Baloola, Mohamed Osman and Ibrahim, Fatimah and Mohktar, Mas Sahidayana (2022) Optimization of medication delivery drone with IoT-Guidance Landing system based on direction and intensity of light. Sensors, 22 (11). ISSN 1424-8220, DOI https://doi.org/10.3390/s22114272.
Full text not available from this repository.Abstract
This paper presents an optimization of the medication delivery drone with the Internet of Things (IoT)-Guidance Landing System based on direction and intensity of light. The IoT-GLS was incorporated into the system to assist the drone's operator or autonomous system to select the best landing angles for landing. The landing selection was based on the direction and intensity of the light. The medication delivery drone system was developed using an Arduino Uno microcontroller board, ESP32 DevKitC V4 board, multiple sensors, and IoT mobile apps to optimize face detection. This system can detect and compare real-time light intensity from all directions. The results showed that the IoT-GLS has improved the distance of detection by 192% in a dark environment and exhibited an improvement in face detection distance up to 147 cm in a room with low light intensity. Furthermore, a significant correlation was found between face recognition's detection distance, light source direction, light intensity, and light color (p < 0.05). The findings of an optimal efficiency of facial recognition for medication delivery was achieved due to the ability of the IoT-GLS to select the best angle of landing based on the light direction and intensity.
| Item Type: | Article |
|---|---|
| Funders: | Grant No: PPSI-2020INDUSTRI-03 |
| Uncontrolled Keywords: | IoT; Guidance landing system; Light direction; Light intensity; Drone; Face recognition |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Engineering > Biomedical Engineering Department |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 16 Oct 2023 04:37 |
| Last Modified: | 16 Oct 2023 04:37 |
| URI: | http://eprints.um.edu.my/id/eprint/42129 |
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