Abstract
This paper provides an overview of some existing methods of Earth remote sensing (ERS) using for agricultural needs. Special emphasis is placed on sensing with the help of UAVs. The paper describes the developed software and hardware complex for an aircraft-type UAV group. The proposed solution significantly increases the operating time and automates the process of monitoring agricultural areas. In addition, legislative restrictions on the use of UAVs are considered.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Collection: Agro-industrial complex of Russia in 2016. Rosinformagrotech, p. 704 (2017)
Uwizera, D., McSharry, P.: Forecasting and monitoring maize production using satellite imagery in Rwanda. In: Technological Innovations in ICT for Agriculture and Rural Development (TIAR), pp. 51–56. IEEE (2017)
Yang, C., Everitt, J.H., Du, Q., Luo, B., Chanussot, J.: Using high-resolution airborne and satellite imagery to assess crop growth and yield variability for precision agriculture. In: Proceedings of the IEEE, vol. 101, No. 3, pp. 582–592 (2013)
Li, W., Yuan, H., Li, W., Song, L.: Prediction of wheat gains with imagery from four-rotor UAV. In: 2nd IEEE International Conference on Computer and Communications, pp. 662–665 (2016)
Perez-Ortiz, M., Gutierrez, P.A., Pena, J.M., Torres-Sanchez, J., Lopez-Granados, F., Hervas-Martınez, C.: Machine learning paradigms for weed mapping via unmanned aerial vehicles. In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI) (2016)
Vehicl, J.N., Prado, J., Lino, M.: Low-cost multi-spectral vegetation classification using an unmanned aerial. In: IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), pp. 336–342 (2017)
Hwang, J., Shin, C., Yoe, H.: Study on an agricultural environment monitoring server system using wireless sensor networks. Sensor 10, 11189–11211 (2010)
Mekala, M.S., Viswanathan, P.: A survey smart agriculture IoT with cloud computing. In: 2017 International conference on Microelectronic Devices, Circuits and Systems (ICMDCS) (2017)
Yonghong, T., Bing, Z., Zeyu, L.: Agricultural greenhouse environment monitoring system based on internet of things. In: 3rd IEEE International Conference on Computer and Communications, pp. 2981–2985 (2017)
Skobelev, P., Budaev, D., Brankovsky, A., Voshuk, G.: Multi-agent tasks scheduling for coordinated actions of unmanned aerial vehicles acting in group. Int. J. Des. Nat. Ecodynamics 13(1), 39–45 (2018)
The Air Code of the Russian Federation. http://docs.cntd.ru/document/9040995. Accessed 5 April 2018
Acknowledgements
The work was supported by the Ministry of Education and Science of the Russian Federation within the contract agreement #14.574.21.0183 - unique identification number RFMEFI57417X0183.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Pantelej, E., Gusev, N., Voshchuk, G., Zhelonkin, A. (2019). Automated Field Monitoring by a Group of Light Aircraft-Type UAVs. In: Abraham, A., Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Third International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’18). IITI'18 2018. Advances in Intelligent Systems and Computing, vol 875. Springer, Cham. https://doi.org/10.1007/978-3-030-01821-4_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-01821-4_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01820-7
Online ISBN: 978-3-030-01821-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)