Bio Informatika Drone

Author


Dafa Rizki Rahmanda Fitrah Hsb(1Mail), Emir Khalil Rangkuti(2), Fathur Rahman Siregar(3), Zaqi Hudzaifah Zailani(4),
(1) Sains dan Teknologi, lmu Komputer, Universitas Islam Negeri Sumatera Utara, Indonesia,
(2) ,
(3) ,
(4) ,

Mail Corresponding Author
Article Analytic
  [File Size: 321KB]  Language: en
Available online: 2025-01-10  |  Published : 2025-01-10
Copyright (c) 2025 Dafa Rizki Rahmanda Fitrah Hsb, Emir Khalil Rangkuti, Fathur Rahman Siregar, Zaqi Hudzaifah Zailani
Article can trace at:

Article Metrics

Abstract Views: 45 times PDF Downloaded: 75 times

Abstract


The rapid advancement of drone technology presents significant potential in various fields, including bioinformatics. This article explores the integration of drone technology in bioinformatics, focusing on environmental monitoring and biological data collection. By enabling efficient sampling and access to hard-to-reach areas, drones enhance the quality and quantity of collected biological data. This integration facilitates comprehensive data analysis, supporting research in ecology, conservation, and biodiversity studies.


Keywords


Drone, Bioinformatics, Environmental Monitoring, Biological Data Collection, UAV Technology.

References


Feng, H., Ge, Y., Ye, G., Wang, J., Zhang, L., & Zhao, J. (2024). UAV Maritime Target Detection Algorithm Based on Improved. Proceedings of the 36th Chinese Control and Decision Conference, CCDC 2024, 54885493. https://doi.org/10.1109/CCDC62350.2024.10588282

Haque, A., Chowdhury, N.-U.-R., & Hassanalian, M. (2023). A Comprehensive Review of Classification and Application of Machine Learning in Drone Technology. https://doi.org/10.20944/preprints202306.1901.v1

Lenick, M., Sidor, E., Dianov, L., Tirpk, F., tefunkov, N., D?ugan, M., Halo, M., Halo, M., Slanina, T., Urban, I., Bany, D., Gre?, A., Roychoudhury, S., Schneir, E. R., & Massnyi, P. (2024). The effect of bee drone brood on the motility and viability of stallion spermatozoaan in vitro study. In Vitro Cellular and Developmental Biology - Animal, 60(6), 596608. https://doi.org/10.1007/s11626-024-00918-y

Liang, Z., Fan, L., Wen, G., & Xu, Z. (2024). Design, Modeling, and Control of a Composite Tilt-Rotor Unmanned Aerial Vehicle. Drones, 8(3). https://doi.org/10.3390/drones8030102

Milano, P. D. I. (2019). School of Industrial and Information Engineering Master of Science in Electrical Engineering Optimal Power Flow for Unbalanced Distribution Network : 1104.

Najihah, F., Zamri, M., Gunawan, T. S., & Kartiwi, M. (2024). Deep Learning Techniques for Advanced Drone Detection Systems : A Comprehensive Review of Techniques , Challenges and Future Directions. 12(4), 818857. https://doi.org/10.52549/ijeei.v12i4.6028

Srivastava, S. K., Seng, K. P., Ang, L. M., Pachas, A. Nahuel A., & Lewis, T. (2022). Drone-Based Environmental Monitoring and Image Processing Approaches for Resource Estimates of Private Native Forest. Sensors, 22(20). https://doi.org/10.3390/s22207872

Vacca, G., & Vecchi, E. (2024). UAV Photogrammetric Surveys for Tree Height Estimation. Drones, 8(3). https://doi.org/10.3390/drones8030106

Venbrux, M., Crauwels, S., & Rediers, H. (2023). Current and emerging trends in techniques for plant pathogen detection. Frontiers in Plant Science, 14(May), 125. https://doi.org/10.3389/fpls.2023.1120968

Wang, E., Sun, J., Liang, Y., Zhou, B., Jiang, F., & Zhu, Y. (2024). Modeling, Guidance, and Robust Cooperative Control of Two Quadrotors Carrying a Y-Shaped-Cable-Suspended Payload. Drones, 8(3). https://doi.org/10.3390/drones8030103


Refbacks

  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.