Micromobility completely changes the way we move within cities. It allows to cover small-medium distances and promote an environmentally friendly way of moving, reducing pollution and traffic. However, in micromobility sharing systems, despite these advantages, the location of vehicles can generate an imbalance between supply and demand by making some areas better served than others and an unequal level of service among system users. To solve these issues, that may jeopardise the implementation of a sharing system, an appropriate relocation planning can be proposed. To the best of our knowledge in literature, for free-floating micromobility electric vehicle sharing systems, no studies deal with relocation considering battery swapping operations and the evaluation of the system equity during the day. For this reason, we propose an integer linear programming optimisation model that aims at providing minimum cost night balancing tours, with related pick-up, drop-off and battery swapping operations, that also optimise demand satisfaction and equity as a measure of a fair distribution of electric vehicles among the zones of the system area. In this study, to evaluate equity, we propose a modified Gini index which considers the available number of electric vehicles and their state of charge. The model pursues equity by defining, for each zone, a target fair number of electric vehicles to be available at the end of the rebalancing tours. These parameters are inferred by means of data-driven microsimulation and data analytics techniques. The proposed data-driven microsimulator, that simulates the functioning of a free-floating micromobility system, is also used to assess the results of the optimisation model. The methodology has been applied to a real case study considering an e-scooter-sharing system: the optimisation model, fed by the parameters learned from data-driven simulation, was able to compute efficient rebalancing tours with different trade-offs between demand satisfaction and equity. Simulation confirmed that optimal balancing tours improve equity while preserving operational efficiency and demand satisfaction, although intermediate (dynamic) rebalancing may be beneficial from an equity standpoint after the midday peak hour. Overall, the proposed methodology provides an interesting tool to support equity-aware electric micromobilty systems’ operations.

Online Social Networks (OSNs) rely on content moderation systems to ensure platform and user safety by preventing malicious activities, like the spread of harmful content. However, there is a growing consensus suggesting that such systems are unfair to historically marginalized individuals, fragile users, and minorities. Additionally, OSN policies are often hardcoded in AI-based violation classifiers, making personalized content moderation challenging. In addition, there is a need for more communication between users and platform administrators, especially in case of disagreement about a moderation decision. To address these issues, we propose integrating content moderation systems with Large Language Models (LLMs) to enhance support for personal content moderation and improve user-platform communication. We also evaluate the content moderation capabilities of GPT 3.5 and LLaMa 2, comparing them to commercial products, as well as discuss the limitations of our approach and the open research directions.

Road anomaly detection is crucial for improving road-user safety and comfort by identifying irregularities that can impact mobility. This study aims to develop a multi-purpose application that, using sensor data from smartphones, creates a comprehensive data layer about road conditions. By using threshold-based methods to analyze accelerometer data, coupled with a dynamic rolling window approach that adjusts based on speed, this system offers robust detection of road anomalies. The method has been validated against ground truth data, demonstrating its potential to provide reliable information. The resulting data layer can be integrated with applications like Google Maps, allowing users to choose routes based on real-time road condition information. This is particularly beneficial for users with specific mobility needs.

Pervasive and mobile computing can play a crucial role in the prevention, detection and management of natural and human-caused disasters. In this context, the Internet of Vehicles (IoV) is particularly noteworthy due to its recent technological advancements and increasing prevalence. In fact, IoV can be leveraged to improve various applications, including those aimed at reducing the millions of fatalities that occur every year. The effectiveness of these applications often relies on the rapid dissemination of emergency messages through positionbased forwarding protocols, which can unfortunately be vulnerable to adversarial attacks. Without loss of generality, we focus on the specific case study of road safety to provide a realistic example and discuss two potential attacks based on fake position claims that malicious nodes could easily execute to compromise the performance of the position-based forwarding protocol. We also propose and analyze a validation system based on machine learning (ML) techniques designed to detect malicious nodes, discard false information, and protect against these attacks.

The non-consensual spread of intimate images and videos is a problematic phenomenon exacerbated by the rise of unmoderated instant messaging platforms like Telegram, where anonymity guarantees meet a loose regulatory framework. The popularity of Telegram groups, channels, and bots where intimate material is shared, along with the severe health consequences associated with this abuse, requires urgent responses and solutions. In this context, we discuss a tool aimed at characterizing the intricate network of Telegram online spaces related to non-consensual pornography and to locate (even slightly edited) copies of images shared across channels and groups. We also discuss the ethical issues associated with our proposal.

This short paper introduces a novel approach to mobile phone cases, addressing the demand for both protection and added functionality. Traditional cases often add bulk to phones without providing additional benefits. We propose smart cases that utilize unused space to integrate innovative features, focusing initially on wireless charging. By incorporating wireless charging capabilities, we offer a cost-effective solution for users seeking to enhance their devices without upgrading. Additionally, we explore the integration of various innovative ideas, resulting in two distinct variants: Variant 1, a wired solution for phones lacking wireless charging, and Variant 2, which leverages reverse charging technology for phones already equipped with wireless charging capabilities. Our research also delves into achieving wireless data transmission within these cases, employing generic modules to host FTP servers and assessing their real-time performance. This study outlines a framework for developing smart cases that not only protect but also enhance the functionality of mobile phones.

The digital and mobile revolutions have changed the way people live their sexuality.Sexting, the practice of sending or receiving any sexually explicit content through mobile devices, has gained popularity, especially amongst teenagers and young adults, bringing several concerns, such as the uncontrolled spread of personal nude or semi-nude media without the owner's consent.Moreover, messaging applications generally used to communicate (and practice sexting) are not safe enough, e.g., they permit to send and forward any received content to anyone else.In this scenario, we believe that, beside education, technological solutions should be devised to avoid or limit sexting abuse.To this aim, we have developed SafeSext, a proof of concept messaging system, which also implements an image forwarding control feature.Through it, we have analyzed possible solutions, as well as their limits, in supporting a safer messaging environment where users retain some form of control over the forwarding of their self-generated sensitive contents.

Reliable communications play a pivotal role in ensuring an efficient response and the coordination of recovery and rescue efforts. However, conventional communication methods may not always be accessible or dependable in such situations. In such circumstances, constellations of Low Earth Orbit (LEO) satellites can provide high bandwidth capabilities with relatively low latency, making them well-suited for supporting on-theground disaster management teams. Satellites can either complement or replace terrestrial telecommunication infrastructures. In this context, reliance on the recently defined QUIC protocol allows for a seamless transition from terrestrial to satellite communication as needed. Therefore, we investigate the possible use of a dual-stack node architecture along with the employment of the QUIC transport protocol for emergency communications, assuming that the backhaul link used to transfer users' applications data may need to be changed (seamlessly). We conduct an extensive emulation study, evaluating the performance of QUIC under varying queuing policies and Congestion Control Algorithm (CCA) behaviour, providing practical insights and recommendations to enhance the protocol's efficiency and robustness. The key aspects and configurations of QUIC protocol stack are identified, presenting optimal communication configurations leveraging CoDel and BBR CCA.

Low Earth Orbit (LEO) satellites offer a promising solution for ubiquitous connectivity and can be utilized in 5G Non-Terrestrial Networks (NTNs) for applications like IoT, autonomous driving, and rural communication. They are particularly suited for smart mobility in urban environments, where fast data transmission and real-time control of vehicles and infrastructure are crucial. In this study, we compare TCP protocols for satellite communication in smart mobility scenarios and propose a solution that uses a limited buffer size to reduce per-packet delays without affecting the throughput.

The DEDICAT-6G project emphasizes dynamic re-sourcing, connectivity, flexibility, and trustworthiness for emerging human-centric services. In response, our Vulnerable Road User safety solution targets the need for heightened awareness in urban settings, leveraging edge computing, communication protocols, and efficient resource management to reduce intersection-related accidents. Our architecture involves Road Side Units, On-Board Units, and Vulnerable Road Users, with a Collision Detection Edge Application for real-time data analysis, incorporating a Monitoring System that facilitates comprehensive performance evaluation. A simulation considering limited sight scenarios at intersections yielded promising early results, indicating the efficacy of our approach. Future endeavors encompass real-world implementation, advanced algorithm integration, resource optimization, and environmental impact assessment, all contributing to advancing secure and adaptive communication systems.

Action video-games (AVGs) could improve reading efficiency, enhancing not only visual attention but also phonological processing. Here we tested the AVG effects upon three consolidated language-based predictors of reading development in a sample of 79 pre-readers at-risk and 41 non-at-risk for developmental dyslexia. At-risk children were impaired in either phonemic awareness (i.e., phoneme discrimination task), phonological working memory (i.e., pseudoword repetition task) or rapid automatized naming (i.e., RAN of colours task). At-risk children were assigned to different groups by using an unequal allocation randomization: (1) AVG (n = 43), (2) Serious Non-Action Video Game (n = 11), (3) treatment-as-usual (i.e., speech therapy, n = 11), and (4) waiting list (n = 14). Pre- and post-training comparisons show that only phonemic awareness has a significantly higher improvement in the AVG group compared to the waiting list, the non-AVG, and the treatment-as-usual groups, as well as the combined active groups (n = 22). This cross-modal plastic change: (i) leads to a recovery in phonemic awareness when compared to the not-at-risk pre-readers; (ii) is present in more than 80% of AVG at-risk pre-readers, and; (iii) is maintained at a 6-months follow-up. The present findings indicate that this specific multisensory attentional training positively affects how phonemic awareness develops in pre-readers at risk for developmental dyslexia, paving the way for innovative prevention programs.

The convergence of vehicular communications, 5th generation mobile network (5G) technology, and edge computing marks a paradigm shift in intelligent transportation. Vehicular communication systems, including Vehicle-to-Vehicle and Vehicle-to-Infrastructure, are integral to Intelligent Transportation Systems. The advent of 5G enhances connectivity, while edge computing brings computational processes closer to data sources. This synergy holds the potential to revolutionize transportation efficiency and safety. This research investigates vehicular communication and edge computing dynamics within a 5G network, considering varying distances between On Board Units and Roadside Units. Energy consumption patterns and CPU load at the RSU are analyzed through meticulous real-world experiments and simulations. Our results show stable energy consumption at shorter distances, with fluctuations increasing at greater ranges. CPU load correlates with communication distance, highlighting the need for adaptive algorithms. While experiments exhibit higher variability, our simulations validate these findings, emphasizing the importance of considering transmission range in vehicular communication network design.

The diffusion of Internet-enabled devices (e.g., smartphones, game consoles, virtual reality (VR) headset, etc.) among adolescents and children has raised several concerns about users' safety, as well as about their awareness on potential online dangers. Besides the numerous digital education initiatives, we believe that learning by facing real-life situations would be more effective in understanding safe and correct ways to engage with others online. In this context, we propose Safe Digital Teens, an application composed of different scenarios inspired by real-life situations through which users can learn to face potentially harmful circumstances in a virtual and protected environment. We also present and discuss the results of a preliminary user study.

Online gaming has seen a significant surge in popularity, becoming a dominant form of entertainment worldwide. This growth has necessitated the evolution of game servers from centralized to distributed models, leading to the emergence of distributed game engines. These engines allow for the distribution of game engine modules (GEMs) across multiple servers, improving scalability and performance. However, this distribution presents a new challenge: the game engine module placement problem. This problem involves strategically placing GEMs to maximize the number of accepted placement requests while minimizing the delay experienced by players, a critical factor in enhancing the gaming experience. The problem can be formulated as an Integer Linear Programming (ILP) model, which provides an optimal solution but suffers from high computational complexity, making it impractical for real-world applications. To address this challenge, this paper introduces two novel heuristic algorithms, MAP-MIND and MAP-MIND*. The MAP-MIND algorithm demonstrates superior performance, achieving near-optimal delay and more than 92% GEM request acceptance in the worst heterogeneous scenarios. The MAP-MIND* algorithm, while slightly under-performing MAP-MIND in terms of delay, proves to be significantly faster, making it a viable alternative for real-world applications with equal GEM request acceptance. The trade-off between the two algorithms offers a flexible approach to GEM placement, balancing performance and computational efficiency.

Cities have been developed to support cars rather than people. This has led to a decrease in people's ability to move, live and interact with their urban surroundings, thus affecting the quality-of-life. Obviously, this applies to all of us, especially to people suffering from impairments. Surprisingly, the lack of information is one of the main obstacles to the construction of services that could bridge the gap between people living in urban areas and their environment. Take Google Maps as an example; one can request a route between any two destinations and will surely be provided with the shortest path, whether traveling by car, public transportation, or on foot. However, there are no pathways or information available to help visually impaired people. In response to the above issue, in this paper, we discuss how the widespread presence of sensor-equipped smartphones can be harnessed to create innovative services capable of improving factors such as interaction with the environment, social inclusion, and quality of life.

The United Nations defined 17 Sustainable Development Goals (SDGs) to foster equitable, healthy, inclusive and safe communities. Clearly, they involve even social networks and, in particular, the sexuality expressed through them. For instance, consider sexting, the practice of sharing self-generated explicit content through mobile devices. Besides its popularity, this phenomenon carries several concerns, such as the possible damages caused by the spread of personal nude or semi-nude images without the owner's consent. Unfortunately, messaging applications generally used to practice sexting are not safe enough as they permit to share any received content with anyone else. Aimed at preventing sexting-related adverse consequences for the wellness of people and creating safer, gender-equal and inclusive online communities, we discuss possible technological approaches to contrast the non-consensual spread of private self-generated content and, in particular, we analyse the impact of employing decentralised architectures in this context.

The Internet of Drones represents an emerging framework with a plethora of applications in the context of Beyond-5G networks. Drone technology uses are spreading from commercial, industrial up to military applications. Drones, a.k.a. Unmanned Aerial Vehicles (UAVs), are largely adopted in all those fields where men cannot reach or are unable to perform in a timely and efficient manner. Communications among UAVs are important to allow task coordination and network organization. However, as a drawback, UAVs are strongly affected by energy consumption that limits their flight and task accomplishment. In this paper, we address the energy consumption issue in UAV swarms and present a novel routing approach, namely ENSING, that aims to save energy consumption. Differently from previous approaches that simply reduce the number of control packets to save UAV battery level, ENSING approach selects the next-hop UAV forwarder according to energy constraints. In this way, only eligible UAVs with acceptable energy requirements can be selected in the packet forwarding, thus avoiding the involvement of those UAVs with limited battery level. Compared to other routing techniques, ENSING exhibits better performance in terms of packet delivery rate, throughput and latency.

Content moderation systems are crucial in Online Social Networks (OSNs). Indeed, their role is to keep platforms and their users safe from malicious activities. However, there is an emerging consensus that such systems are unfair to fragile users and minorities. Furthermore, content moderation systems are difficult to personalize and lack effective communication between users and platforms. In this context, we propose an enhancement of the current framework of content moderation, integrating Large Language Models (LLMs) in the enforcing pipeline.

Today, billions of small devices that can sense things are connected, creating the Internet of Things (IoT). This major technological step has led to ideas like smart cities, smart factories, and smart countries. One important use of this technology is pervasive sensing, which could benefit from a network that covers a wide area but does not use much power. This paper looks closely at the advantages and disadvantages of using LoRa—a network technology that can reach long distances with limited energy use—in situations like this. To this aim, we have created a holistic solution to manage the considered network enabling synchronization, routing, and reliability. In particular, we have even developed an adaptive spreading factor mechanism, simple and effective in allowing the network to cope better when the connection is not very good.