Abstract
The goal of this work is to provide (non-specialist) users with the means to seamlessly setup and monitor a Wireless Sensor-Actuator Network (WSN) without writing any code or performing subtle hardware configurations. Towards this goal, we present an architecture that allows the seamless configuration, deployment and management of applications over WSN. We explore the fact that most deployments have a common modus operandi: (a) simple data readers running on the nodes periodically gather and send data to sinks, and; (b) sinks process incoming data and, accordingly, issue actuation commands to the nodes. We argue that, given the knowledge of a platform's capabilities, its sensors and actuators and their respective programming interfaces, it is possible to fully automate the process of configuring, building, and deploying an application over a WSN. Similarly, monitoring and managing the deployment can be vastly simplified by using a middleware that supports user defined tasks that process data from the nodes, divide the WSN into regions, defined by simple boolean predicates over data, and eventually issue actuation commands on regions.

Abstract
The potential of virtual world technologies to improve teaching and learning has been recognized in recent years, creating new possibilities for teaching and learning processes, with virtual environments impacting the achievement of student learning and collaboration. Learning in Metaverses: Co-Existing in Real Virtuality discusses a better way to understand this new learning universe, exploring the possibilities of new social organization through the use of avatars in virtual worlds. Examining platforms such as Web 3D, metaverse, MDV3D, ECODI, hybrid living and sharing spaces, gamification, alternate reality, mingled reality, and augmented reality to evaluate the possibilities for their implementation in education, this reference book will be of use to academics, educators, students, researchers, gamers, and professionals.

Abstract
Software process improvement requires a team composed by highly motivated members, good working capabilities and large experience. This type of team allows the implementation of tools and techniques that help to improve communication, coordination and collaboration and cooperation, thus minimizing failures resulting from the development process. Believing on these principles the 4C model emerged as an improvement of the 3C collaboration model. This model was proposed to analyze the Hybrid Methodology for User Centered Development (HMUCD) used to develop the educational resource Courseware Sere - The Human Being and Natural Resources. The 4 model objective is to analyze and propose improvements to educational software development processes. In this study we describe the 3C collaboration model and its evolution to the 4C model. For this we present the data collection and analysis process as well as the techniques used for data analysis and used on the development of the educational resource - Courseware Sere. The 4C model allowed us to identify improvements to HMUCD by adjusting the current development methods and implementing new methods of User Centered Design.

Abstract
Data centers are large energy consumers and a substantial portion of this power consumption is due to the control of physical parameters, which bring the need of high efficiency environmental control systems. In this work, we describe a hardware sensing platform specifically tailored to collect physical parameters (temperature, pressure, humidity and power consumption) in large data centers. Our system architecture is composed of Smart Objects, the datacenter racks, that cooperate to contribute for the overall goal of finding opportunities to optimize energy consumption and achieving energy-efficient data centers.We also introduce an analysis of the delay to obtain the sensing data from the sensor network. This analysis provides an insight into the time scales supported by our platform, and also allows to study the delay for different data center topologies. Finally, we exemplify some capabilities of the system with a real deployment.

Abstract
This research presents an innovative mobile robotic system designed for active surveillance operations. This mobile robot moves along a rail and is equipped with a monocular camera. Thus, it enhances the surveillance capability when compared to conventional systems (mainly composed by multiple static cameras). In addition, the paper proposes a technique for multi-object tracking called MTMP (Multi-Tracking of Motion Profiles). The MTMP resorts to a formulation based on the Kalman filter and tracks several moving objects using motion profiles. A motion profile is characterized by the dominant flow vector and is computed using the optical flow signature with removal of outliers. A similarity measure based on the Mahalanobis distance is used by the MTMP for associating the moving objects over frames. The experiments conducted in realistic environments have proved that the static perception mode of the proposed robot is able to detect and track multiple moving objects in a short period of time and without using specialized computers. In addition, the MTMP exhibits a good computational performance since it takes less than 5 milliseconds to compute. Therefore, results show that the estimation of motion profiles is suitable for analyzing motion on image sequences.

Abstract
Media content recommendations for a mobile user based on his changing contextual preferences, otherwise called context-aware media recommendations, constitute a very important challenge. Context-aware media recommendation systems take context information such as user preferences, activities, time, location, device, and network capabilities as inputs for media recommendations, whereas the traditional recommendation systems use only user preferences in the form of ratings to deliver media recommendations. This paper presents a generic high-level architecture of context-aware recommendations, discussing its key techniques and solutions, which are based on context acquisition, recognition, and representations, using MPEG-21 and ontology model, and a contextual user profiling process, as well as MPEG-7 for media description model and media presentation adaptation.