{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T05:07:04Z","timestamp":1781586424897,"version":"3.54.5"},"reference-count":32,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,6,3]],"date-time":"2022-06-03T00:00:00Z","timestamp":1654214400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2019s 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\u2019s detection distance, light source direction, light intensity, and light color (p &lt; 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.<\/jats:p>","DOI":"10.3390\/s22114272","type":"journal-article","created":{"date-parts":[[2022,6,3]],"date-time":"2022-06-03T10:33:01Z","timestamp":1654252381000},"page":"4272","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Optimization of Medication Delivery Drone with IoT-Guidance Landing System Based on Direction and Intensity of Light"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9382-218X","authenticated-orcid":false,"given":"Mohamed Osman","family":"Baloola","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia"},{"name":"Centre for Innovation in Medical Engineering (CIME), Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia"},{"name":"College of Engineering and IT, Ajman University, Ajman P.O. Box 346, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1804-4362","authenticated-orcid":false,"given":"Fatimah","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia"},{"name":"Centre for Innovation in Medical Engineering (CIME), Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia"},{"name":"Centre for Printable Electronics, Universiti Malaya, Kuala Lumpur 50603, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7859-4396","authenticated-orcid":false,"given":"Mas S.","family":"Mohktar","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia"},{"name":"Centre for Innovation in Medical Engineering (CIME), Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"48572","DOI":"10.1109\/ACCESS.2019.2909530","article-title":"Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges","volume":"7","author":"Shakhatreh","year":"2019","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.cja.2020.06.006","article-title":"Do drones have a realistic place in a pandemic fight for delivering medical supplies in healthcare systems problems","volume":"34","author":"Euchi","year":"2020","journal-title":"Chin. J. Aeronaut."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Beck, S., Bui, T.T., Davies, A., Courtney, P., Brown, A., Geudens, J., and Royall, P.G. (2020). An Evaluation of the Drone Delivery of Adrenaline Auto-Injectors for Anaphylaxis: Pharmacists\u2019 Perceptions, Acceptance, and Concerns. Drones J., 4.","DOI":"10.3390\/drones4040066"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e12989","DOI":"10.1111\/ijcp.12989","article-title":"Drones in medicine\u2014The rise of the machines","volume":"71","author":"Balasingam","year":"2017","journal-title":"Int. J. Clin. Pract."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"204","DOI":"10.18043\/ncm.80.4.204","article-title":"The Case for Drone-assisted Emergency Response to Cardiac Arrest","volume":"80","author":"Bogle","year":"2019","journal-title":"North Carol. Med. J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e016687","DOI":"10.1161\/JAHA.120.016687","article-title":"Improving Access to Automated External Defibrillators in Rural and Remote Settings: A Drone Delivery Feasibility Study","volume":"9","author":"Cheskes","year":"2020","journal-title":"J. Am. Heart Assoc."},{"key":"ref_7","first-page":"2454","article-title":"Optimizing a Drone Network to Deliver Automated External Defibrillators","volume":"135","author":"Boutilier","year":"2017","journal-title":"J. Am. Heart Assoc. Circ."},{"key":"ref_8","unstructured":"Roca-Riu, M., and Menendez, M. (2019, January 15\u201317). Logistic deliveries with drones: State of the art of practice and research. Proceedings of the 19th Swiss Transport Research Conference (STRC 2019), Ascona, Switzerland."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kortli, Y., Jridi, M., Al Falou, A., and Atri, M. (2020). Face Recognition Systems: A Survey. Sensors, 20.","DOI":"10.3390\/s20020342"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.jvolgeores.2019.01.018","article-title":"Review of drones, photogrammetry and emerging sensor technology for the study of dykes: Best practises and future potential","volume":"373","author":"Dering","year":"2019","journal-title":"J. Volcanol. Geotherm. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1007\/s11277-021-08252-2","article-title":"Automation System Software Assisting Educational Institutes for Attendance, Fee Dues, Report Generation Through Email and Mobile Phone Using Face Recognition","volume":"119","author":"Tamilkodi","year":"2021","journal-title":"Wireless Pers. Commun."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Adjabi, I., Ouahabi, A., Benzaoui, A., and Taleb-Ahmed, A. (2020). Past, Present, and Future of Face Recognition: A Review. Electronics, 9.","DOI":"10.20944\/preprints202007.0479.v1"},{"key":"ref_13","unstructured":"Wang, Z., Wang, G., Huang, B., Xiong, Z., Hong, Q., Wu, H., Yi, P., Jiang, K., Wang, N., and Pei, Y. (2021, September 07). Masked Face Recognition Dataset and Application. Available online: https:\/\/arxiv.org\/abs\/2003.09093."},{"key":"ref_14","first-page":"39","article-title":"Face Recognition on Drones: Issues and Limitations","volume":"4","author":"Tamilarasu","year":"2018","journal-title":"Scope Int. J. Sci. Humanit. Manag. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1186\/s13673-018-0157-2","article-title":"3D face recognition: A survey","volume":"8","author":"Zhou","year":"2018","journal-title":"Hum. Cent. Comput. Inf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Cho, S.W., Baek, N.R., Kim, M.C., Koo, J.H., Kim, J.H., and Park, K.R. (2018). Face Detection in Nighttime Images Using Visible-Light Camera Sensors with Two-Step Faster Region-Based Convolutional Neural Network. Sensors, 18.","DOI":"10.3390\/s18092995"},{"key":"ref_17","unstructured":"Shanthi, G., Vidhya, S.S., Vishakha, K., Subiksha, S., Srija, K.K., and Srinee Mamtha, R. (2021). Algorithms for face recognition drones. Mater. Today Proc., in press."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Dudhe, P., Kadam, N., Hushangabade, R., and Deshmukh, M. (2017, January 1\u20132). Internet of Things (IOT): An overview and its applications. Proceedings of the 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), Chennai, India.","DOI":"10.1109\/ICECDS.2017.8389935"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"e50109","DOI":"10.4025\/actascitechnol.v43i1.50109","article-title":"Health management and user protection: An analysis of gamification elements in applications for pregnant women","volume":"43","author":"Monte","year":"2021","journal-title":"Acta Scientiarum. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Aldaej, A., Ahanger, T.A., Atiquzzaman, M., Ullah, I., and Yousufudin, M. (2022). Smart Cybersecurity Framework for IoT-Empowered Drones: Machine Learning Perspective. Sensors, 22.","DOI":"10.3390\/s22072630"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Jorke, P., Falkenberg, R., and Wietfeld, C. (2018, January 9\u201313). Power Consumption Analysis of Nb-IOT and Emtc in Challenging Smart City Environments. Proceedings of the 2018 IEEE Globecom Workshops (GC Wkshps), Abu Dhabi, United Arab Emirates.","DOI":"10.1109\/GLOCOMW.2018.8644481"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Saif, A., Dimyati, K., Noordin, K.A., Shah, N.S.M., Abdullah, Q., and Mukhlif, F. (2020, January 9). Unmanned Aerial Vehicles for Post-Disaster Communication Networks. Proceedings of the 2020 IEEE 10th International Conference on System Engineering and Technology (ICSET), Shah Alam, Malaysia.","DOI":"10.1109\/ICSET51301.2020.9265369"},{"key":"ref_23","unstructured":"GSMA (2021, November 15). 5G, the Internet of Things (IoT) and Wearable Devices. Available online: https:\/\/www.gsma.com\/publicpolicy\/resources\/5g-internet-things-iot-wearable-devices."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"26521","DOI":"10.1109\/ACCESS.2017.2775180","article-title":"Internet of Things for Smart Healthcare: Technologies. Challenges, and Opportunities","volume":"5","author":"Baker","year":"2017","journal-title":"IEEE Access"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lagkas, T., Argyriou, V., Bibi, S., and Sarigiannidis, P. (2018). UAV IoT Framework Views and Challenges: Towards Protecting Drones as \u201cThings\u201d. Sensors, 18.","DOI":"10.3390\/s18114015"},{"key":"ref_26","unstructured":"Alex, G., Varghese, B., Jose, J., and Abraham, A.A. (2021, January 05). Modern Health Care System Using IOT and Android. Available online: http:\/\/www.journal4research.org\/articles\/J4RV2I1027.pdf."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"50024","DOI":"10.1063\/5.0066831","article-title":"Development of in-shoe wearable pressure sensor using an Android application","volume":"2386","author":"Mostfa","year":"2022","journal-title":"AIP Conf. Proc."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Almalki, F.A., and Soufiene, B.O. (2022). Modifying Hata-Davidson Propagation Model for Remote Sensing in Complex Environments Using a Multifactional Drone. Sensors, 22.","DOI":"10.3390\/s22051786"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhou, H., Wang, A., Li, M., Zhao, Y., and Iwahori, Y. (2021, January 19\u201321). Epidemic Prevention System Based on Voice Recognition Combined with Intelligent Recognition of Mask and Helmet. Proceedings of the 2021 3rd International Conference on Video, Signal and Image Processing, Wuhan, China.","DOI":"10.1145\/3503961.3503963"},{"key":"ref_30","unstructured":"Aufranc, J. (2022, March 29). HuskyLens AI Camera & Display Board Is Powered by Kendryte RISC-V Processor (Crowdfunding). CNX Software-Embedded Systems News. Available online: https:\/\/www.cnx-software.com\/2019\/08\/01\/huskylens-ai-camera-display-board-is-powered-by-kendryte-risc-v-processor-crowdfunding\/."},{"key":"ref_31","unstructured":"Canaan (2022, March 29). Kendryte K210. Available online: https:\/\/canaan.io\/product\/kendryteai."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (July, January 26). You Only Look Once: Unified, Real-Time Object Detection. Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.91"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/11\/4272\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:24:17Z","timestamp":1760138657000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/11\/4272"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,3]]},"references-count":32,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["s22114272"],"URL":"https:\/\/doi.org\/10.3390\/s22114272","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,3]]}}}