@article{Spyridis2021,

title = {Modelling and simulation of a new cooperative algorithm for UAV swarm coordination in mobile RF target tracking},

author = { Y. Spyridis, T. Lagkas, P. Sarigiannidis and J. Zhang},

url = {https://www.researchgate.net/publication/346563683_Modelling_and_simulation_of_a_new_cooperative_algorithm_for_UAV_swarm_coordination_in_mobile_RF_target_tracking},

doi = {10.1016/j.simpat.2020.102232},

year  = {2021},

date = {2021-02-01},

journal = {Simulation Modelling Practice and Theory},

volume = {107},

pages = {102232},

publisher = {Elsevier BV},

abstract = {Recent advancements in sensor technology have allowed unmanned aerial vehicles (UAVs) to function as sensing devices in cooperative aerial communication networks, offering novel solutions in applications of environment inspection, disaster detection and search and rescue operations. Towards this trend, the efficient deployment and coordination of UAV networks is of vital importance. Generating controlled experimental conditions to implement and evaluate different approaches in this context can be impractical and costly and thus the solution of modelling is often preferred. This paper introduces a tracking model in which multirotor UAVs, equipped with received signal strength indicator (RSSI) sensors, are organized in a swarm and cooperate to approximate and trail a moving target. The proposed algorithm is able to offer autonomous tracking in large scale environments, by utilising just the strength of the communication signal emitted by a radio frequency transmitter carried by the target. A model of the proposed algorithm is created, and its performance is thoroughly evaluated in a specialized simulator developed in the Processing IDE. Results demonstrate the increased tracking efficiency of the proposed solution compared to a trilateration method. © 2020 Elsevier Ltd},

keywords = {Mobile target tracking, Modelling, RSSI, Simulation, UAV swarm, unmanned aerial vehicles, wireless sensor networks},

pubstate = {published},

tppubtype = {article}

}

@article{Boursianis2020,

title = {Smart Irrigation System for Precision Agriculture - The AREThOU5A IoT Platform},

author = { A. D. Boursianis and M. S. Papadopoulou and A. Gotsis and S. Wan and P. Sarigiannidis and S. Nikolaidis and S. K. Goudos},

url = {Smart Irrigation System for Precision Agriculture - The AREThOU5A IoT Platform},

doi = {10.1109/jsen.2020.3033526},

year  = {2020},

date = {2020-01-01},

journal = {IEEE Sensors Journal},

pages = {1--1},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

abstract = {Agriculture 4.0, as the future of farming technology, includes several key enabling technologies towards sustainable agriculture. The use of state-of-the-art technologies, such as the Internet of Things, transform traditional cultivation practices, like irrigation, to modern solutions of precision agriculture. In this paper, we present in detail the subsystems and the architecture of an intelligent irrigation system for precision agriculture, the AREThOU5A IoT platform. We describe the operation of the IoT node that is utilized in the platform. Moreover, we apply the radiofrequency energy harvesting technique to the presented IoT platform, as an alternative technique to deliver power to the IoT node of the platform. To this end, we fabricate and validate a rectenna module for radiofrequency energy harvesting. Experimental results of the fabricated rectenna exhibit a satisfactory performance as a harvester of ambient sources in an outdoor environment. IEEE},

keywords = {Intelligent sensors, IoT technology, Irrigation, precision agriculture, Radio frequency, radio frequency energy harvesting, smart irrigation, Wireless communication, wireless sensor networks},

pubstate = {published},

tppubtype = {article}

}

@article{Triantafyllou2019b,

title = {Precision agriculture: A remote sensing monitoring system architecture},

author = { A. Triantafyllou and P. Sarigiannidis and S. Bibi},

url = {https://www.researchgate.net/publication/337192880_Precision_Agriculture_A_Remote_Sensing_Monitoring_System_Architecture},

doi = {10.3390/info10110348},

year  = {2019},

date = {2019-01-01},

journal = {Information (Switzerland)},

volume = {10},

number = {11},

abstract = {Smart Farming is a development that emphasizes on the use of modern technologies in the cyber-physical field management cycle. Technologies such as the Internet of Things (IoT) and Cloud Computing have accelerated the digital transformation of the conventional agricultural practices promising increased production rate and product quality. The adoption of smart farming though is hampered because of the lack of models providing guidance to practitioners regarding the necessary components that constitute IoT-based monitoring systems. To guide the process of designing and implementing Smart farming monitoring systems, in this paper we propose a generic reference architecture model, taking also into consideration a very important non-functional requirement, the energy consumption restriction. Moreover, we present and discuss the technologies that incorporate the seven layers of the architecture model that are the Sensor Layer, the Link Layer, the Encapsulation Layer, the Middleware Layer, the Configuration Layer, the Management Layer and the Application Layer. Furthermore, the proposed Reference Architecture model is exemplified in a real-world application for surveying Saffron agriculture in Kozani, Greece. © 2019 by the authors.},

keywords = {Cloud Computing, Communication technologies, Internet of things, precision agriculture, smart farming, wireless sensor networks},

pubstate = {published},

tppubtype = {article}

}

@article{Sarigiannidis20157560,

title = {Detecting Sybil attacks in wireless sensor networks using UWB ranging-based information},

author = { P. Sarigiannidis and E. Karapistoli and A.A. Economides},

url = {https://www.researchgate.net/publication/279153588_Detecting_Sybil_Attacks_in_Wireless_Sensor_Networks_using_UWB_Ranging-based_Information?_sg=8HafLwH09h8CvldAKWBSwxdP1uPr4CVat2Xutl6381pf9s5GybAmhWbTDwL3Y4fLD9wOI6trjwQ6MWI},

doi = {10.1016/j.eswa.2015.05.057},

year  = {2015},

date = {2015-01-01},

journal = {Expert Systems with Applications},

volume = {42},

number = {21},

pages = {7560-7572},

abstract = {Security is becoming a major concern for many mission-critical applications wireless sensor networks (WSNs) are envisaged to support. The inherently vulnerable characteristics of WSNs appoint them susceptible to various types of attacks. This work restrains its focus on how to defend against a particularly harmful form of attack, the Sybil attack. Sybil attacks can severely deteriorate the network performance and compromise the security by disrupting many networking protocols. This paper presents a rule-based anomaly detection system, called RADS, which monitors and timely detects Sybil attacks in large-scale WSNs. At its core, the proposed expert system relies on an ultra-wideband (UWB) ranging-based detection algorithm that operates in a distributed manner requiring no cooperation or information sharing between the sensor nodes in order to perform the anomaly detection tasks. The feasibility of the proposed approach is proven analytically, while the performance of RADS in exposing Sybil attacks is extensively assessed both mathematically and numerically. The obtained results demonstrate that RADS achieves high detection accuracy and low false alarm rate appointing it a promising ADS candidate for this class of wireless networks. © 2015 Elsevier Ltd. All rights reserved.},

keywords = {Detection probability analysis, Rule-based anomaly detection system, Ultra-wideband (UWB) radio technology, UWB ranging-based Sybil attack detection, wireless sensor networks},

pubstate = {published},

tppubtype = {article}

}