Accurate energy consumption forecasting is essential for optimizing energy management in smart grids. Traditional models often fail to capture both short-term fluctuations and long-term dependencies. To address this, we propose a hybrid CNN-LSTM model enhanced with Fourier Transform features. CNNs extract local patterns, LSTMs model temporal dependencies, and Fast Fourier Transform (FFT) incorporates frequency-domain insights to improve trend recognition. Evaluated on real-world StoreNet energy data, the proposed model outperforms baseline LSTM and traditional forecasting methods. It achieves lower Mean Squared Error (MSE) and Mean Absolute Error (MAE) while increasing the R ^2 score, demonstrating superior predictive accuracy. Additionally, a 5.04

Artificial Intelligence is progressively employed in the decision-making processes of the public sector; nevertheless, the absence of transparency and reliability in these systems may result in societal distrust. The domain of Explainable AI (XAI) has emerged as a critical instrument for augmenting transparency and accountability in this particular area. To effectively implement XAI in the public sector, it is crucial to employ systems that guarantee reliability and verifiability. Integrating blockchain technology—particularly through the use of oracles—provides external, trustworthy data to AI systems, enhancing explainability and enabling automation. Oracles act as secure bridges between external data sources and the blockchain, ensuring that AI models are based on authentic and tamper-proof information. Moreover, the decentralization, cryptography, and traceability offered by blockchain provides a guarantee to citizens: they ensure the integrity and confidentiality but also facilitate transparency and traceability in the decision-making process. The use of smart contracts automates compliance with regulations and policies, increasing the efficiency and security of AI systems. This approach assists in reducing the risk of bias and discrimination, facilitating auditing and oversight. By offering verifiable explanations of decisions, it fosters citizen's trust in institutions and promotes participation in the decision-making procedure. This integrated framework, grounded in ethical principles and respect for privacy, optimizes resource use while promoting equity and social cohesion. It facilitates the establishment of more robust and sustainable institutions by aligning with the Sustainable Development Objectives (SDOs). By supporting environmental and social sustainability, XAI enhanced with blockchain technology ensures a positive impact on both the community and the environment.

Smart agriculture is transforming a traditionally static sector by introducing advanced monitoring of crop processes and field conditions. In particular, the integration of the Internet of Things with Distributed Ledger Technology enhances agricultural operations by enabling real-time insights and fostering trust through secure, tamper-proof data management. This paper presents an innovative system that leverages IOTA’s decentralized ledger to securely capture and store realtime data from IoT sensors monitoring key environmental parameters such as temperature, humidity, and soil moisture. By removing centralized control, the system ensures data integrity, transparency, and resistance to tampering. Additionally, the use of smart contracts developed in the Move programming language strengthens the platform by automating data validation and facilitating traceable, reliable interactions. Field implementation demonstrates the system’s potential to improve decision-making, minimize resource waste, and support sustainable agricultural practices. Emphasizing security, scalability, and cost-efficiency, this solution offers a forward-looking approach to precision agriculture.

With the development of communications technologies, the remarkable progress of IoT and the growth of Industry 4.0 in recent years, research in cybersecurity is of increasing interest in industry and economic field. Moreover, quantum computing threatens to break traditional cryptographic systems and traditional cybersecurity schemes. Therefore, it is essential to deploy new solutions in order to overcome this challenge. In this paper we address some of the most relevant aspects of the field of cybersecurity in the context of the development of quantum technologies, both in terms of challenges to be overcome and new opportunities. In this sense, the article is divided into several sections that address the different aspects. Each of the sections consists of two parts. The first part consists of a brief bibliographical review. The second part introduces a framework and a roadmap to advance in the investigation of each of them in the future.

As communication technologies evolve and the Internet of Things (IoT) continues to advance, along with the rapid growth of Industry 4.0, the importance of cybersecurity research is increasingly recognised across industrial and economic sectors. Furthermore, quantum computing poses a significant challenge to traditional cryptographic methods and established cybersecurity protocols. Consequently, the development of new approaches to address these emerging risks and opportunities is vital. The article is structured into multiple sections focused on different aspects, with the central part being the section on Regev’s algorithm and QML for cyberattack detection. Each of these two sections is divided into two parts: the first provides the main challenge encountered in the implementation of quantum algorithms for prime factorisation and threat detection, while the second explains the chosen strategy to address it. The final section of this study will present a review of the potential economic impact of these advances. The main outcome of this paper is to show the way forward in quantum algorithms research for cybersecurity in the post-quantum era, both for key cracking and cyber-attack detection.

Europe’s position in the current cloud market needs to be improved. This market is currently dominated by non-European players by 75%, shaping the way that Europe is deploying and using cloud services. Although these players are bound to laws and regulations of foreign powers, such as PR China and USA, generating legitimate concerns for the EU, its businesses and citizens. EU’s digital future resides on having installed secure, high-quality data processing capacity. This can only be offered by cloud services both centrally and at the edge. In this context NOUS’s ambition is completely in line with the European Strategy for data as aims to create the foundations for a European Cloud Service which exploits the HPC network and tackles specific-to-the-EU-economy requirements as well as leverages different data spaces (Mobility, Energy, Green Deal and Manufacturing).

This paper examines the use of blockchain technology in improving the carbon offset market and promoting carbon farming for smallholders. The paper presents a survey of six blockchain-based platforms for carbon offsetting, namely Blockchain for Climate Foundation, Open Climate Collabathon, Aircarbon Exchange, Cryptocarbon NFT, Toucan, and KlimaDAO. The platforms were evaluated based on their impact on the carbon offset market, and their potential to make carbon farming operational for smallholders was discussed. Overall, this paper demonstrates that blockchain technology has the potential to enhance the carbon offset market and empower smallholders in carbon farming.

While Distributed Ledger Technologies offer (DLT) increased security, transparency, and resilience, the decentralized ecosystem is currently fragmented, lacking interoperability between different DLT platforms. Bridging protocols act as a bridge between different DLT networks, enabling the transfer of assets and data across disparate systems. This paper explores the development of bridging protocols in DAG-based DLTs, with a focus on facilitating interaction between IOTA and other networks. This paper offers insights into the characteristics and requirements of effective bridging protocols, which are crucial for realizing the full potential of DLTs and unlocking new use cases for decentralized systems.

Databases play a fundamental role in today’s world, being used by most companies, especially those that offer services through the Internet. Today there is a wide variety of database models, each adapted for use according to the specific requirements of each application. Traditionally, the relational models with centralized architectures have been used mostly due to their simplicity and general-purpose query language, which made relational systems suitable for almost any application. However, with the growth of the Internet in recent decades, both in the number of users and in the amount of information, those centralized models began to suffer availability and scalability issues. To address those issues, the use of decentralized architectures and alternative database models began to arise, eventually replacing relational databases and centralized architectures when the requirements on availability and scalability are high. Those database models alternative to the traditional relational model are grouped under the name of NoSQL (Not only Structured Query Language). In this article, we present a NoSQL database developed as an end of degree work, with a flexible data model based on documents and a fully decentralized architecture based on the Gossip protocol for node discovery and a distributed hash table, in particular the rendezvous hashing algorithm, used to distribute and replicate the data across all the nodes. The main goals of the system are to achieve high availability (the data should be almost always accessible) and high scalability (the system should be able to scale by increasing the number of nodes to increase its capacity both on data and number of users). High availability is achieved thanks to the replication of the data, while high scalability is achieved by its decentralized architecture, which allows multiple entry points from the requests, and the data distribution, effectively increasing the database capacity by increasing the number of nodes.

Industry 4.0 (the Fourth Industrial Revolution) is a concept devised for improving the operation of modern factories through the use of the latest technologies, under paradigms such as the Industrial Internet of Things (IIoT) or Big Data. One of such technologies is Blockchain, which is able to provide industrial processes with security, trust, traceability, reliability and automation. This paper proposes a technological framework that combines an information sharing platform and a Blockchain platform. One of the main features of the this framework is the use of smart contracts for validating and auditing the content received throughout the production process to ensure the correct traceability of the data. The conclusion drawn from this study is that this technology is under-researched and has significant potential to support and enhance the industrial revolution. Moreover, this study identifies areas for future research.

Boosting the engagement of users and content creators is of critical importance for online video platforms. The success of an online platform can be defined by the number of active users and the amount of time they spend on it, as they will probably take the best advantage of all the available functionalities and spread the word about it. The goal of this research is to propose effective algorithms to create a reputation system capable of generating trust among users and increasing engagement. The algorithm rewards users and content creators for their actions, in addition to motivating them through considerable increases in their reputation during their initial iterations with the platform. The growth is modelled by three basic reputation functions: exponential, logarithmic and lineal mappings. The Noixion TV platform has been used to develop the use case and its data has been gathered to analyse the behaviour of the proposed system.

This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris-Vélib' Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques.

Organization-based multi-agent systems (MASs) are open distributed systems, to which other distributed intelligent systems can be connected. The scalability of virtual organizations (VOs) is an advantage in the development of smart distributed systems, but at the same time it can create security issues as the newly incorporated systems may be malicious. To ensure the security of the system, this work proposes the use of a main blockchain with additional blockchains created by new VOs, which support the main system. Another advantage of agent organizations is that they can be created according to the needs of the system and their function may change whenever required. This chapter introduces the concept of EdgeChain, and a case study is conducted with bank transactions to evaluate the proposal. On certain days of the month, banks have an increase in transactions due to the payment of bills, payroll income, etc. The proposed model is based on virtual agent organizations and will be used to create EdgeChains that optimize on-demand bank transactions. EdgeChains will be created with certain specifications as required (e.g. more processing capacity). In this work, we present a new method based on VOs of agents and blockchain technology, designed to improve the processes according to demand.

This paper proposes an architecture capable of responding to the acquisition, processing and storage of information using as reference data of the Smart City, for this purpose it will suggest the use of certain technologies to be used together to meet the needs of a Smart City. A new Cloud Computing paradigm will be used, Sensing as a Service increasing the amount of data recovered and processed to add more value to the system. It proposes the creation of an open, flexible, extensible and self-adaptive architecture in a Big Data environment, capable of providing the acquisition and processing of large volumes of information while maintaining reliability and availability, as well as allowing easy adaptation in terms of scalability.

As a result of the 2017 boom in the cryptocurrency market, some governments around the world have begun to work in the direction of regularizing and supervising digital currency. People have gained trust in the use of cryptocurrency thanks to the security of the blockchain technology and of their economic ecosystem. This paper reviews the challenges faced by five different cryptocurrencies with the highest market capitalization. Furthermore, we analyze the blockchain technology that underlies them.

The increase in population is increasing the growth of the number of residues. A large amount of this waste can be recycled so that it does not remain in uncontrolled landfills, pollute air, land or water. Although many campaigns and policies of recycling have been developed all-way there is not a total awareness about this problem and a large number of waste does not end up in the right place to be recycled. It is necessary to increase the amount of recycled waste and for this citizen participation is key. It is vital to involve the population in a more active way to recycle through some kind of social benefit. For this reason, GarbMAS proposes a system that generates a motivation for citizen participation by reducing the garbage tax applied by its local government. Thus, the increase in the amount of waste collected to be recycled is expected. GarbMAS employs a multi-agent system that simulates data collection and efficient waste management in cities through gamification techniques to produce the change motivation of citizens and therefore increase participation and recycled quantity. The case study in which the simulation was carried out showed an increase in citizen participation by 34.2% and an increase of 29.4% in the amount of waste collected.

Databases are an essential tool in the real world. Traditionally, the relational model and centralized architectures have been used mostly. However, with the growth of the Internet in recent decades, both in the number of users and in the amount of information, the use of decentralized architectures and alternative database models to the relational model has been extended, which receive the name of NoSQL (Not only Structured Query Language) databases. With the present end of degree work, the development of a distributed NoSQL database is proposed, which will try to achieve high availability and high scalability through a decentralized architecture based on DHT (Distributed Hash Tables).

Although the majority application of Blockchain Technologies (BT) are in the field of cryptocurrencies, they are gradually spreading to other services where a decentralized, reliable and immutable model makes sense. One of the fields where the use of Blockchain Technologies is spreading the most is in Smart Contracts, computer programs which are executed in the blockchains establishing a collection of clauses between the participating parties that agree to interact with each other and that are executed automatically at the moment in which these clauses are fulfilled. As it is a computer code, both the client and the service provider cannot misinterpret the agreed clauses, facilitating and verifying the agreement of the contract. This article will review existing applications and reviews the main vulnerabilities of Smart Contracts deployed within Blockchain Technologies. It also reviews the legal implications of the use of these technologies.