Towards Adaptive Sensor Data Management for Distributed Fire Evacuation Infrastructure

We introduce a novel strategy for data processing in Wireless Sensor Networks (WSNs) in the case of emergency fire evacuation with stringent delay constraints. Such networks should perform distributed emergency assessment, continuous emergency monitoring, and dynamic selection of optimal evacuation strategies. The obvious complexity of these tasks restricts applying existing WSN optimization solutions. Our approach is based on considering the WSN as a complex adaptive system where a complicated task of multi-agent scheduling is factored into a set of smaller subtasks. In this case, decisions made locally by individual sensors can efficiently converge into desirable information processing patterns. A notable feature of our method is its scalability, which allows the sensornet to operate with sufficient quality of service under heavy information loads. We demonstrate the utility of our approach using different fire evacuation scenarios.

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