A knowledge-based method for generating summaries of spatial movement in geographic areas

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

‘This square is our home!’: the organisation of urban space in the spanish 15M movement

Why should a progressive planner/urbanist pay attention to the Spanish 15M movement? From a disciplinary standpoint, its most complex and interesting aspect, which could hypothetically be transferred to other contexts (as in fact happened in the Occupy Wall Street and Occupy London movements), is its 'spatiality'. This article analyses the spatial practices of the so called #spanishrevolution, one of the 2011 social movements that showed the possibility for a new collective appropriation and self-management (autogestion) of urban public space. Although the political goals of the movement were vague at the time of its inception, the practices and spatial imaginaries deployed by it have become consolidated and proven to be yet another of its more successful facets in promoting the spreading and organisation of the protest, making it a phenomenon that calls for reflection on the part of urban thinkers and planners.

New PV self-orientating roof based on a balanced movement

New PV self-orientating roof based on a balanced movement

Modelling Human Displacement through Movement Surfaces.

This paper introduces a new approach for predicting people displacement by means of movementsurfaces. These surfaces can allow the simulation of a person?s movement through the use of semanticmovement concepts such as those making up the environment, the people who are moving, eventsthat describe a human activity, and time of occurrences. In order to represent this movement we havetransformed the trajectory of a person or group of persons into a raindrop path over a surface. As araindrop flows over a surface looking for the maximum slopes, people flow over the landscapelooking for the maximum utility. The movement surfaces are the response to a chained succession of events describing the way a person moves from one destination to another passing through the mostaffine trajectory to his interest. The three construction phases of this modelling approach (exploration,reasoning and prediction) are presented in this paper. The model was implemented in Protégé and aJava application was developed to generate the movement surface based on a recreational scenario.The results had shown the opportunity to apply our approach to optimise the accessibility of recreational areas according to the preferences of the users of that location.

Development of a human movement monitoring system based on wearable devices

It is essential to remotely and continuously monitor the movements of individuals in many social areas, for example, taking care of aging people, physical therapy, athletic training etc. Many methods have been used, such as video record, motion analysis or sensor-based methods. Due to the limitations in remote communication, power consumption, portability and so on, most of them are not able to fulfill the requirements. The development of wearable technology and cloud computing provides a new efficient way to achieve this goal. This paper presents an intelligent human movement monitoring system based on a smartwatch, an Android smartphone and a distributed data management engine. This system includes advantages of wide adaptability, remote and long-term monitoring capacity, high portability and flexibility. The structure of the system and its principle are introduced. Four experiments are designed to prove the feasibility of the system. The results of the experiments demonstrate the system is able to detect different actions of individuals with adequate accuracy.