2021
V. Moysiadis; P. Sarigiannidis; V. Vitsas; A. Khelifi
Smart Farming in Europe Journal Article
In: Computer Science Review, vol. 39, pp. 100345, 2021.
Περίληψη | BibTeX | Ετικέτες: Μεγάλα Δεδομένα και Ευφυείς Εφαρμογές στο Διαδίκτυο των Πραγμάτων, Cloud Computing, Image Processing, machine learning, smart farming, Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), Wireless Sensor Networks (WSNs) | Σύνδεσμοι:
@article{Moysiadis2021,
title = {Smart Farming in Europe},
author = { V. Moysiadis and P. Sarigiannidis and V. Vitsas and A. Khelifi},
url = {https://www.researchgate.net/publication/346716261_Smart_Farming_in_Europe},
doi = {10.1016/j.cosrev.2020.100345},
year = {2021},
date = {2021-02-01},
journal = {Computer Science Review},
volume = {39},
pages = {100345},
publisher = {Elsevier BV},
abstract = {Smart Farming is the new term in the agriculture sector, aiming to transform the traditional techniques to innovative solutions based on Information Communication Technologies (ICT). Concretely, technologies like Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), Image Processing, Machine Learning, Big Data, Cloud Computing, and Wireless Sensor Networks (WSNs), are expected to bring significant changes in this area. Expected benefits are the increase in production, the decrease in cost by reducing the inputs needed such as fuel, fertilizer and pesticides, the reduction in labor efforts, and finally improvement in the quality of the final products. Such innovative methods are crucial in recent days, due to the exponential increase of the global population, the importance of producing healthier products grown with as much fewer pesticides, where public opinion of European citizens is sensitized. Moreover, due to the globalization of the world economy, European countries face the low cost of production of other low-income countries. In this vein, Europe tries to evolve its agriculture domain using technology, aiming at the sustainability of its agricultural sector. Although many surveys exist, most of them tackle in a specific scientific area of Smart Farming. An overview of Smart Farming covering all the involved technologies and providing an extensive reference of good practices around Europe is essential. Our expectation from our work is to become a good reference for researchers and help them with their future work. This paper aims to provide a comprehensive reference for European research efforts in Smart Farming and is two-fold. First, we present the research efforts from researchers in Smart Farming, who apply innovative technology trends in various crops around Europe. Second, we provide and analyze the most significant projects in Europe in the area of Smart Farming. © 2021 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.},
keywords = {Big Data, Cloud Computing, Image Processing, machine learning, smart farming, Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), Wireless Sensor Networks (WSNs)},
pubstate = {published},
tppubtype = {article}
}
2020
A. Triantafyllou; P. Sarigiannidis; S. Bibi; F. Vakouftsi; P. Vassilis
Modelling deployment costs of Precision Agriculture Monitoring Systems Conference
2020.
Περίληψη | BibTeX | Ετικέτες: cost model, Precision agriculture costs, smart farming, SWOT analysis, Unmanned Aerial Vehicle (UAVs), Wireless Sensor Networks (WSNs) | Σύνδεσμοι:
@conference{Triantafyllou2020252,
title = {Modelling deployment costs of Precision Agriculture Monitoring Systems},
author = { A. Triantafyllou and P. Sarigiannidis and S. Bibi and F. Vakouftsi and P. Vassilis},
url = {https://www.researchgate.net/publication/344050120_Modelling_deployment_costs_of_Precision_Agriculture_Monitoring_Systems},
doi = {10.1109/DCOSS49796.2020.00048},
year = {2020},
date = {2020-01-01},
journal = {Proceedings - 16th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2020},
pages = {252-259},
abstract = {Unmanned Aerial Vehicles (UAVs) and smart sensors are the tools towards the fifth agricultural revolution. Remote sensing is thriving in agriculture, broadening the horizons of cultivators and farming practitioners. However, adopting such a technological endeavour in a raw production process is a challenging task for farmers. Operation and maintenance of such systems require specific ICT knowledge. There is also a wide variety of software and hardware equipment to choose from that can greatly impact business costs and system performance according to the kind of cultivation. Due to the lack of guidance regarding the employment of precision agriculture monitoring systems, this paper proposes a detailed decision model regarding the requirements and considerations of deploying remote sensing capabilities on a cultivation. Agricultural businesses are in need of guidance when it comes to the adoption of technological advancements especially in the case when a carefully planned operation can produce a significant amount of profits. © 2020 IEEE.},
keywords = {cost model, Precision agriculture costs, smart farming, SWOT analysis, Unmanned Aerial Vehicle (UAVs), Wireless Sensor Networks (WSNs)},
pubstate = {published},
tppubtype = {conference}
}
Διεύθυνση
Internet of Things and Applications Lab
Department of Electrical and Computer Engineering
University of Western Macedonia Campus
ZEP Area, Kozani 50100
Greece
Πληροφορίες Επικοινωνίας
tel: +30 2461 056527
Email: ithaca@uowm.gr