SPSDASJul 3, 2019

Audio-Based Search and Rescue with a Drone: Highlights from the IEEE Signal Processing Cup 2019 Student Competition

arXiv:1907.04655v144 citations
Originality Synthesis-oriented
AI Analysis

This addresses the challenge of finding humans in inaccessible areas using drones, but it is incremental as it builds on existing audio-based localization efforts.

The paper describes the IEEE Signal Processing Cup 2019, which tackled the problem of using drones for audio-based localization in search and rescue scenarios, where participants developed methods to locate people in emergencies, though no specific performance numbers are provided.

Unmanned aerial vehicles (UAV), commonly referred to as drones, have raised increasing interest in recent years. Search and rescue scenarios where humans in emergency situations need to be quickly found in areas difficult to access constitute an important field of application for this technology. While research efforts have mostly focused on developing video-based solutions for this task \cite{lopez2017cvemergency}, UAV-embedded audio-based localization has received relatively less attention. Though, UAVs equipped with a microphone array could be of critical help to localize people in emergency situations, in particular when video sensors are limited by a lack of visual feedback due to bad lighting conditions or obstacles limiting the field of view. This motivated the topic of the 6th edition of the IEEE Signal Processing Cup (SP Cup): a UAV-embedded sound source localization challenge for search and rescue. In this article, we share an overview of the IEEE SP Cup experience including the competition tasks, participating teams, technical approaches and statistics.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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