Auto-Encoder Learning-Based UAV Communications for Livestock Management
Open Access
- 25 September 2022
- Vol. 6 (10), 276
- https://doi.org/10.3390/drones6100276
Abstract
The advancement in computing and telecommunication has broadened the applications of drones beyond military surveillance to other fields, such as agriculture. Livestock farming using unmanned aerial vehicle (UAV) systems requires surveillance and monitoring of animals on relatively large farmland. A reliable communication system between UAVs and the ground control station (GCS) is necessary to achieve this. This paper describes learning-based communication strategies and techniques that enable interaction and data exchange between UAVs and a GCS. We propose a deep auto-encoder UAV design framework for end-to-end communications. Simulation results show that the auto-encoder learns joint transmitter (UAV) and receiver (GCS) mapping functions for various communication strategies, such as QPSK, 8PSK, 16PSK and 16QAM, without prior knowledge.Keywords
Funding Information
- Deputyship for Research and Innovation, Ministry of Educa- 239 tion in Saudi Arabia (FP-A-201-2-1)
This publication has 25 references indexed in Scilit:
- Use of Unmanned Aerial Vehicles for Livestock Monitoring based on Streaming K-Means ClusteringIFAC-PapersOnLine, 2019
- An Integrated Precision Farming Application Based on 5G, UAV and Deep Learning TechnologiesPublished by Springer Science and Business Media LLC ,2019
- Research Challenges and Opportunities of UAV Millimeter-Wave CommunicationsIEEE Wireless Communications, 2019
- Detection of Cattle Using Drones and Convolutional Neural NetworksSensors, 2018
- An Introduction to Deep Learning for the Physical LayerIEEE Transactions on Cognitive Communications and Networking, 2017
- Visual Localisation and Individual Identification of Holstein Friesian Cattle via Deep LearningPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Agriculture drones: A modern breakthrough in precision agricultureJournal of Statistics and Management Systems, 2017
- Use of an Unmanned Aerial Vehicle−Mounted Video Camera to Assess Feeding Behavior of Raramuri Criollo CowsRangeland Ecology & Management, 2016
- Wireless communications with unmanned aerial vehicles: opportunities and challengesIEEE Communications Magazine, 2016
- An Accurate Modulation Recognition Method of QPSK SignalMathematical Problems in Engineering, 2015