An effective and efficient web platform for monitoring, control, and management of drones supported by a new microservices approach

In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality, however, these systems are quite simple and directed to specific functionality. This dissertation proposes the development of a web platform made in Vue.js and Node.js to control, manage and monitoring drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks, and can be done in real time or by scheduling routes. This dissertation addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone, without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.Nos últimos anos tem-se assistido a um grande crescimento do uso de drones, sendo utilizados em diversas áreas como a da segurança, da agricultura ou da investigação. A existência de alguns sistemas que permite o controlo de drones à distância é uma realidade, porém, estes sistemas são bastante simples e direcionados a uma funcionalidade específica. Esta dissertação propõe a elaboração de uma plataforma web feita em Vue.js e Node.js para controlar, gerir e monitorizar drones em tempo real. Usando uma arquitetura de microsserviços, o projeto proposto será capaz de integrar algoritmos que permitem a otimização de processos. A comunicação com os aparelhos remotos é sugerida via HTTP através das redes de 3G, 4G e 5G, e pode ser feita em tempo real ou através de agendamento de rotas. Esta dissertação aborda o caso dos incêndios florestais como um dos serviços que poderia ser incluído num sistema semelhante ao apresentado. Os resultados obtidos com a elaboração deste projeto foram um sucesso. A comunicação entre a plataforma web com drones permitiu o seu controlo e monitorização à distância. A incorporação do algoritmo de deteção de incêndios na plataforma demonstrou ser possível uma análise em tempo real das imagens captadas pelo drone, sem intervenção humana. O sistema proposto demonstrou ser uma mais valia ao uso de UAVs na deteção de incêndios. A arquitetura da aplicação desenvolvida permite que outros algoritmos sejam implementados, obtendo uma aplicação mais complexa e com clara expansão

The role of communication systems in smart grids: Architectures, technical solutions and research challenges

The purpose of this survey is to present a critical overview of smart grid concepts, with a special focus on the role that communication, networking and middleware technologies will have in the transformation of existing electric power systems into smart grids. First of all we elaborate on the key technological, economical and societal drivers for the development of smart grids. By adopting a data-centric perspective we present a conceptual model of communication systems for smart grids, and we identify functional components, technologies, network topologies and communication services that are needed to support smart grid communications. Then, we introduce the fundamental research challenges in this field including communication reliability and timeliness, QoS support, data management services, and autonomic behaviors. Finally, we discuss the main solutions proposed in the literature for each of them, and we identify possible future research directions

IEEE Access special section editorial: Mission critical public-safety communications: architectures, enabling technologies, and future applications

Disaster management organizations such as fire brigades, rescue teams, and emergency medical service providers have a high priority demand to communicate with each other and with the victims by using mission-critical voice and data communications [item 1) in the Appendix]. In recent years, public safety agencies and organizations have started planning to evolve their existing land mobile radio system (LMRS) with long-term evolution (LTE)-based public safety solutions which provides broadband, ubiquitous, and mission-critical voice and data services. LTE provides high bandwidth and low latency services to the customers using internet protocol-based LTE network. Since mission critical communication services have different demands and priorities for dynamically varying situations for disaster-hit areas, the architecture and the communication technologies of the existing LTE networks need to be upgraded with a system that has the capability to respond efficiently and in a timely manner during critical situations

Decentralized Access Control in Distributed File Systems

The Internet enables global sharing of data across organizational boundaries. Distributed file systems facilitate data sharing in the form of remote file access. However, traditional access control mechanisms used in distributed file systems are intended for machines under common administrative control, and rely on maintaining a centralized database of user identities. They fail to scale to a large user base distributed across multiple organizations. We provide a survey of decentralized access control mechanisms in distributed file systems intended for large scale, in both administrative domains and users. We identify essential properties of such access control mechanisms. We analyze both popular production and experimental distributed file systems in the context of our survey

Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles

The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors’ firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians. Connected vehicles will soon become a reality on our roads, bringing along new services and capabilities, but also technical challenges and security threats. To overcome these risks, the CARAMEL project has developed several anti-hacking solutions for the new generation of vehicles. CARAMEL (Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles), a research project co-funded by the European Union under the Horizon 2020 framework programme, is a project consortium with 15 organizations from 8 European countries together with 3 Korean partners. The project applies a proactive approach based on Artificial Intelligence and Machine Learning techniques to detect and prevent potential cybersecurity threats to autonomous and connected vehicles. This approach has been addressed based on four fundamental pillars, namely: Autonomous Mobility, Connected Mobility, Electromobility, and Remote Control Vehicle. This book presents theory and results from each of these technical directions

State-of-the-art authentication and verification schemes in VANETs:A survey

Vehicular Ad-Hoc Networks (VANETs), a subset of Mobile Ad-Hoc Networks (MANETs), are wireless networks formed around moving vehicles, enabling communication between vehicles, roadside infrastructure, and servers. With the rise of autonomous and connected vehicles, security concerns surrounding VANETs have grown. VANETs still face challenges related to privacy with full-scale deployment due to a lack of user trust. Critical factors shaping VANETs include their dynamic topology and high mobility characteristics. Authentication protocols emerge as the cornerstone of enabling the secure transmission of entities within a VANET. Despite concerted efforts, there remains a need to incorporate verification approaches for refining authentication protocols. Formal verification constitutes a mathematical approach enabling developers to validate protocols and rectify design errors with precision. Therefore, this review focuses on authentication protocols as a pivotal element for securing entity transmission within VANETs. It presents a comparative analysis of existing protocols, identifies research gaps, and introduces a novel framework that incorporates formal verification and threat modeling. The review considers key factors influencing security, sheds light on ongoing challenges, and emphasises the significance of user trust. The proposed framework not only enhances VANET security but also contributes to the growing field of formal verification in the automotive domain. As the outcomes of this study, several research gaps, challenges, and future research directions are identified. These insights would offer valuable guidance for researchers to establish secure authentication communication within VANETs

Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified