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Sensing, tracking and contextualizing entities in ubiquitous computing

Information and Communications Technology is increasingly becoming a part of our daily activities. Nowadays, we are able to sense a broad range of entities in the world: from physical entities that comprise the Internet of Things (IoT) to social entities that include people in social networks. We can expect to have a ubiquitous sensing infrastructure in different environments, with varying needs and complexities. While these sensors/entities are mostly static, smart phones are taking center stage as the most widely adopted and ubiquitous computing device. Smart phones have enormous potential for the study of human social networks and human behavior "in vivo," in a natural context outside laboratories. Besides their computing power, smart phones are currently available with an increasing rich set of embedded sensors, such as GPS, accelerometer, microphone, camera, gyroscope and digital compass. Sensing vast areas becomes more feasible when people carrying their portable devices collect data and collaborate among themselves. Systems that enable sensed data in this way are named participatory sensing systems (PSSs). In those networks, the shared data is not limited to sensor readings passively generated by the device, but also includes proactive user observations. A challenge is how to obtain meaningful information from this large amount of data at different scales along the time. Some of the traditional techniques that have been used to process those distinct data sources are information fusion, data mining and machine learning. Notice that the consumers of such information can be, in one extreme, a large set of cooperating or non-cooperating entities, and, in the other, an individual or a "thing", for instance.
 Two important attributes of the sensed data are the location and time where they are collected. Localization and tracking play a key role in ubiquitous computing due to the fact that a wide variety of envisioned applications that collect sensed data rely on their ability to detect, localize and track different entities. This adds a new dimension to this problem when obtaining meaningful information from data associated to different entities. An important problem here is target tracking, which is the capacity of detecting and continuously tracking the state of a target (entity), or a set of targets. This is another fundamental problem in ubiquitous computing.
 Finally, the last dimension considered in this talk is context, which can be defined as any information used to characterize an entity. Context and context-awareness provide a ubiquitous computing environment with the capacity of adapting available services by autonomically deriving the entities' needs from the context they are.
 In this talk, we will discuss each one of these basic building blocks, and discuss how the combination of sensing, tracking and contextualization give us information to make sound decisions in ubiquitous computing that can definitely lead to useful services in areas as diverse as economics, social network, ecology, security, environment and health.