DunavNET (Serbia)

Blockchain offers decentralized, trustworthy and immutable data storage based on distributed ledger technology. Blockchain technology is recognized as an innovation enabler in many areas, with the food supply chain being one of them. This paper provides a systematic literature review of the current state of adoption of blockchain technology in the agri-food sector, specifically with a focus on the wine supply chain. Blockchain has the potential to improve the traceability and authenticity of the data provenance of wine products, increase consumer trust, and reduce fraud and errors. With these goals in mind, this study identifies the main research questions pertinent to the value proposition and competitive advantage of blockchain technology in the wine value chain and key players involved in the authentication and value chain recording. The PRISMA methodology was adopted to identify, screen and select only the relevant studies that were included in the analysis. This study also addresses the limitations and challenges for adoption, such as high implementation cost and lack of competences, and the need for standardized protocols and regulations. Finally, this systematic literature review includes an analysis of reports of blockchain applications in the wine sector and outlines the recommendations for future research to further explore the potential of blockchain-based solutions that could benefit all stakeholders across the wine value chain.

The scope of Internet of Things (IoT) European Platforms Initiative (IoT-EPI) is to create ecosystems of "Platforms for Connected Smart Objects", integrating the future generations of devices, embedded systems, network technologies, and other evolving ICT advances.

The food market is changing dramatically in the last century as the world population is growing with the unprecedented pace. The wine industry is recognized as part of both agriculture and food industry, but also as a commodity. Developments in information technology and digitalization are playing a major role in the introduction of new solutions in agriculture and food production. The idea is to improve productivity of farms and vineyards, improve quality of agriculture products by optimizing irrigation, pesticide usage, and overall efficiency of the process. Furthermore, the consumer awareness about food products, its quality and origin, is on the constant rise. The information about the product throughout the whole “farm-to-fork”, or in this case “vineyard-to-glass”, value chain needs to be collected and utilized by all the participating stakeholders, in order to get a better, healthier, and more affordable product. This paper address the considerations related to implementation of a blockchain-based transparency and data provenance in the food value chain, more specifically with a focus on the wine industry.

This paper presents the evaluation of a fungal disease forecast model in vineyards for qualitative parameter analysis using the data from off the shelf sensors, i.e. temperature and air relative humidity, rain precipitation, and leaf wetness. The rules for the fungal disease models are digitalized as a decision support tool that serve as an indicator to farmers for the need of spraying of the chemical substances to ensure the best growing condition and suppress the level of parasites. The temperature and humidity contexts are used interchangeably in practice to detect the risk of the disease occurrence. By taking into account a number of influences on these parameters collected from the shelf sensors, new topics for research in the multidimensional field of precision agriculture emerge. In this study, the impact of the humidity is evaluated by assessing how different humidity parameters correlate with the accuracy of the Botrytis cinerea fungi forecast. Each humidity parameter has it’s own threshold that triggers the second step of the disease modeling - risk index based on the temperature. The research showed that for humidity a low-cost relative humidity sensor can detect in average 14.61% risk values, a leaf wetness sensor an additional 3.99% risk cases, and finally, a precipitation sensor will detect only an additional 0.59% risk cases.

We present a review of papers considering the subcarrier intensity modulation free-space optical (FSO) communication systems in the presence of phase noise. This phase noise is a consequence of imperfect reference signal extraction in electrical domain after photodetector. We illustrate the effects of this phenomenon on the system symbol-error rate performance. The examples show that receiver imperfections, presented through phase noise, can degrade the FSO system performance to a large extent.

This paper presents SemMR, a semantic framework for modelling interactions between human and non-human entities and managing reusable and optimized cultural experiences, towards a shared cultural experience ecosystem that might seamlessly accommodate mixed reality experiences. The SemMR framework synthesizes and integrates interaction data into semantically rich reusable structures and facilitates the interaction between different types of entities in a symbiotic way, within a large, virtual, and fully experiential open world, promoting experience sharing at the user level, as well as data/application interoperability and low-effort implementation at the software engineering level. The proposed semantic framework introduces methods for low-effort implementation and the deployment of open and reusable cultural content, applications, and tools, around the concept of cultural experience as a semantic trajectory or simply, experience as a trajectory (eX-trajectory). The methods facilitate the collection and analysis of data regarding the behaviour of users and their interaction with other users and the environment, towards optimizing eX-trajectories via reconfiguration. The SemMR framework supports the synthesis, enhancement, and recommendation of highly complex reconfigurable eX-trajectories, while using semantically integrated disparate and heterogeneous related data. Overall, this work aims to semantically manage interactions and experiences through the eX-trajectory concept, towards delivering enriched cultural experiences.

The chapter focuses on the importance of a strong ecosystem for successful and sustainable market presence in the Internet of Things world. It analyzes emerging value and business models together with the ecosystem structure and the roles of different stakeholders. The supply chain domain-related use cases, the ecosystem supporting them as well as ways of creating and expanding such ecosystems are given based on the experience of H2020 TagItSmart! project, which ran for over three years with more than 30 partners.

Dynamicity of the cloud computing system, complexity of real-world decision-making problems, and nontransparent market imply numerous difficulties in finding the corresponding solution for cloud supplier evaluation and selection. Due to that reason, there is a need to develop a model that can contribute to increase of reliability of evaluation and reduction of subjectivity of the decision-maker. Having in mind the aforementioned, the authors proposed a new concept to model a cloud supplier evaluation based on technology perspective. Here, we developed a model that combined fuzzy techniques with implemented simulation of model parameters. The proposed method for cloud supplier evaluation is flexible with an objective evaluation and ensures more precise numerical value. Numerical examples are presented to demonstrate the effectiveness and pragmatism of the proposed approach.