Towards Protecting Agriculture from Exogenous and Endogenous Factors: An Holistic Architecture

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• Ιούλιος 1, 2020
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Περίληψη

An holistic architecture that fosters the application of Smart Farming (SF) in the context of agriculture is proposed in this paper. The proposed architecture exploits the benefits of Internet of Things (IoT), by utilizing a) Wireless Sensor Networks (WSN) for real time monitoring and b) Unmanned Aerial Vehicles (UAVs) / flying Ad-hoc Networks (FANETs) for macroscopic monitoring of the field and inspecting the crops using multispectral cameras. The aggregated data coming from the monitoring process feed the cloud infrastructure, where Machine Learning (ML) and Computer Vision (CV) techniques are applied in order to protect plants from exogenous (e.g., pests) and endogenous (e.g., diseases) factors. © 2020 IEEE.

Σύνδεσμοι

• https://www.researchgate.net/publication/346808047_Towards_Protecting_Agricultur[...]
• doi:10.1109/csndsp49049.2020.9249561

BibTeX (Download)

@conference{Kakamoukas2020b,
title = {Towards Protecting Agriculture from Exogenous and Endogenous Factors: An Holistic Architecture},
author = { G. Kakamoukas and P. Sarigiannidis and I. Moscholios},
editor = { Networks 2020 12th International Symposium on Communication Systems and Digital Signal Processing ({CSNDSP})},
url = {https://www.researchgate.net/publication/346808047_Towards_Protecting_Agriculture_from_Exogenous_and_Endogenous_Factors_An_Holistic_Architecture},
doi = {10.1109/csndsp49049.2020.9249561},
year  = {2020},
date = {2020-07-01},
booktitle = {2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)},
journal = {2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2020},
publisher = {IEEE},
abstract = {An holistic architecture that fosters the application of Smart Farming (SF) in the context of agriculture is proposed in this paper. The proposed architecture exploits the benefits of Internet of Things (IoT), by utilizing a) Wireless Sensor Networks (WSN) for real time monitoring and b) Unmanned Aerial Vehicles (UAVs) / flying Ad-hoc Networks (FANETs) for macroscopic monitoring of the field and inspecting the crops using multispectral cameras. The aggregated data coming from the monitoring process feed the cloud infrastructure, where Machine Learning (ML) and Computer Vision (CV) techniques are applied in order to protect plants from exogenous (e.g., pests) and endogenous (e.g., diseases) factors. © 2020 IEEE.},
keywords = {flying ad-hoc networks, plant protection, smart farming, unmanned aerial vehicles, wireless sensor networks},
pubstate = {published},
tppubtype = {conference}
}