Real-time Social Distancing Detection Approach Using YOLO and Unmanned Aerial Vehicles

Darwin Merizalde, Paulina Morillo

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

Resumen

The current COVID-19 pandemic has undoubtedly brought new challenges to society and the constant search for solutions to control and reduce its effects. In this sense, the use of technology has become essential to cope with the situation. Thus, this work proposes a real-time social distancing detection system using Deep Learning algorithms and carrying out the monitoring through a UAV. This system consists of two fundamental blocks. The first one consists of convolutional neural network training to detect people using the YOLO object detection system while the second one consists of real-time video acquisition and analysis. Practical applications involves detecting people and calculating the distances between them to determine whether social distancing measurements are being obeyed or not. By increasing surveillance capabilities, authorities and security forces may control and prevent possible outbreaks of massive COVID-19 infections. The experiments were made in three different flight scenarios with altitudes of 15, 30, and 50 m. According to the results, the detection system’s recall reaches values close to 90%, although the highest values were obtained in flights at 30 m high. Regarding the calculation of the distances, in the three scenarios, the average relative error did not exceed 5%. Thus, the video transmission showed a high performance during the experiments. Hence, the system returns reliable results to control compliance with measures such as social distancing.

Idioma originalInglés
Título de la publicación alojadaSmart Technologies, Systems and Applications - 2nd International Conference, SmartTech-IC 2021, Revised Selected Papers
EditoresFabián R. Narváez, Julio Proaño, Paulina Morillo, Diego Vallejo, Daniel González Montoya, Gloria M. Díaz
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas114-127
Número de páginas14
ISBN (versión impresa)9783030991692
DOI
EstadoPublicada - 2022
Evento2nd International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2021 - Quito, Ecuador
Duración: 1 dic. 20213 dic. 2021

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen1532 CCIS
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

Conferencia2nd International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2021
País/TerritorioEcuador
CiudadQuito
Período1/12/213/12/21

Nota bibliográfica

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

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