Abstract
Unmanned Aerial Vehicles (UAVs), or drones, are increasingly used in various fields. A major concern with UAV operation is their limited power capacity which impacts mission planning, operational efficiency, and battery management, presenting significant research and engineering challenges. This paper evaluates the applications of multiple AI algorithms in predicting the energy consumption of low-cost quadcopter drones. One of the primary contributions involves developing four prediction models, including random forest, regression tree, support vector machine, artificial neural network, and adaptive Neuro-Fuzzy Inference System (ANFIS) on an open-source dataset of small quadcopter flights. This paper also performs a comparative study on the performance of the aforementioned algorithms in predicting the energy consumption of a UAV. This research enhances the field not only by leveraging established machine learning techniques but also by adopting and examining ANFIS, which has received limited prior research attention. By introducing and applying ANFIS, this study not only expands the existing knowledge but also offers a unique perspective, potentially paving the way for further research, especially in addressing uncertainty like weather conditions. According to our study, the power consumption of the UAV is notably influenced by the aircraft’s altitude, wind speed, and velocity. The Random Forest model demonstrates superior accuracy in forecasting UAV power consumption compared to other models. We also provide an overview of the ongoing challenges and potential future endeavors.
Original language | English |
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Title of host publication | 2024 IEEE 100th Vehicular Technology Conference, VTC 2024-Fall - Proceedings |
Place of Publication | Washington DC |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 9798331517786 |
ISBN (Print) | 9798331517793 |
DOIs | |
Publication status | Published - 2024 |
Event | IEEE Vehicular Technology Conference, Fall 2024 - Ronald Reagan Building and International Trade Center, Washington D.C., United States Duration: 07 Oct 2024 → 10 Oct 2024 https://events.vtsociety.org/vtc2024-fall/ https://ieeexplore.ieee.org/xpl/conhome/1000784/all-proceedings (Proceedings) https://events.vtsociety.org/vtc2024-fall/wp-content/uploads/sites/41/2024/10/vtc2024fall_final-program-online.pdf (Program) |
Publication series
Name | IEEE Vehicular Technology Conference |
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ISSN (Print) | 1550-2252 |
Conference
Conference | IEEE Vehicular Technology Conference, Fall 2024 |
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Country/Territory | United States |
City | Washington D.C. |
Period | 07/10/24 → 10/10/24 |
Other | The 2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall) will be held 7-10 October 2024 in Washington DC, USA. This semi-annual flagship conference of IEEE Vehicular Technology Society will bring together individuals from academia, government, and industry to discuss and exchange ideas in the fields of wireless, mobile, and vehicular technology. IEEE VTC2024-Fall will feature world-class plenary speakers, tutorials, technical as well as application sessions, and an innovative Industry Track, which will feature panels and presentations with industry leaders sharing their perspectives on the latest technologies. |
Internet address |