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Real-Time Human Motion Tracking by Tello EDU Drone
Human movement tracking is useful in a variety of areas, such as search-and-rescue activities. CCTV and IP cameras are popular as front-end sensors for tracking human motion; however, they are stationary and have limited applicability in hard-to-reach places, such as those where disasters have occur...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860987/ https://www.ncbi.nlm.nih.gov/pubmed/36679699 http://dx.doi.org/10.3390/s23020897 |
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author | Boonsongsrikul, Anuparp Eamsaard, Jirapon |
author_facet | Boonsongsrikul, Anuparp Eamsaard, Jirapon |
author_sort | Boonsongsrikul, Anuparp |
collection | PubMed |
description | Human movement tracking is useful in a variety of areas, such as search-and-rescue activities. CCTV and IP cameras are popular as front-end sensors for tracking human motion; however, they are stationary and have limited applicability in hard-to-reach places, such as those where disasters have occurred. Using a drone to discover a person is challenging and requires an innovative approach. In this paper, we aim to present the design and implementation of a human motion tracking method using a Tello EDU drone. The design methodology is carried out in four steps: (1) control panel design; (2) human motion tracking algorithm; (3) notification systems; and (4) communication and distance extension. Intensive experimental results show that the drone implemented by the proposed algorithm performs well in tracking a human at a distance of 2–10 m moving at a speed of 2 m/s. In an experimental field of the size [Formula: see text] , the drone tracked human motion throughout a whole day, with the best tracking results observed in the morning. The drone was controlled from a laptop using a Wi-Fi router with a maximum horizontal tracking distance of 84.30 m and maximum vertical distance of 13.40 m. The experiment showed an accuracy rate for human movement detection between 96.67 and 100%. |
format | Online Article Text |
id | pubmed-9860987 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98609872023-01-22 Real-Time Human Motion Tracking by Tello EDU Drone Boonsongsrikul, Anuparp Eamsaard, Jirapon Sensors (Basel) Article Human movement tracking is useful in a variety of areas, such as search-and-rescue activities. CCTV and IP cameras are popular as front-end sensors for tracking human motion; however, they are stationary and have limited applicability in hard-to-reach places, such as those where disasters have occurred. Using a drone to discover a person is challenging and requires an innovative approach. In this paper, we aim to present the design and implementation of a human motion tracking method using a Tello EDU drone. The design methodology is carried out in four steps: (1) control panel design; (2) human motion tracking algorithm; (3) notification systems; and (4) communication and distance extension. Intensive experimental results show that the drone implemented by the proposed algorithm performs well in tracking a human at a distance of 2–10 m moving at a speed of 2 m/s. In an experimental field of the size [Formula: see text] , the drone tracked human motion throughout a whole day, with the best tracking results observed in the morning. The drone was controlled from a laptop using a Wi-Fi router with a maximum horizontal tracking distance of 84.30 m and maximum vertical distance of 13.40 m. The experiment showed an accuracy rate for human movement detection between 96.67 and 100%. MDPI 2023-01-12 /pmc/articles/PMC9860987/ /pubmed/36679699 http://dx.doi.org/10.3390/s23020897 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Boonsongsrikul, Anuparp Eamsaard, Jirapon Real-Time Human Motion Tracking by Tello EDU Drone |
title | Real-Time Human Motion Tracking by Tello EDU Drone |
title_full | Real-Time Human Motion Tracking by Tello EDU Drone |
title_fullStr | Real-Time Human Motion Tracking by Tello EDU Drone |
title_full_unstemmed | Real-Time Human Motion Tracking by Tello EDU Drone |
title_short | Real-Time Human Motion Tracking by Tello EDU Drone |
title_sort | real-time human motion tracking by tello edu drone |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860987/ https://www.ncbi.nlm.nih.gov/pubmed/36679699 http://dx.doi.org/10.3390/s23020897 |
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