Mission-oriented Sensor Networks Research Articles

Human-machine conversations to support multi-agency missions

In domains such as emergency response, environmental monitoring, policing and security, sensor and information networks are deployed to assist human users across multiple agencies to conduct missions at or near the 'front line'. These domains present challenging problems in terms of human-machine collaboration: human users need to task the network to help them achieve mission objectives, while humans (sometimes the same individuals) are also sources of mission-critical information. We propose a natural language-based conversational approach to supporting humanmachine working in mission-oriented sensor networks. We present a model for human-machine and machine-machine interactions in a realistic mission context, and evaluate the model using an existing surveillance mission scenario. The model supports the flow of conversations from full natural language to a form of Controlled Natural Language (CNL) amenable to machine processing and automated reasoning, including high-level information fusion tasks. We introduce a mechanism for presenting the gist of verbose CNL expressions in a more convenient form for human users. We show how the conversational interactions supported by the model include requests for expansions and explanations of machine-processed information.

MARINE

Wireless sensor networks (WSNs) operate in a highly heterogeneous and dynamic scenario. On one hand, there is a wide range of potential applications for WSNs, each one with different features and requirements and defining a different mission for the sensor nodes to accomplish. On the other hand, the execution context regarding the devices, networks and the physical environment around is subject to frequent changes. In order to achieve the best network performance while meeting requirements of different application missions and contexts, it is crucial to endow the WSN with customization and adaptation capabilities. Such capabilities should be preferably provided by a middleware layer that translates application missions to network configuration in a transparent way for the final users and client applications. This middleware should also provide facilities to program the WSN nodes, to access sensor generated data and to promote interoperability among different applications and networks. To tackle these challenges, we propose MARINE (MiddlewAre for Resource and mIssion-oriented sensor NEtworks), a WSN middleware built on REST and microkernel architectural patterns. MARINE tailors the WSN to requirements of each application mission while saving the overall resource consumption in sensor nodes.