis of the relevant literature. By identifying the challenges in the various projects and organising them under the V-model development lifecycle levels, we provide a reference guide for future projects. Understanding the challenges early on will facilitate current and future smart-cities IoT research projects to reduce implementation time and deliver secure and resilient testbeds

    Exploring acceptance of autonomous vehicle policies using KeyBERT and SNA: Targeting engineering students

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    This study aims to explore user acceptance of Autonomous Vehicle (AV) policies with improved text-mining methods. Recently, South Korean policymakers have viewed Autonomous Driving Car (ADC) and Autonomous Driving Robot (ADR) as next-generation means of transportation that will reduce the cost of transporting passengers and goods. They support the construction of V2I and V2V communication infrastructures for ADC and recognize that ADR is equivalent to pedestrians to promote its deployment into sidewalks. To fill the gap where end-user acceptance of these policies is not well considered, this study applied two text-mining methods to the comments of graduate students in the fields of Industrial, Mechanical, and Electronics-Electrical-Computer. One is the Co-occurrence Network Analysis (CNA) based on TF-IWF and Dice coefficient, and the other is the Contextual Semantic Network Analysis (C-SNA) based on both KeyBERT, which extracts keywords that contextually represent the comments, and double cosine similarity. The reason for comparing these approaches is to balance interest not only in the implications for the AV policies but also in the need to apply quality text mining to this research domain. Significantly, the limitation of frequency-based text mining, which does not reflect textual context, and the trade-off of adjusting thresholds in Semantic Network Analysis (SNA) were considered. As the results of comparing the two approaches, the C-SNA provided the information necessary to understand users' voices using fewer nodes and features than the CNA. The users who pre-emptively understood the AV policies based on their engineering literacy and the given texts revealed potential risks of the AV accident policies. This study adds suggestions to manage these risks to support the successful deployment of AVs on public roads.Comment: 29 pages with 11 figure

    Resilience and food security in a food systems context

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    This open access book compiles a series of chapters written by internationally recognized experts known for their in-depth but critical views on questions of resilience and food security. The book assesses rigorously and critically the contribution of the concept of resilience in advancing our understanding and ability to design and implement development interventions in relation to food security and humanitarian crises. For this, the book departs from the narrow beaten tracks of agriculture and trade, which have influenced the mainstream debate on food security for nearly 60 years, and adopts instead a wider, more holistic perspective, framed around food systems. The foundation for this new approach is the recognition that in the current post-globalization era, the food and nutritional security of the world’s population no longer depends just on the performance of agriculture and policies on trade, but rather on the capacity of the entire (food) system to produce, process, transport and distribute safe, affordable and nutritious food for all, in ways that remain environmentally sustainable. In that context, adopting a food system perspective provides a more appropriate frame as it incites to broaden the conventional thinking and to acknowledge the systemic nature of the different processes and actors involved. This book is written for a large audience, from academics to policymakers, students to practitioners

    Impact of plant growth promoting rhizobacteria (PGPR) on stress resistance of winter wheat (Triticum aestivum L.)

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    Wheat is one of the worldwide most cultivated crop and highly contribute to secure food production in different world regions. Although, it grows almost ubiquitous, its production is severely vulnerable to drought. Soil and rhizosphere microbial communities associated to plants come more and more into the focus of modern agrobiology research, as a solution to maintain productivity under drought, and reinforce sustainable production. Whereas numerous studies on wheat production and the beneficial influence of the soil microbiome under drought have been performed in arid and semiarid regions of the world, comparable studies in Central Europe are rare. This might change due to the ongoing climate crisis and expected less frequent precipitations during the vegetation season. So far, most studies that focus on acclimatization of the wheat rhizobiome to water deficit mostly consider, at best, two interacting factors, and lack to consider other biotic or abiotic drivers of rhizosphere microbial communities structure and function. Therefore, the aim of this thesis was to combine complementary analytical approaches to investigate drought-induced structural and functional changes in wheat rhizosphere bacterial communities and individual species in dependency of soil type, farming system, wheat cultivar and plant development stage, and to determine how these changes affect wheat performance as a consequence of possible climate change scenarios in Central Germany. The presented thesis starts with a general introduction and presentation of the project, followed by three consecutive chapters containing the main findings published in peer-reviewed articles. Starting with an experiment performed in the greenhouse (Chapter 1) and then moving to a realistic climate scenario under field conditions (Chapter 2 and 3), the three chapters demonstrate the sole and interacting effects of drought and farming system (Chapter 1-3), soil type and wheat cultivar (Chapter 1), as well as plant growth stages (Chapter 2 and 3) on bacterial communities and individual taxa of the wheat rhizobiome. The methods used reach from traditional cultivation and in-vitro bioassays (Chapter 3), over extracellular enzyme activity potentials (Chapter 1 and 2) to more advanced technologies such as metabarcoding (Chapter 1 and 2) and computational tools (Chapter 1 and 2), addressing single bacterial taxa as well as community level. Finalizing the thesis, a concluding synopsis compiles and critically reviews the gained results and formulates future study perspectives. In Chapter 1, we evaluated the impact of soil type (loamy vs. sandy), farming management (conventional vs. organic), wheat cultivar (non-demanding vs. demanding), and the interacting effects of these factors on wheat rhizobacterial community composition and function under extreme drought conditions. Water deficit exerted a strong pressure on rhizobacterial communities, and interacted with soil type and farming management, but not with the wheat cultivar types. In the sandy soil, we observed a strong drought-induced shift in community composition, with a decrease in species diversity and extracellulare enzyme production, while changes by drought were less prominent in the fertile loamy soil. A particular exception from this pattern was found for enzyme activities involved in carbon cycling in the sandy soil suggesting a positive plant-soil-feedback on enzyme activities by drought conditioning. In Chapter 2, two individual, but interrelated aims were pursued. First, we used the platform of the Global Change Experimental Facility (GCEF) to explore the impact of two farming practices (conventional vs. organic) and two climate treatments (ambient vs. future) on bacterial community composition and activity profiles of extracellulare enzymes involved in C,N and P cycles in the wheat rhizosphere at two different plant growth stages. The climate treatment in the GCEF had no effect on the rhizobacterial communities. Rhizobacterial community composition and functions significantly differed between vegetative and mature growth stages of the plants, in both conventional and organic farming. In a second step, we reused the data to explore further the accuracy of computational approaches, like Tax4Fun and PanFP, to predict functional profiles of bacterial communities based on 16S rDNA abundance data. To this end, we compared the measured enzyme activities with respective gene abundances in the community under different climate and farming treatments, and at the two plant development stages. This analysis revealed qualitative, but not necessarily quantitative concordances, i.e. we found effects of the different treatments on the measured enzyme activities reflected in the gene abundances. Chapter 3 is a complementary approach to Chapter 2 with a focus on individual bacterial species level. Culture-dependent methods were used to specifically isolate strong P-solubilizing bacteria from the rhizosphere of wheat, which were tested for their in-vitro drought tolerance. Among the more than 800 isolated species, Phyllobacterium, Pseudomonas and Streptomyces species dominated. While farming management and climate treatment had only minor effects on composition and functions of the isolates, the wheat growth stages had an impact, whereby a dominance of Pseudomonas species at the vegetative growth phase was replaced by dominance of Phyllobacterium species at the mature growth phase. Since P-solubilizing potential was paralleled by a high in vitro drought tolerance, Phyllobacterium species were characterized as promising plant growth promoting rhizobacteria (PGPR) of wheat under future drought conditions. In the synopsis part, we evaluated the multifactorial and multidisciplinary approaches and investigated to what extent the adaptations of bacterial communities in field and pot experiments coincided or differed. Overall, we found common and distinct adaptation processes of bacterial communities and individual species in the rhizosphere of wheat to drought, whereby single factors, but also interacting effects exerted a strong impact on these processes. This study underlines the importance of multifactorial approaches to reveal community- or species-specific plant-soil-feedbacks.:Contents 3 Preface 5 Bibliographic description 6 Zusammenfassung 9 Summary 13 Introduction 16 When extreme events become the new normal 17 Feedback to agricultural production and need for management adaptation 20 Difficulties in exploring the soil microbiome and identification of plant beneficial microbial taxa 22 Our approach with wheat 24 Bibliography 27 ֎ Chapter 1 31 Interactions Between Soil Properties, Agricultural Management and Cultivar Type Drive Structural and Functional Adaptations of the Wheat Rhizosphere Microbiome To Drought 31 Supplemental Tables 51 Supplemental Figures 55 ╬ Chapter 2 59 Can We Estimate Functionality of Soil Microbial Communities from Structure-Derived Predictions? A Reality Test in Agricultural Soils 59 Supplementary Tables 79 Supplemental Figures 84 Supplemental Material 1: 87 Variation in edaphic parameters according to experimental factors 87 Supplemental Material 2 88 Effect of abiotic soil parameters on bacterial community structure and function 88 Supplemental Material 3 90 Indicator species analysis 90 ۝ Chapter 3 95 Shifts Between and Among Populations of Wheat Rhizosphere Pseudomonas, Streptomyces and Phyllobacterium Suggest Consistent Phosphate Mobilization at Different Wheat Growth Stages Under Abiotic Stress 95 Supplementary Figures 112 Supplementary Tables 117 Synopsis 152 Multidisciplinary approaches combine advantages of cultivation-based and high throughput community-based methods 155 Multifactorial approaches to gain a more holistic understanding of plant-microbe interactions in pot experiments 157 Transferability of findings gained in the pot experiment to field conditions 159 Towards a wheat core microbiome? 161 Study limitations and outlook 163 Bibliography 164 Acknowledgements 169 Curriculum Vitae 171 Personal details 171 Education 171 Work experience 172 Research and Mentoring experience 172 Extracurricular activities 173 List of publications and Presentations 174 Publications in peer-reviewed journals: 174 Oral Presentations: 175 Poster Presentations: 175 Statutory declaration 176 Eidesstattliche ErklĂ€rung 177 Author contributions 178Weizen ist eine der weltweit am hĂ€ufigsten angebauten Kulturpflanzen und trĂ€gt zur Sicherung der Nahrungsmittelproduktion in verschiedenen Regionen der Welt bei. Obwohl er fast ĂŒberall angebaut werden kann, ist die Produktion durch Trockenheit limitiert. Daher rĂŒcken mehr und mehr die mikrobiellen Gemeinschaften im Boden und in der RhizosphĂ€re in den Mittelpunkt der modernen agrarbiologischen Forschung, um die ProduktivitĂ€t bei Trockenheit aufrechtzuerhalten und eine nachhaltige Produktion zu fördern. WĂ€hrend bereits zahlreiche Studien ĂŒber die Weizenproduktion und den positiven Einfluss des Bodenmikrobioms in ariden und semiariden Regionen der Welt durchgefĂŒhrt wurden, sind vergleichbare Studien in Mitteleuropa selten. Dies könnte sich aufgrund der anhaltenden Klimakrise und der zu erwartenden ausbleibenden SommerniederschlĂ€ge Ă€ndern. Dabei haben die meisten Studien, die sich mit der Akklimatisierung des Weizenrhizobioms an Wasserdefizite befasst haben, bestenfalls den Einfluss von Trockenheit und ein oder zwei weiteren biotischen oder abiotischen Einflussfaktoren, die zudem miteinander interagieren können, auf die Struktur und Funktion der mikrobiellen Gemeinschaften in der RhizosphĂ€re untersucht. Ziel dieser Arbeit war es daher, verschiedene komplementĂ€re Analysemethoden zu kombinieren, um trockenheitsbedingte strukturelle und funktionelle VerĂ€nderungen in den bakteriellen Gemeinschaften und auch einzelner Arten in der WeizenrhizosphĂ€re, in AbhĂ€ngigkeit von Bodentyp, Landnutzungssystem, Weizensorte und Pflanzenentwicklungsstadium zu untersuchen, und zu ermitteln, wie sich diese VerĂ€nderungen auf die ProduktivitĂ€t des Weizens als Folge möglicher Szenarien des Klimawandels in Mitteldeutschland auswirken. Die vorliegende Arbeit leitet mit einer allgemeinen EinfĂŒhrung und Vorstellung des Projekts ein, gefolgt von drei aufeinanderfolgenden Kapiteln, die die wichtigsten Ergebnisse enthalten, die in von Fachleuten begutachteten Artikeln veröffentlicht wurden. Beginnend mit einem Experiment im GewĂ€chshaus (Kapitel 1) und weiterfĂŒhrend zu einem realistischen Klimaszenario unter Feldbedingungen (Kapitel 2 und 3), beschreiben die drei Kapitel die alleinigen und interagierenden Auswirkungen von Trockenheit und Anbausystem (Kapitel 1-3), Bodentyp und Weizensorte (Kapitel 1), sowie Pflanzenwachstumsstadien (Kapitel 2 und 3) auf Bakteriengemeinschaften und einzelne Taxa des Weizenrhizobioms. Die verwendeten Methoden reichen dabei von der traditionellen Kultivierung und In-vitro-Bioassays (Kapitel 3), ĂŒber extrazellulĂ€re EnzymaktivitĂ€tspotenziale (Kapitel 1 und 2), bis hin zu fortschrittlicheren Technologien, wie Metabarcoding (Kapitel 1 und 2) und computergestĂŒtzten Vorhersagen (Kapitel 1 und 2). Zum Abschluss der Arbeit werden in einer abschließenden Synopsis die gewonnenen Ergebnisse zusammengetragen und kritisch betrachtet, sowie Ideen fĂŒr zukĂŒnftige Studien formuliert. In Kapitel 1 untersuchten wir die Auswirkungen des Bodentyps (lehmig vs. sandig), der Bewirtschaftung (konventionell vs. ökologisch), der Weizensorte (anspruchslos vs. anspruchsvoll) und die Wechselwirkungen zwischen diesen Faktoren auf die Zusammensetzung und Funktion der Bakteriengemeinschaft in der RhizosphĂ€re von Weizen unter extremen Trockenheitsbedingungen. Das Wasserdefizit ĂŒbte einen starken Druck auf die RhizosphĂ€renbakteriengemeinschaften aus und stand in Wechselwirkung mit dem Bodentyp und der Bewirtschaftung, nicht aber mit den Weizensorten. In den Sandböden beobachteten wir eine starke trockenheitsbedingte VerĂ€nderung der Zusammensetzung der Gemeinschaft mit einem RĂŒckgang der Artenvielfalt und der extrazellulĂ€ren Enzymproduktion, wĂ€hrend die VerĂ€nderungen durch die Trockenheit in den fruchtbaren Lehmböden weniger stark ausgeprĂ€gt waren. Eine besondere Ausnahme von diesem Muster wurde fĂŒr EnzymaktivitĂ€ten gefunden, die am Kohlenstoffkreislauf im Sandboden beteiligt sind, was auf eine positive RĂŒckkopplung zwischen Pflanze und Bodengemeinschaften unter Trockenheit hindeutet. In Kapitel 2 wurden zwei einzelne, jedoch miteinander verknĂŒpfte Ziele verfolgt. Erstens nutzten wir die Plattform der Global Change Experimental Facility (GCEF), um die Auswirkungen von zwei Anbaupraktiken (konventionell vs. ökologisch) und zwei Klimabehandlungen (ambient vs. zukĂŒnftig) auf die Zusammensetzung der Bakteriengemeinschaft und die AktivitĂ€tsprofile extrazellulĂ€rer Enzyme, die an den C-, N- und P-Zyklen in der RhizosphĂ€re von Weizen beteiligt sind, in zwei verschiedenen Pflanzenwachstumsstadien zu untersuchen. Die Klimabehandlung in der GCEF hatte keinen Einfluss auf die RhizosphĂ€renbakteriengemeinschaften. Die Zusammensetzung und die Funktionen der RhizosphĂ€renbakteriengemeinschaften unterschieden sich signifikant zwischen dem vegetativen und dem generativen Wachstumsstadium der Pflanzen, sowohl im konventionellen als auch im ökologischen Landbau. In einem zweiten Schritt nutzten wir die gewonnenen Daten, um die Genauigkeit rechnerischer AnsĂ€tze wie Tax4Fun und PanFP zur Vorhersage funktioneller Profile von Bakteriengemeinschaften auf der Grundlage von 16S rDNA-Daten zu ĂŒberprĂŒfen. Zu diesem Zweck verglichen wir die gemessenen EnzymaktivitĂ€ten mit den jeweiligen GenhĂ€ufigkeiten in der Gemeinschaft unter verschiedenen Klima- und Anbaubedingungen und in den beiden Entwicklungsstadien der Pflanzen. Diese Analyse ergab qualitative, aber nicht unbedingt quantitative Übereinstimmungen, d. h. wir fanden Auswirkungen der verschiedenen Behandlungen auf die gemessenen EnzymaktivitĂ€ten, die sich auch in den GenhĂ€ufigkeiten widerspiegeln. Kapitel 3 stellt einen ergĂ€nzenden Ansatz zu Kapitel 2 dar, wobei der Schwerpunkt auf einzelnen Bakterienarten liegt. Mit kulturabhĂ€ngigen Methoden wurden gezielt stark Phosphat-solubilisierende Bakterien aus der RhizosphĂ€re von Weizen isoliert und auf ihre In-vitro-Trockenheitstoleranz getestet. Unter den mehr als 800 isolierten Arten dominierten Phyllobacterium-, Pseudomonas- und Streptomyces-Arten. WĂ€hrend Anbaumanagement und Klimabehandlung nur geringe Auswirkungen hatten, wirkten sich die Wachstumsstadien des Weizens signifikant auf die Zusammensetzung und Funktionen der Isolate aus, wobei eine Dominanz von Pseudomonas-Arten in der vegetativen Wachstumsphase durch eine Dominanz von Phyllobacterium-Arten in der generativen Wachstumsphase ersetzt wurde. Da das Potenzial zur P-Solubilisierung mit einer hohen in vitro-Trockenheitstoleranz einherging, wurden Phyllobacterium-Arten als vielversprechende pflanzenwachstumsfördernde Rhizobakterien (PGPR) fĂŒr Weizen unter zukĂŒnftigen Trockenheitsbedingungen charakterisiert. In der Synopsis dieser Arbeit bewerteten wir die multifaktoriellen und multidisziplinĂ€ren AnsĂ€tze, und untersuchten, inwieweit die Anpassungen der Bakteriengemeinschaften in Feld- und Topfversuchen ĂŒbereinstimmen oder sich unterscheiden. Insgesamt fanden wir allgemeine, aber auch differenzielle Anpassungsprozesse von Bakteriengemeinschaften und einzelnen Arten in der RhizosphĂ€re von Weizen an die Trockenheit, wobei einzelne Faktoren, aber auch interagierende Effekte einen starken Einfluss auf diese Prozesse ausĂŒbten. Diese Studie unterstreicht damit die Bedeutung multifaktorieller AnsĂ€tze, um gemeinschafts- oder artspezifische RĂŒckkopplungen zwischen Pflanze und Boden zu untersuchen.:Contents 3 Preface 5 Bibliographic description 6 Zusammenfassung 9 Summary 13 Introduction 16 When extreme events become the new normal 17 Feedback to agricultural production and need for management adaptation 20 Difficulties in exploring the soil microbiome and identification of plant beneficial microbial taxa 22 Our approach with wheat 24 Bibliography 27 ֎ Chapter 1 31 Interactions Between Soil Properties, Agricultural Management and Cultivar Type Drive Structural and Functional Adaptations of the Wheat Rhizosphere Microbiome To Drought 31 Supplemental Tables 51 Supplemental Figures 55 ╬ Chapter 2 59 Can We Estimate Functionality of Soil Microbial Communities from Structure-Derived Predictions? A Reality Test in Agricultural Soils 59 Supplementary Tables 79 Supplemental Figures 84 Supplemental Material 1: 87 Variation in edaphic parameters according to experimental factors 87 Supplemental Material 2 88 Effect of abiotic soil parameters on bacterial community structure and function 88 Supplemental Material 3 90 Indicator species analysis 90 ۝ Chapter 3 95 Shifts Between and Among Populations of Wheat Rhizosphere Pseudomonas, Streptomyces and Phyllobacterium Suggest Consistent Phosphate Mobilization at Different Wheat Growth Stages Under Abiotic Stress 95 Supplementary Figures 112 Supplementary Tables 117 Synopsis 152 Multidisciplinary approaches combine advantages of cultivation-based and high throughput community-based methods 155 Multifactorial approaches to gain a more holistic understanding of plant-microbe interactions in pot experiments 157 Transferability of findings gained in the pot experiment to field conditions 159 Towards a wheat core microbiome? 161 Study limitations and outlook 163 Bibliography 164 Acknowledgements 169 Curriculum Vitae 171 Personal details 171 Education 171 Work experience 172 Research and Mentoring experience 172 Extracurricular activities 173 List of publications and Presentations 174 Publications in peer-reviewed journals: 174 Oral Presentations: 175 Poster Presentations: 175 Statutory declaration 176 Eidesstattliche ErklĂ€rung 177 Author contributions 17

    Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity

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    IoT networks are increasingly becoming target of sophisticated new cyber-attacks. Anomaly-based detection methods are promising in finding new attacks, but there are certain practical challenges like false-positive alarms, hard to explain, and difficult to scale cost-effectively. The IETF recent standard called Manufacturer Usage Description (MUD) seems promising to limit the attack surface on IoT devices by formally specifying their intended network behavior. In this paper, we use SDN to enforce and monitor the expected behaviors of each IoT device, and train one-class classifier models to detect volumetric attacks. Our specific contributions are fourfold. (1) We develop a multi-level inferencing model to dynamically detect anomalous patterns in network activity of MUD-compliant traffic flows via SDN telemetry, followed by packet inspection of anomalous flows. This provides enhanced fine-grained visibility into distributed and direct attacks, allowing us to precisely isolate volumetric attacks with microflow (5-tuple) resolution. (2) We collect traffic traces (benign and a variety of volumetric attacks) from network behavior of IoT devices in our lab, generate labeled datasets, and make them available to the public. (3) We prototype a full working system (modules are released as open-source), demonstrates its efficacy in detecting volumetric attacks on several consumer IoT devices with high accuracy while maintaining low false positives, and provides insights into cost and performance of our system. (4) We demonstrate how our models scale in environments with a large number of connected IoTs (with datasets collected from a network of IP cameras in our university campus) by considering various training strategies (per device unit versus per device type), and balancing the accuracy of prediction against the cost of models in terms of size and training time.Comment: 18 pages, 13 figure

    Capturing the Dynamic Nature of Cyber Risk: Evidence from an Explorative Case Study

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    In this research, we developed a novel approach to enable a dynamic cyber risk management strategy as the dynamic nature of cyber risk is rarely considered in current decision support tools. Our explorative case study shows that many management challenges such as investment decisions, priority setting, and “shelf time” analyses can be continuously analyzed. Our research using system thinking and modelling provides valuable insights about these challenges to support current strategic decision-making practices and improve managerial learning. These insights enable management to identify and analyze the effectiveness of future cyber risk management strategies before implementing them

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
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