01655nas a2200193   4500000000100000008004100001100001800042700001700060700001700077700001700094700001600111700001900127245010400146856004400250300000900294490000700303520113700310022001401447       2016                            d1 aEsunly Medina1 aDavid López1 aRoc Meseguer1 aSergio Ochoa1 aDolors Royo1 aRodrigo Santos00aMobile Autonomous Sensing Unit (MASU): A Framework That Supports Distributed Pervasive Data Sensing  uhttp://www.mdpi.com/1424-8220/16/7/1062  a10620 v163 aPervasive data sensing is a major issue that transverses various research areas and application domains. It allows identifying people’s behaviour and patterns without overwhelming the monitored persons. Although there are many pervasive data sensing applications, they are typically focused on addressing specific problems in a single application domain, making them difficult to generalize or reuse. On the other hand, the platforms for supporting pervasive data sensing impose restrictions to the devices and operational environments that make them unsuitable for monitoring loosely-coupled or fully distributed work. In order to help address this challenge this paper present a framework that supports distributed pervasive data sensing in a generic way. Developers can use this framework to facilitate the implementations of their applications, thus reducing complexity and effort in such an activity. The framework was evaluated using simulations and also through an empirical test, and the obtained results indicate that it is useful to support such a sensing activity in loosely-coupled or fully distributed work scenarios.  a1424-8220