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Dynamic Adaptation of LoRaWan Traffic for Real-time Emergency Operations

Modern standards for IoT communications support fast deployment, large coverage in the order of kilometers, and physical layer adaptations to increase link robustness under time-varying propagation and interference conditions. A possible use of such IoT technologies is in case of emergency scenarios where first responders (FRs) arrive after a disastrous event. Indeed, an important challenge for emergency management is the need to (re)establish real-time communication capabilities and to offer integrated decision making facilities based on information gathered by FRs acting on the crisis site. In this paper, we present a system architecture based on LoRaWAN technology for connecting emergency operators in real-time and reliably communicating environmental information, audio streams/messages, and vital signs received from the first responders' sensors. In particular, based on LoRa modulation parameters, we propose an adaptation algorithm which adjusts user's voice messages and the resolution of the data flows to keep alive communications also when link quality is critically low, thus avoiding delay and saturation problems. Opportunistically, audio signals can be processed locally by the first responder's equipment with a speech-to-text conversion, thus significantly reducing traffic requirements. We demonstrate that the adaptation scheme can be performed real-time, even on a per-packet basis. Thanks this innovative system, FRs can communicate from the crisis site in an efficient and cost-effective way.