@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 = {2021-01-01},
journal = {Computer Science Review},
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}
}

@article{Kakamoukas2020,
title = {FANETs in agriculture A routing protocol survey},
author = { G.A. Kakamoukas and P.G. Sarigiannidis and A.A. Economides},
url = {https://www.researchgate.net/publication/339904801_FANETs_in_Agriculture_-_A_routing_protocol_survey},
doi = {10.1016/j.iot.2020.100183},
year = {2020},
date = {2020-01-01},
journal = {Internet Things},
abstract = {Breakthrough advances on communication technology, electronics and sensors have led to integrated commercialized products ready to be deployed in several domains. Agriculture is and has always been a domain that adopts state of the art technologies in time, in order to optimize productivity, cost, convenience, and environmental protection. The deployment of Unmanned Aerial Vehicles (UAVs) in agriculture constitutes a recent example. A timely topic in UAV deployment is the transition from a single UAV system to a multi-UAV system. Collaboration and coordination of multiple UAVs can build a system that far exceeds the capabilities of a single UAV. However, one of the most important design problems multi-UAV systems face is choosing the right routing protocol which is prerequisite for the cooperation and collaboration among UAVs. In this study, an extensive review of Flying Ad-hoc network (FANET) routing protocols is performed, where their different strategies and routing techniques are thoroughly described. A classification of UAV deployment in agriculture is conducted resulting in six (6) different applications: Crop Scouting, Crop Surveying and Mapping, Crop Insurance, Cultivation Planning and Management, Application of Chemicals,and Geofencing. Finally, a theoretical analysis is performed that suggests which routing protocol can serve better each agriculture application, depending on the mobility models and the agricultural-specific application requirements.},
keywords = {Flyingadhoc networks (FANETs), Mobility models, Precision agriculture, Routing protocols, Smart farming, Unmanned Aerial Vehicles (UAVs)},
pubstate = {published},
tppubtype = {article}
}

@article{Lytos2020,
title = {Towards smart farming: Systems, frameworks and exploitation of multiple sources},
author = { A. Lytos and T. Lagkas and P. Sarigiannidis and M. Zervakis and G. Livanos},
url = {https://www.researchgate.net/publication/339221382_Towards_Smart_Farming_Systems_Frameworks_and_Exploitation_of_Multiple_Sources},
doi = {10.1016/j.comnet.2020.107147},
year = {2020},
date = {2020-01-01},
journal = {Computer Networks},
abstract = {Agriculture is by its nature a complicated scientific field, related to a wide range of expertise, skills, methods and processes which can be effectively supported by computerized systems. There have been many efforts towards the establishment of an automated agriculture framework, capable to control both the incoming data and the corresponding processes. The recent advances in the Information and Communication Technologies (ICT) domain have the capability to collect, process and analyze data from different sources while materializing the concept of agriculture intelligence. The thriving environment for the implementation of different agriculture systems is justified by a series of technologies that offer the prospect of improving agricultural productivity through the intensive use of data. The concept of big data in agriculture is not exclusively related to big volume, but also on the variety and velocity of the collected data. Big data is a key concept for the future development of agriculture as it offers unprecedented capabilities and it enables various tools and services capable to change its current status. This survey paper covers the state-of-the-art agriculture systems and big data architectures both in research and commercial status in an effort to bridge the knowledge gap between agriculture systems and exploitation of big data. The first part of the paper is devoted to the exploration of the existing agriculture systems, providing the necessary background information for their evolution until they have reached the current status, able to support different platforms and handle multiple sources of information. The second part of the survey is focused on the exploitation of multiple sources of information, providing information for both the nature of the data and the combination of different sources of data in order to explore the full potential of ICT systems in agriculture. © 2020 The Authors},
keywords = {Agriculture, Big data, Internet of things, Machine learning, Smart farming},
pubstate = {published},
tppubtype = {article}
}

@article{Radoglou-Grammatikis2020,
title = {A compilation of UAV applications for precision agriculture},
author = { P. Radoglou-Grammatikis and P. Sarigiannidis and T. Lagkas and I. Moscholios},
url = {https://www.researchgate.net/publication/339233121_A_Compilation_of_UAV_Applications_for_Precision_Agriculture},
doi = {10.1016/j.comnet.2020.107148},
year = {2020},
date = {2020-01-01},
journal = {Computer Networks},
volume = {172},
abstract = {Climate change has introduced significant challenges that can affect multiple sectors, including the agricultural one. In particular, according to the Food and Agriculture Organization of the United Nations (FAO) and the International Telecommunication Union (ITU), the world population has to find new solutions to increase the food production by 70% by 2050. The answer to this crucial challenge is the suitable adoption and utilisation of the Information and Communications Technology (ICT) services, offering capabilities that can increase the productivity of the agrochemical products, such as pesticides and fertilisers and at the same time, they should minimise the functional cost. More detailed, the advent of the Internet of Things (IoT) and specifically, the rapid evolution of the Unmanned Aerial Vehicles (UAVs) and Wireless Sensor Networks (WSNs) can lead to valuable and at the same time economic Precision Agriculture (PA) applications, such as aerial crop monitoring and smart spraying tasks. In this paper, we provide a survey regarding the potential use of UAVs in PA, focusing on 20 relevant applications. More specifically, first, we provide a detailed overview of PA, by describing its various aspects and technologies, such as soil mapping and production mapping as well as the role of the Global Positioning Systems (GPS) and Geographical Information Systems (GIS). Then, we discriminate and analyse the various types of UAVs based on their technical characteristics and payload. Finally, we investigate in detail 20 UAV applications that are devoted to either aerial crop monitoring processes or spraying tasks. For each application, we examine the methodology adopted, the proposed UAV architecture, the UAV type, as well as the UAV technical characteristics and payload. © 2020 The Authors},
keywords = {Precision agriculture (PA), Remote sensing (RS), Unmanned aerial vehicle (UAV)},
pubstate = {published},
tppubtype = {article}
}