Abstract Following the period marked by the spread of the COVID-19 virus, tourists and enthusiasts flocked to museums and archaeological parks, highlighting persistent and emerging challenges concerning the enhancement of cultural heritage. This study proposes a novel framework that leverages context-aware recommender systems (CARS) to personalize the cultural experience based on the contextual conditions in which it occurs. The framework has been specifically developed and tested within the archaeological sites of Paestum and Pompeii. The evaluation process was conducted in two phases. The first phase focused on assessing the accuracy and reliability of the proposed context-aware approach, using a dataset comprising 972 user ratings collected from visitors to the Pompeii archaeological park. The second phase measured user satisfaction through a large-scale, in situ evaluation conducted directly within the archaeological parks. This phase involved nearly 2000 participants and aimed to assess the real-world usability and perceived satisfaction of the platform through direct interaction in cultural settings. The results confirm the effectiveness of the approach, with over 90% of respondents expressing a high level of satisfaction.

The growing intricacy in the administration of solar systems necessitates novel strategies to guarantee efficiency and reliability. This research presents a sophisticated methodology for developing a Digital Twin for the solar system at the University of Salerno campus. The primary aim is to create a dynamic digital model that facilitates real-time monitoring of the system's operational conditions and enhances predictive maintenance techniques. The integration of sophisticated technologies, including the Internet of Things (IoT), Building Information Modeling (BIM), and Geographic Information Systems (GIS), enabled the creation of a virtual replica of the physical system. The ThingsBoard platform centralizes and analyzes the real-time data collected by IoT sensors, while Autodesk Revit and Dynamo create a parametric BIM model that enables a comprehensive and interactive depiction of the system. Georeferencing and spatial analysis, executed using ArcGIS, enhance the Digital Twin, facilitating a thorough comprehension of the interactions between the system and its environmental surroundings. The findings indicate that the Digital Twin facilitates prompt anomaly identification, failure prevention, and the simulation of predictive maintenance scenarios. This approach enabled the optimization of operational management and a substantial reduction in maintenance expenses. The method shows how the Digital Twin can be used to effectively manage solar power plants and can serve as a model for managing other important infrastructures. This helps promote sustainable and resilient management.

Spa treatments may mistakenly be considered palliative compared to traditional medicines; however, this is not the case. Mineral/thermal waters are medicines for all intents and purposes and should be analyzed and used as such. The difference in spa treatments compared to other medicines is the greater complexity with which they are delivered. Patients must follow a course of treatment that can last up to a couple of weeks, during which the effects of the therapy gradually go into evidence. Both inside and outside the spa facility, having patient monitoring could be a valuable tool to measure the effectiveness of treatment and possibly even intervene with personalized care based on the parameters detected. New technologies and paradigms such as the Internet of Things can offer a valuable tool to improve spa care through active monitoring of patients, both inside and outside the facilities, by going to measure what are the key parameters (i.e., heart rate, blood oxygenation, etc.) to track the progress of the therapy accurately and precisely during treatment. In particular, wearable devices (smartwatches or smart bands) can perform constant and non-invasive monitoring of the patient's status and the therapy itself. Therefore, the work aims to define a framework based on the Internet of Things paradigm for intelligent analysis of spa treatments to manage patients correctly.

Cultural Heritage Buildings need to be preserved through interventions and actions that ensure accessibility and availability to present and future generations. The diffusion o f new technologies, including low-cost sensors and devices, has introduced many possibilities and strategies to monitor environments, including Historical and Cultural value buildings. Based on the Internet of Things (IoT) paradigm, modern devices and sensors can collect and manage helpful information to build a Digital Twin of the surrounding environment. In this scenario, reproducing a Digital Twin of Cultural Heritage Buildings could be crucial to monitoring, managing, and performing action aiming to protect them. One of the challenges in recent years is the automatic analysis of collected information. This paper introduces a novel approach to protecting Buildings using Heritage Building Information Modeling (HBIM), which leverages a sensor network and Deep Learning techniques to analyze sensor data. A case study related to the Archeological Park of Pompeii will be presented, where real-time collected data is managed and shared via a web-cloud-IoT platform. Then, collected data are analyzed through a Generative Adversarial Network (GAN) to prevent future issues related to Cultural Heritage Buildings, particularly humidity inside structures, which is crucial for ancient building preservation.

In March 2020, due to the pandemic linked to the COVID-19 virus spreading, all in-person teaching activities planned at the University of Salerno were suspended. This sudden suspension has forced the academic world to rethink in a short time the didactics and to modify teaching styles and approaches, especially in those courses in which laboratory activities were planned. This article will be presented the experiences made in the Computer Networks and Protocols for the Internet of Things (IoT) course. The course includes a significant laboratory component where students must put into practice what they learned during the theoretical lessons. In particular, the laboratory exercises involve using specific equipment and devices that can build digital ecosystems for the control and management of well-defined operational contexts difficult to reproduce virtually. Therefore, to give continuity to the didactic activity, it was necessary to redesign the entire exercise system preserving the original educational objectives.

The world of Cultural Heritage finds significant ad-vantages from fusion with new technologies. For example, the use of Recommender Systems to analyze contextual information and the Digital Storytelling technique allows improving the experience of users who get in touch with artistic and cultural heritage. This paper aims to describe a new approach that suggests cultural-touristic paths exploit recommendation techniques and propose multimedia content. Moreover, the proposed approach aims to provide recommendations when ratings are unknown, using a novel approach that takes advantage of the user and item profile knowledge. The proposed approach has been tested through an application prototype. The test involved standard and expert users of the University of Salerno with promising results.

Today, the existing technologies, such as smartphone and other pervasive devices, can be used for context awareness and help people to undertake conscious choices.In fact, unlike what happened in the past, all of these data are managed and contextualized for the particular application.We need to understand, select, treat and finally opportunely expose these data.In this scenario, there are many Context Aware applications.This paper introduces a tailor made system for providing personalized services and it is based on a graphical formalism for the context representation: the Context Dimension Tree.This system provides the needed information about places that are of great interest for the visitors, selecting them using user preferences.A case study is applied to an event in Salerno, an Italian town, called Artist's Lights.Finally, an experimental campaign has been conducted, obtaining interesting results.

This letter deals with the problem of adaptive detection in Gaussian disturbance with unknown but persymmetric structured covariance matrix. A partially-homogeneous environment is considered at the design stage, and a receiver based on the generalized likelihood ratio test (GLRT) is derived. At the analysis stage, the performance of the new receiver is assessed, also in comparison with the unstructured GLRT, showing that thea-prioriinformation on the covariance structure can lead to a noticeable performance improvement.