Automated homecare is an emerging application leveraging the increasing number of networked sensors. We present CommonSens, a complex event processing (CEP) system and query language that provide the abstractions of capabilities and locations of interest to facilitate the task of the application programmer through reuse, easier personalisation, and system supported sensor selection. To achieve these goals we have developed three independent models that represent the concepts an application programmer can use: (1) event model, (2) environment model, and (3) sensor model. The sensor capabilities and locations of interest allow us to decouple the event specification from a particular instance, i.e., an installation of sensors in a particular home. CommonSens investigates the particular environment and chooses sensors that provide the correct capabilities and cover the locations of interest. The personalisation is achieved by updating the values in the conditions, the locations of interest and the time specifications in the queries. We describe the proof-of-concept implementation of CommonSens and demonstrate with a use-case the ease of personalising a query in two different environments.
Automated home care uses sensors to report about the well-being of monitored persons. Our complex event processing (CEP) system CommonSens simplifies the work of the application programmers, i.e., those who write the complex queries, by facilitating reuse of queries, sensor instances and environments. We have observed that many automated home care systems focus on detecting alarming behaviour, e.g., falls and heart attacks. However, it is impossible to predict and describe everything that can go wrong. In this paper we define deviation detection in CommonSens, which means that the application programmer only needs to state queries that define correct behaviour. If something happens that does not correspond to the query, this is interpreted as a deviation and a notification or alarm is sent. We believe that this approach further simplifies the work of the application programmer. Deviation detection is implemented in our CommonSens prototype, and we show that our prototype detects deviations as expected by running a set of functionality tests and an experiment based on real-world trace files.
In our project, we design middleware services for emergency and rescue scenarios in sparse Mobile AdHoc Networks (SMANETs). One of these services is a distributed event notification service (DENS) for asynchronous communication. The DENS architecture allows several subscription languages for different kinds of subscriptions. To support complex subscriptions, we use a Data Stream Management System (DSMS) for filtering of the data streams and matching of filtered events and subscriptions. We have designed a simple rescue scenario to investigate the possibilities of using a DSMS together with the DENS middleware layer. In this paper we discuss the design of our implementation and first experimental results of our ongoing work.
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