Work

Determinação de Riscos de Sobrevoo por Visão Computacional

Year: 2025

Type: conference-paper

Abstract: In the 20th century, aviation has proven itself as one of the most importanttechno-social revolutions of modern human history. Now,Unmanned Aerial Systems (UAS) are on the verge of leading thenext techno-social revolution, remodelling several areas and movinga global market that does not stop growing. The establishmentof UAV Traffic Management (UTM) systems is necessary to makethis revolution happen, and one of the main obstacles is the risksinvolved in UAS flight, especially in urban environments. A methodologyto estimate risks on the overflown environment was carriedout by the usage of convolutional neural networks on the imageryof such environments, allowing the definition of safer routes andtheir management on the fly. Development and experimentationprocesses were carried out, with promising results including a convolutionalneural network for pixel-wise domain that was capableof estimate risks from satellite imagery and return overflight risksheat maps.

Source: Anais do Computer on the Beach

DOI: 10.14210/cotb.v16.p160-167

Authors: Rafael Marinho de Andrade, Elcio Hideiti Shiguemori, Rafael Duarte Coelho dos Santos

Institutions: Instituto de Estudios Avanzados, Instituto de Estudos Avançados da Universidade de São Paulo, Instituto Nacional de Pesquisas Espaciais

Language: English

Topic: Air Traffic Management and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4410770592

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