1,721,090 research outputs found
AI developments for industrial robotics and intelligent drones
No full textIn today's rapidly evolving technological landscape, industries increasingly turn to industrial robots and intelligent drones to streamline processes, improve efficiency, and reduce costs. However, the complexity of these smart devices, coupled with the need for seamless integration of machine learning, AI, robotics, and deep learning technologies, poses significant challenges for researchers and practitioners alike. As a result, there is a growing demand for comprehensive resources that explore the latest advancements in these fields and provide practical insights and solutions for effectively leveraging these technologies. AI Developments for Industrial Robotics and Intelligent Drones addresses this pressing need by offering a detailed and insightful examination of the key technologies driving the development of industrial robots and intelligent drones. By compiling the latest research and developments in the field, this book serves as a comprehensive guide for researchers, scholars, and professionals seeking to understand and harness the full potential of these technologies. Through its in-depth exploration of topics such as industrial robots, intelligent drones, IoT integration, programming, control systems, and security, this book provides readers with a holistic view of the challenges and opportunities in the field. By offering practical insights and real-world examples, this book empowers readers to navigate the complexities of industrial robots and intelligent drones, making it an indispensable resource for anyone looking to stay at the forefront of technological innovation
Context awareness for e-Tourism: An adaptive mobile application
No full textThe Italian towns have a cultural heritage that often do not succeed in being completely enhanced. The natural, artistic and cultural resources present in the Italian towns, above all the smallest ones, many times remain hidden and are not enjoyed by the tourists. In this paper, it is introduced an Adaptive Context Aware app able to support a tourist inside a town. The system can guide the tourist in the discovery of a town proposing him/her resources and services mainly interesting for the user according to his/her interests and the position where he/she is. The objective is reached through the use of a system of description of the context through a graphical formalism named Context Dimension Tree. The App collects information also from social environments adapting the proposed itinerary taking into account the communities and the interests of the user. The entire approach has been tested inside the town of Salerno with very interesting results
Adaptive hypermedia system: A design proposal and a case study
No full textAdaptive hypermedia is a new and promising area of research at the crossroads of hypermedia and adaptive systems. One of the most important fields where this approach can be applied is the e-Learning. In this context the adaptive learning resources selection and sequencing is recognized as among the most interesting research questions. This paper addresses the design problem of an Adaptive hypermedia system by the definition of original user and adaptation model. The proposed adaptive hypermedia system was integrated in an e-Learning platform and an experimental campaign was conducted. In particular we used the proposed approach in three different blended courses (Introduction to Computer Science, Computer Networks and Web Design) and a comparison with traditional approach was conducted. The obtained results are very promising. © 2009 IEEE
Lightweight Ciphers in Automotive Networks: A Preliminary Approach
No full textNowadays, the growing need to connect modern vehicles through computer networks leads to increased risks of cyberattacks. The internal network, which governs the several electronic components of a vehicle, is becoming increasingly overexposed to external attacks. The Controller Area Network (CAN) protocol, used to interconnect those devices is the key point of the internal network of modern vehicles. Therefore, securing such protocol is crucial to ensure a safe driving experience. However, the CAN is a standard that has undergone little changes since it was introduced in 1983. More precisely, in an attempt to reduce latency, the transfer of information remains unencrypted, which today represents a weak point in the protocol. Hence, the need to protect communications, without introducing low-level alterations, while preserving the performance characteristics of the protocol. In this work, we investigate the possibility of using symmetric encryption algorithms for securing messages exchanged by CAN protocol. In particular, we evaluate the using of lightweight ciphers to secure CAN-level communication. Such ciphers represent a reliable solution on hardware-constrained devices, such as microcontrollers
A Multilevel Graph Representation for Big Data Interpretation in Real Scenarios
No full textNowadays with the increase of smart objects, which make our world ever smart, it can be possible to observe a rapidly growing up of a large amount of data produced from a various sources. Even if there are numerous approaches, automatic and manual, present in the literature that try to interpret data by extracting information, these data become overwhelmed with a mass of information that is difficult to understand. In this context, we have to analyse and understand the data in order to have a new knowledge starting from this information. These data, if correctly managed, could help us for Big Data analysis and it has helpful for Smart City application. The main aim of this paper is to provide an approach for data interpretation, which take advance of three graphs (Ontologies, Context Dimension Tree and Bayesian Networks). This approach, through graph approaches abovementioned, is able to represent the real scenario both from the point of view of the sensors involved and of the services and events connected to the data
Predictive Maintenance of an Archeological Park: An IoT and Digital Twin Based Approach
No full textThe preservation of cultural heritage is one of the main goals that a nation must pursue since it represents an important resource, both economically and for the historical memory it holds. Thanks to the spread of new technologies, the possibility of applying innovative approaches to historical heritage is becoming increasingly real, in order to monitor in real time the progressive damage of structures or intercept any sudden risk situations. In this scenario, a significant contribution is made by the paradigm of the Internet of Things, which enables the collection in real time, of data from sensors installed on the structures to be monitored, and the concept of the Digital Twin, which represents a digital copy of reality, and can be utilized for practical purposes, such as simulations and tests. To make the Digital Twin even more effective, it is possible to link it to the real structure through HBIM, which is a process that aims not only at the mere restitution of the tridimensional model but at the creation of so-called “smart models”, in which all the components are parametric objects with well-defined semantics and capable of containing all the information useful for understanding the artifact. The paper, therefore, presents a methodology to consider HBIM models as Digital Twins enriched with data from real-time IoT devices placed on the structures to be monitored. The proposed methodology was applied to a real case study within the Velia Archaeological Park: Porta Rosa, which is the oldest known example of a round arch in Italy. The first results of the experiment are more than satisfactory
A multigraph approach for supporting computer network monitoring systems
No full textThe pervasiveness of information technologies has reached very high levels: most human activities involve the use of sensor-based systems connected to the network. The increasingly widespread use of the Internet of things has significantly improved our quality of life but has introduced a series of new problems, especially from the security point of view. Protecting these systems from cyber-attacks has become a priority as possible malfunctions can lead to issues with a significant social impact. Imagine, for example, computer attacks on smart cars connected to the network or remotely controlled electrical or water systems. Protecting this type of system is a complex task as there are many elements to consider and the data to be monitored. An analysis able to foresee eventual attacks through the study of the data and their variations could be a useful tool to prevent malfunctions. This paper proposes a methodology based on the integrated use of three graphic models to address the problem of preventing attacks on pervasive systems from three different perspectives: probabilistic, contextual, and ontological. The paper proposes the use of Bayesian networks built through an ontological definition of the problem dropped on a particular context represented by a Context Dimension Tree—the proposed approach experiments in a real scenario providing satisfactory results
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