Intermittent connectivity is one of the main challenges to the reliability and scalability of the Internet of Things (IoT) deployments, especially in resource-constrained or unstable environments. Reputation mechanisms have been suggested as decentralized mechanisms to enhance cooperation, prevent selfishness, and maintain service delivery in distributed and intermittently connected IoT networks. This paper discusses a systematic literature review of 26 primary studies from 2020 to 2024 found in ACM, IEEE, Scopus, ScienceDirect, and Springer using the PRISMA guidelines for article selection. The review proposes a classification framework designed for intermittently connected IoT systems that incorporates reputation sources, with dissemination techniques, and cooperative decision-making models in a single analytical lens. To our knowledge, this study is the first survey to position network intermittency and cooperation incentives at the center of the analysis, unlike other studies conducted in the wider IoT or blockchain domains. Results indicate that the application of reputation mechanisms generally enhances trust, delivery reliability, and network performance, with about 70% of studies reporting measurable performance improvements. However, more than 20% of studies have no real-world validation, with only theoretical or simulation-based evaluation. Additionally, more than 15% of the studies analyze blockchain-based approaches that offer security and decentralization benefits; however, these often have high computational overhead and little practical validation. Based on this synthesis, the survey identifies nine open research challenges, including experimental validation, methodological standardization, computational efficiency, modular system design, social trust modeling, interoperability, reputation freshness, partition-resilient trust management, and resilience to adaptive attacks.

Mobile applications and Internet of Things (IoT) solutions increasingly rely on efficient integration with cloud and edge infrastructures to deliver real-time services and maintain high-quality user experiences. However, in many urban and rural environments, IoT applications often face intermittent connectivity, which compromises service reliability and availability. To address this challenge, this work proposes a reputation-based cooperative framework designed to operate over intermittent and challenged networks, leveraging the device-edge-cloud continuum. The proposed mechanism integrates Machine Learning techniques to dynamically assign adaptive weights to both technical and behavioural factors, including Battery, Storage, Interaction Score (I_Score), Delivery Quality (Q_Delivery), and Interaction History (Hist). These factors are aggregated into a dynamic reputation score that guides cooperation decisions among IoT-enabled mobile devices, even under intermittent network conditions. The framework was validated through simulations and a real-world pilot using the Wall by Wall tourism application, integrating device-to-device cooperation with cloud-assisted programmability. Results demonstrate a cooperation rate of 80.4%, a node rejection rate of 19.6%, and an average energy consumption of only 2.14% per interaction, achieving minimal overhead and enhanced energy efficiency. The close alignment between simulated and real-world results confirms the robustness and practical viability of the approach.

With the growing adoption of the Internet of Medical Things (IoMT), concerns around security, reliability, and anomaly detection across heterogeneous system layers are increasing. The essence of contemporary anomaly detection lies in Machine Learning (ML), training models on datasets for the desired functionality. Nonetheless, currently available datasets are mostly insufficiently supported with multi-layer analysis, as they usually target a single architectural layer or a narrow attack type. To close this gap, we offer X-IoMT, a publicly available dataset designed to enable the research of anomaly detection in IoMT environments. In the Internet of Things (IoT) architecture, the X-IoMT data embodies anomalies from the perception, network, and application layers. Besides, it incorporates adversarial perturbations by Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) under both L2 and L∞ norms with extra adversarial augmentation: both on detection performance under common attacks and on resilience against adversarially manipulated samples. Thus, X-IoMT could be an important tool for evaluating and benchmarking reliable anomaly detection models in IoMT scenarios with cross-layer attack coverage and extra adversarial augmentation. This paper contributes with the presentation of the dataset, inherently aiming to support the advancement of more reliable and secure IoMT systems.

This study explores the integration of futuristic thinking and soft skills development within educational settings, emphasizing their potential role in equipping students to navigate the complexities of the modern workforce. In this paper, we report our insights captured from both higher education teachers and K-12 students. The findings from two experimental sessions-one involving teachers and the other with K-12 students-demonstrate not only high levels of engagement and satisfaction but also the adaptability and relevance of these methodologies across different age groups and educational stages. These results underscore the effectiveness of integrating futuristic thinking with soft skills training, highlighting their potential to be widely adopted in educational curricula.

The Internet of Medical Things (IoMT) is a technological paradigm that enables continuous health monitoring, yet it also introduces significant security and reliability challenges, as systems are not only exposed to cyberattacks but also to devicelevel anomalies. Modern anomaly detection increasingly relies on machine learning (ML). However, the availability of datasets to train or test ML models remains limited and lacking diversity in anomaly types. This work presents the X-IoMT dataset, a multi-layer anomaly dataset comprising perception, network, and application-layer anomalies, collected from real IoMT devices. Device failures, cyberattacks, and clinical irregularities are examples of anomalies that allow for an extensive evaluation of anomaly detection techniques. ML models were used to analyze the dataset in binary, layer-wise, and multiclass classification tasks. Accuracy, precision, recall, and F1-score were used to assess performance. The findings show the challenge and the realism of the X-IoMT dataset, with more advanced methods capturing its varied anomaly patterns while simpler models found it difficult to handle.

University life is a significant phase in students' journey, full of challenges and potential for personal and academic growth. Social interaction and integration into the educational institution play crucial roles in shaping an enriching experience. It is well known that these experiences can positively/negatively influence students' academic performance and emotional well-being. In today's world, games and social networks have experienced significant diffusion among young people, substantially reconfiguring the way they relate to and connect with the world around them. These technologies have proven to be effective as tools to promote socialization and exploration among users, providing more informal and dynamic interactions while stimulating the exploration of various places and content. Hence, this Paper presents a mobile game, titled UBI Journey, with the purpose of enhancing the university experience of students. The project aims to promote socialization among students, exploring both the resources of the institution, University of Beira Interior, and the characteristics of the city of Covilhã, Portugal. The dissertation presents a detailed analysis of the benefits of UBI Journey, highlighting how social integration and exploration are key elements to enrich the student experience. The work also discusses the practical construction of the game, exploring technical and design aspects, as well as different approaches and tools used for its implementation. In conclusion, the research aims to contribute a gamification-based model that can be applied in universities or other teaching institutions, aiming to improve student integration and socialization.

In rural and remote areas, characterized by limited or inadequate communication infrastructures and difficulty in monitoring residents, often senior citizens, face challenges of information exclusion. For this reason, there is a necessity to develop ubiquitous systems capable of real-time data collection, aiming not only to enhance the understanding of the quality of life of the residents but also to provide timely alerts regarding potential hazards such as fires or the detection of dangerous levels of carbon monoxide, carbon dioxide, and radon gas. This paper presents, RuraLTHINGS, a novel IoT autonomous monitoring system for remote and rural regions, focused on the surveillance of the quality of living and quality of air. The proposal focuses on key parameters, such as temperature, humidity, carbon monoxide/dioxide, and radon gas. Radon is a serious health hazard, and the prolonged risk of exposure is associated with lung cancer and childhood leukemia. The proposed system presents an interoperable IoT sensor network, connected securely and transparently, that enables monitoring of the parameters, empowering the residents and the municipalities to improve their quality of life. The system is prepared to be deployed in a network constraint scenario, and it includes access to multiple communication protocols. This paper presents the system implementation details, communication protocols, and prototype. Moreover, it presents the IoT system validation by evaluating the power usage and latency when the prototype is communicating. For this assessment, we compared the system with Wi-Fi versus LoRa communication.

Massive text visualization is a burgeoning field that addresses the visualization, exploration, and analysis of extensive textual datasets, encompassing various domains such as social media, scientific literature, news articles, and more. This paper overviews recent advances, challenges, and potential solutions in massive text visualization and systematically categorizes these works, focusing on shared characteristics such as objectives, preprocessing techniques, processing approaches, and visualization methods. This comprehensive analysis can better understand the current and emerging trends in massive text visualization.

The increasing adoption of technology in the classroom offers several advantages, but also challenges all stakeholders, including instructors, students and decision makers. E-learning has gained momentum, especially in the last two years with the onset of the pandemic, forcing lectures to migrate to the internet and requiring new methodologies to support knowledge transfer between instructors and students. Thus, to verify the situation of Angola in relation to practices and methodologies related to the teaching of informatics, we search to identify existing practices through the application of a questionnaire to teachers of informatics subjects in secondary schools, colleges, and universities of the country. This study aims to discover the effects of using technology as a support for teaching computer science classes, including software engineering, programming, and computer networks. Therefore, 82 participants were involved in this study answering an online survey. Results shown that, although digital technologies are revolutionizing the world and consequently education, institutions in Angola still face several challenges, such as, lack of laboratories for practical classes, lack of electricity, lack of internet, and lack of computers for students. In addition, the adoption of technologies in the classroom proved ineffective, perhaps because of the absence of determining factors for technological inclusion by the institutions, or even because of the training of teachers in the area, whether weak, inefficient, or incomplete. In this sense, although the use of software in the classroom facilitates the acquisition of knowledge, there are still several barriers to be overcome for this to happen broadly. This study concludes that it is necessary to consider technology as a basic need for the facilitating role it plays in society.

Nowadays, access to healthcare services in rural or remote regions remains a major issue in both developing and developed countries. The advent of mobile health (m-Health) services is becoming a major improvement for patients. The main objective of this paper is the development and Quality of Experience (QoE) evaluation of a mHealth solution for healthcare professionals in remote areas. The system architecture is based on a Service Oriented Architecture (SOA). Android OS was chosen for developing the application, mainly, due to its open source APIs and the vast diversity of covered mobile devices. The system was evaluated and demonstrated in a real pilot in cooperation with a healthcare institution involving 42 patients and 4 healthcare professionals. A total of 294 patients evaluated the solution. Hardware issues, such as network disconnection and energy issues were reported in 4% of all the cases. This system reduced significantly care costs lessen the need for physical contact between patient and physician.

Network architectures based on mobile devices and wireless communications present several constraints (e.g., processor, energy storage, bandwidth, etc.) that affect the overall network performance. Cooperation strategies have been considered as a solution to address these network limitations. In the presence of unstable network infrastructures, mobile nodes cooperate with each other, forwarding data and performing other specific network functionalities. This article proposes a generalized incentive-based cooperation solution for mobile services and applications called MobiCoop. This reputation-based scheme includes an application framework for mobile applications that uses a Web service to handle all the nodes reputation and network permissions. The main goal of MobiCoop is to provide Internet services to mobile devices without network connectivity through cooperation with neighbor devices. The article includes a performance evaluation study of MobiCoop considering both a real scenario (using a prototype) and a simulation-based study. Results show that the proposed approach provides network connectivity independency to users with mobile apps when Internet connectivity is unavailable. Then, it is concluded that MobiCoop improved significantly the overall system performance and the service provided for a given mobile application.

The wide dissemination of Internet around the world changed the way people communicate among them. The evolution of the information and communication technologies (ICT) or artificial intelligence (AI) allowed the creation of new types of services involving electronic devices with huge potential. The emergence of intelligent personal assistants (IPAs) is one of such potential example. Combining the IPA concept with the recent paradigm of Internet of Things (IoT), offers new possibilities and new services to end users, since they could learn more about other entities present in the surrounding environment. This paper proposes a novel mobile gateway solution for a ubiquitous mobile health scenario, in which information gathered from a body sensor network (BSN) is used by an IPA belonging to another person, typically mentioned to as caretaker. The mobile gateway receives real time information related to location, heart rate, and possible falls of the monitored person and acts as a communication channel between the BSN sensors and the IPA platform. Furthermore, the paper presents a performance evaluation study of the proposed mobile IoT-based gateway demonstrating and validating its feasibility.

Health telematics is a growing up issue that is becoming a major improvement on patient lives, especially in elderly, disabled, and chronically ill. In recent years, information and communication technologies improvements, along with mobile Internet, offering anywhere and anytime connectivity, play a key role on modern healthcare solutions. In this context, mobile health (m-Health) delivers healthcare services, overcoming geographical, temporal, and even organizational barriers. M-Health solutions address emerging problems on health services, including, the increasing number of chronic diseases related to lifestyle, high costs of existing national health services, the need to empower patients and families to self-care and handle their own healthcare, and the need to provide direct access to health services, regardless of time and place. Then, this paper presents a comprehensive review of the state of the art on m-Health services and applications. It surveys the most significant research work and presents a deep analysis of the top and novel m-Health services and applications proposed by industry. A discussion considering the European Union and United States approaches addressing the m-Health paradigm and directives already published is also considered. Open and challenging issues on emerging m-Health solutions are proposed for further works.

Elderly people need regular healthcare services and several times are dependent of physicians' personal attendance. This dependence rises several issues to elders, such as the need to travel and mobility support. Mobile Health (m-Health) services and applications offer good healthcare solutions that can be used indoor or in mobility environments. This paper presents an ambient assisted living (AAL) solution for mobile environments. It includes elderly biofeedback monitoring using body sensors for data collection offering support for remote monitoring. The used sensors are attached to the human body (such as the electrocardiogram, blood pressure, and temperature). They collect data providing comfort, mobility, and guaranteeing efficiency and data confidentiality. Periodic collection of patients' data is important to gather more accurate measurements and to avoid common risky situations. The presented proposal monitors elderly people, storing collected data in a personal computer, tablet, or smartphone through Bluetooth. This application allows an analysis of possible health condition warnings based on the input of supporting charts, and real-time bio-signals monitoring.

Mobile health (m-Health) applications delivers healthcare services through mobile applications regardless of time and place. An m-Health application makes use of wireless communications to sustain its health services and often providing a patient-doctor interaction. Therefore, m-Health applications present several challenging issues and constraints, such as, mobile devices battery and storage capacity, broadcast constraints, interferences, disconnections, noises, limited bandwidths, network delays, and of most importance, privacy and confidentiality concerns. This paper proposes a novel and enhanced cryptography solution in a cooperative environment considering a novel and early-proposed cooperation strategy for m-Health Applications. This proposal aims to face the challenges related to privacy and security issues of all forwarded and retrieved data concerning user sensitive information. Furthermore, it presents a performance evaluation of this proposal considering a comparison with an earlier proposed encryption strategy for the same cooperative environment.

Medication errors have been identified as one of the most problematic issues in modern health-care systems. Patients are responsible for most of the intake mistakes. The most common are wrong medications (different that the ones prescribed) and administration of medications out of date, under or over doses due to erratic intakes. This paper presents SapoMed, a mobile health (m-Health) application for medication administration management. In the recent years, with the advent of mobile technologies, m-Health systems are able to provide healthcare anytime and anywhere in a pervasive way. SapoMed is a medication intake diary that tracks and manages all the prescribed medication aiming to prevent medication errors. Through visual, audio, and vibrating alerts, SapoMed keeps users aware of their medication schedule. The application allows users to register medications through the mobile phone camera to capture the barcode available at the medication boxes. It makes use of Web services to consequently retrieve all the medication information and posology. Furthermore, it uses the same Web services to save past intake medication and their intake records. The proposal was evaluated and demonstrated through a solution created for Android OS and it is ready for use.

Mobile Health (m-Health) systems include the use of mobile devices and applications that interact with patients and caretakers. However, mobile devices have several constraints (such as, processor, energy, and storage resource limitations), affecting the quality of service and user experience. This paper proposes a novel cooperation strategy for m-Health services and applications. This contribution addresses two related limitations to m-Health applications with service-oriented architectures, namely the network infrastructure and Internet connectivity dependency. It follows a reputation-based approach as an incentive method for cooperation, which includes a Web service to manage all the network cooperation. It is responsible for verifying the cooperation status of neighbor nodes and to provide relay nodes the required data in order to perform a full data request. A performance evaluation study in a real scenario is presented, using an available m-Health application, called SapoFit. For performance evaluation purposes, an analytical model is also considered in order to compare the obtained experiment results. It is clearly shown that referred dependencies are relevantly decreased, providing mobile nodes without Internet connectivity a free of charge and suitable alternative to access its remotely stored health information. It also improves the service delivery probability while increasing the overall network throughput.

Mobile health (m-Health) includes the use of mobile applications to deliver healthcare services anytime and anywhere. This paradigm benefits with the advent of Web services based systems since they allow health applications available for users with mobility support. This paper presents a novel cooperation strategy for m-Health services and applications. It comprises a reputation-based strategy for Web services oriented architectures that includes a cooperative Web service for managing all the network cooperation and nodes reputation. The cooperation strategy considers two modules for mobile nodes, one for verifying the cooperation status of neighbor nodes and another for classifying the neighbor nodes in function of their reputation. The performance of the proposal is evaluated in a real scenario, using an m-Health application, called SapoFit.

Vehicular delay tolerant networks (VDTNs) were proposed as a novel disruptive network concept based on the delay tolerant networking (DTN) paradigm. VDTN network architecture uses vehicles to relay messages, enabling network connectivity in challenged scenarios. Due to intermittent connectivity, network nodes carry messages in their buffers, relaying them only when a proper contact opportunity occurs. The storage capacity and message retrieving of intermediate nodes directly affects the network performance. Therefore, efficient and robust caching and forwarding mechanisms are needed. This paper proposes a content storage and retrieval solution for VDTN networks. It consists on storage and retrieval control labels, attached to every message of aggregated traffic (data bundles). These labels define cacheable contents, and apply cache-control and forwarding restrictions on data bundles. This solution is fully automated, providing a fast, safe, and reliable data transfer and storage management, while improves the applicability and performance of VDTN networks significantly. The proposed algorithms were evaluated and validated through a VDTN testbed.

In modern organizations, the communication between collaborators is essential to improve productivity. There is a need for mobile collaboration tools that allow efficient collaboration among staff in organization which may be located in different geographical areas and time zones. Mobile and pervasive computing provides easy and convenient access to information, enabling effective collaboration. This paper describes a context and location-aware mobile application, called MP-Collaborator, created to improve and optimize the communication between collaborators in any organization. MP Collaborator draws information from location, user status and Pocket Outlook Calendar to create a user availability profile, which is published to any other user in the network. Based on availability status, the user can be reached using a simple phone call or a message. Through the opportunistic use of available mobile technologies MP-Collaborator provides a simple but critical service - user presence service. The proposed solution is validated both in terms of features and communication through a series of experiments on real devices through Wi-Fi network.