PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

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• Bademlioglu, A. H., Canbolat, A. S., Yamankaradeniz, N., & Kaynakli, O. (2018). Investigation of parameters affecting Organic Rankine Cycle efficiency by using Taguchi and ANOVA methods. Applied Thermal Engineering, 145(1), 221–228. https://doi.org/10.1016/j.applthermaleng.2018.09.032
  
  Behjati, M., Noh, Y., Alobaidy, H. A. H., Zulkifley, M. A., Nordin, R., & Abdullah, N. F. (2021). LoRa communications as an enabler for internet of drones towards large-scale livestock monitoring in rural farms. Sensors, 21(15), 5044–5071. https://doi.org/10.3390/s21155044
  
  Caruso, M., Boano, C. A., & Romer, K. (2021). Collection of data with drones in precision agriculture: Analytical model and LoRa case study. IEEE Internet of Things Journal, 8(22), 16692–16704. https://doi.org/10.1109/JIOT.2021.3075561
  
  Cattani, A., Chessa, S., Escolar, S., Barba, J., & Lopez, J. C. (2017). An experimental evaluation of the reliability of lora long-range low-power wireless communication. Journal of Sensors and Actuator Networks, 6(2), 7–26. https://doi.org/10.3390/jsan6020007
  
  Davis, R., & Pretesh, J. (2018). Application of Taguchi-based design of experiments for industrial chemical processes. In V. Silva (Ed.), Statistical Approaches With Emphasison Design of Experiments Applied to Chemical Processes (pp. 137-156). IntechOpen. http://dx.doi.org/10.5772/intechopen.69501
  
  Ding, Y., Feng, Y., Lu, W., Zheng, S., Zhao, N., Meng, L., Nallanathan , A., & Yang, X. (2022). Online edge learning offloading and resource management for UAV-assisted MEC secure communications. IEEE Journal of Selected Topics in Signal Processing, 17(1), 54–65. https://doi.org/10.1109/JSTSP.2022.3222910
  
  Edward, P., El-Aasser, M., Ashour, M., & Elshabrawy, T. (2020). Interleaved chirp spreading LoRa as a parallel network to enhance LoRa capacity. IEEE Internet of Things Journal, 8(5), 3864–3874. https://doi.org/10.1109/JIOT.2020.3027100
  
  Faber, M. J., van der Zwaag, K. M., dos Santos, W. G. V., de O Rocha, H. R., Segatto, M. E. V., & Silva, J. A. L. (2020). A theoretical and experimental evaluation on the performance of LoRa technology. IEEE Sensors Journal, 20(16), 9480–9489. 10.1109/JSEN.2020.2987776
  
  Ghazali, M. H. M., Teoh, K., & Rahiman, W. (2021). A systematic review of real-time deployments of UAV-based LoRa communication network. IEEE Access, 9, 124817–124830. https://doi.org/10.1109/ACCESS.2021.3110872
  
  Ginting, E., & Tambunan, M. M. (2018). Selection of optimal factor level from process parameters in palm oil industry. In IOP Conference Series: Materials Science and Engineering (Vol. 288, No. 1, p. 012056). IOP Publishing. https://doi.org/10.1088/1757-899X/288/1/012056
  
  Liang, R., Zhao, L., & Wang, P. (2020). Performance evaluations of LoRa wireless communication in building environments. Sensors, 20(14), 3828–3847. https://doi.org/10.3390/s20143828
  
  Liu, J., Wu, J., & Liu, M. (2020). UAV monitoring and forecasting model in intelligent traffic oriented applications. Computer Communications, 153, 499–506. https://doi.org/10.1016/j.comcom.2020.02.009
  
  Liu, S., Yang, X., & Zhou, Z. (2020). Development of a low-cost UAV-based system for CH4 monitoring over oil fields. Environmental Technology, 42(20), 3154–3163. https://doi.org/10.1080/09593330.2020.1724199
  
  Lu, W., Yandan, M., Feng, Y., Gao, Y., Zhao, N., Wu, Y., & Moose, P. H. (2022). Secure transmission for multi-UAV-assisted mobile dge computing based on reinforcement learning. IEEE Transactions on Network Science and Engineering, 10(3), 1270–1282. https://doi.org/10.1109/TNSE.2022.3185130
  
  Petajajarvi, J., Mikhaylov, K., Pettisalo M., Janhunen, J., & Iinatti, J. (2017). Performance of a low-power wide-area network based on LoRa technology: Doppler, robustness, scalability, and coverage. International Journal of Distributed Sensor Networks, 13(3), 1–16. https://doi.org/10.1177/1550147717699412
  
  Said, M. S. M., Ghani, J. A., Kassim, M. S., Tomadi, S. H., & Haron, C. H. C. (2013). Comparison between Taguchi method and response surface methodology (RSM) in optimizing machining condition. In Proceeding of 1st International Conference on Robust Quality Engineering (pp. 60-68). UTM Razak School.
  
  Sanchez-Iborra, R., Sanchez-Gomez, J., Ballesta-Vinas, J., Maria-Dolores, C., & Skarmeta, A. F. (2018). Performance evaluation of LoRa considering scenario conditions. Sensors, 18(3), 772–791. https://doi.org/10.3390/s18030772
  
  Trasvina-Moreno, C. A., Blasco, R., Marco, A., Casas, R., & Trasvina-Castro, A. (2017). Unmanned aerial vehicle based wireless sensor network for marine coastal environment monitoring. Sensors, 17(3), 460–482. https://doi.org/10.3390/s17030460
  
  Vlasceanu, E., Dima, M., Popescu, D., & Ichim, L. (2019). Sensor and communication considerations in UAV-WSN based system for precision agriculture. In 2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM) (pp. 281-286). IEEE Publishing. https://doi.org/10.1109/CIS-RAM47153.2019.9095823
  
  Wang, S. Y., Chen, Y. R., Chen, T. Y., Chang, C. H., Cheng, Y. H., Hsu, C. C., & Lin, Y. B. (2017). Performance of LoRa-based IoT applications on campus. In 2017 IEEE 86th vehicular technology conference (VTC-Fall) (pp. 1-6). IEEE Publishing. https://doi.org/10.1109/VTCFall.2017.8288154
  
  Wang, Z., Wen, M., Dang, S., Yu, L., & Wang, Y. (2021). Trajectory design and resource allocation for UAV energy minimization in a rotary-wing UAV-enabled WPCN. Alexandria Engineering Journal, 60(1), 1787–1796. https://doi.org/10.1016/j.aej.2020.11.027
  
  Yim, D., Chung, J., Cho, Y., Song, H., Jin, D., Kim, S., Ko, S., Smith, A., & Riegsecker, A. (2018). An experimental LoRa performance evaluation in tree farm. In 2018 IEEE sensors applications Symposium (SAS) (pp. 1-6). IEEE Publishing. https://doi.org/10.1109/SAS.2018.8336764
  
  Zorbas, D., & O'Flynn, B. (2019). A network architecture for high volume data collection in agricultural applications. In 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS) (pp. 578-583). IEEE Publishing. https://doi.org/10.1109/DCOSS.2019.00107