Crowd Detection System Using Blimp Drones as an Effort to Mitigate the Spread of Covid-19 Based on Internet of Things

Mashoedah Mashoedah, Department of Electronics and Informatics Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
Oktaf Agni Dhewa, Department of Electronics and Informatics Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
Zulhakim Seftiyana Roviyan, Department of Electronics and Informatics Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
Dheni Leo, Department of Electrical Engineering Education , Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
Silvia Larasatul Masyitoh, Department of Electronics and Informatics Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia

 10.21831/elinvo.v6i2.43873

Abstract


The application of health protocols is a regulation that is applied to prevent the spread of Covid-19. Public awareness of the implementation of health protocols is still lacking. This study aims to determine the performance of the detection system using the Blimp Drone as an effort to mitigate the spread of Covid-19 based on the Internet of Things. The method used in system development consists of literature review, needs analysis, design, manufacture, and testing. This system uses the Blimp Drone as a vehicle to carry out flight missions. Raspberry pi camera as a component for distance detection in crowds and mask detection, and Flir Lepton 2.5 as a component for temperature detection. In addition, thealso used raspberry pi 4 is as a component for image processing of the distance detection system for crowd, mask, and temperature detection. The results of the tests carried out are: (1) the results of the analysis of the lifting power of the Blimp Drone  using pure helium and a diameter of 0.91m capable of lifting a load of 0.45kg (2) the system can detect the distance of each person in the crowd (3) the system can detect everyone who using a mask and not wearing a mask (4) the system can detect the temperature of each person using image processing (5) an audio warning sounds when a person who is not wearing a mask is detected and the distance between 2 people in a crowd of less than 1 meter is detected (6) the advantages of this tool ie can work autonomous  in flight missions to detect the distance the crowd, masks, and temperature, as well as integrated with system the Internet of Things so that data the results capturing can be accessed in real time for further action by the authorities.

Keywords


Covid-19, Blimp Drone, Detection, Internet of Things

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DOI: https://doi.org/10.21831/elinvo.v6i2.43873

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