Altitude-Adaptive and Cost-Effective Object Recognition in an Integrated Smartphone and UAV System

Authors

Ignacio Martinez-Alpiste, Gelayol Golcarenarenji, Qi Wang and Jose Maria Alcaraz-Calero

Conference	2020 European Conference on Networks and Communications (EuCNC)
Track	Vertical Applications and Internet of Things
Core	48% Acceptance Ratio
Location	Dubrovnik
Number of pages	5
Early online date	21st of September
Original language	English

Human Search and Rescue (SAR) tasks are mission-critical and take place in the wild, and thus solutions require timely and accurate human detection on a highly portable platform. This paper proposes a novel lightweight and practical SAR system that meets those demanding requirements by running optimised machine learning in a smartphone, interoperable with Unmanned Aerial Vehicles (UAV) that provides live video feed. In particular, the proposed approach significantly extends a standard machine learning algorithm to achieve adaptive object recognition in response to changing altitudes to accelerate the speed of finding missing people and eliminate redundant computing. Our approach achieved 91.02% of accuracy and real-time speed on a smartphone that hosts the machine learning platform and the new algorithm. This proposed system is highly portable, cost-effective, fast with high accuracy suitable for UAV applications.

DOI:10.1109/EuCNC48522.2020.9200951

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