Christos Bouras
Short CV: Christos Bouras is Professor in the University of Patras, Department of Computer Engineering and Informatics. Also he is a scientific advisor of Research Unit 6 in Computer Technology Institute and Press – Diophantus, Patras, Greece. His research interests include Analysis of Performance of Networking and Computer Systems, Computer Networks and Protocols, Mobile and Wireless Communications, Telematics and New Services, QoS and Pricing for Networks and Services, e-learning, Networked Virtual Environments and WWW Issues. He has extended professional experience in Design and Analysis of Networks, Protocols, Telematics and New Services. He has published more than 450 papers in various well-known refereed books, conferences and journals. He is a co-author of 9 books in Greek and editor of 2 in English. He has been member of editorial board for international journals and PC member and referee in various international journals and conferences. He has participated in R&D projects.
Journal Articles
Bouras, Christos; Stergiou, Eirini; Karakostaki, Charitini; Tzanos, Vasileios; Kokkinos, Vasileios
The Nexus between Wind Energy, Biodiversity Protection and Social Acceptance: Evidence of Good Practices from Greece, Latvia and Poland Journal Article
In: International Journal of Environmental and Ecological Engineering , World Academy of Science, Engineering and Technology, vol. 18, pp. 85-94, 2024.
Abstract | Links | BibTeX | Tags:
@article{4672,
title = {The Nexus between Wind Energy, Biodiversity Protection and Social Acceptance: Evidence of Good Practices from Greece, Latvia and Poland},
author = {Christos Bouras and Eirini Stergiou and Charitini Karakostaki and Vasileios Tzanos and Vasileios Kokkinos},
url = {https://telematics.upatras.gr/wp-content/uploads/2024/06/IJEEE2023_Bouras.pdf},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {International Journal of Environmental and Ecological Engineering , World Academy of Science, Engineering and Technology},
volume = {18},
pages = {85-94},
abstract = {Wind power represents a major pathway to curtailing greenhouse gas emissions and thus reducing the rate of climate change. A wind turbine runs practically emission-free for 20 years, representing one of the most environmentally sustainable sources of energy. Nevertheless, environmental and biodiversity concerns can often slow down or halt the deployment of wind farms due to local public opposition. This opposition is often fuelled by poor relationships between wind energy stakeholders and civil society, which in many cases led to conflictual protests and property damage. In this context, addressing these concerns is essential in order to facilitate the proliferation of wind farms in Europe and the phase-out of fossil fuels from the energy mix. The aim of this study is to identify a number of good practices and cases to avoid increasing biodiversity protection at all stages of wind farms’ lifecycle in three participating countries, namely Greece, Latvia, and Poland. The results indicate that although available technological solutions are already being exploited worldwide, in these countries, there is still room for improvement. To address this gap, a set of policy recommendations is proposed to accomplish the wind energy targets in the near future while simultaneously mitigating the pertinent biodiversity risks.},
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pubstate = {published},
tppubtype = {article}
}
Wind power represents a major pathway to curtailing greenhouse gas emissions and thus reducing the rate of climate change. A wind turbine runs practically emission-free for 20 years, representing one of the most environmentally sustainable sources of energy. Nevertheless, environmental and biodiversity concerns can often slow down or halt the deployment of wind farms due to local public opposition. This opposition is often fuelled by poor relationships between wind energy stakeholders and civil society, which in many cases led to conflictual protests and property damage. In this context, addressing these concerns is essential in order to facilitate the proliferation of wind farms in Europe and the phase-out of fossil fuels from the energy mix. The aim of this study is to identify a number of good practices and cases to avoid increasing biodiversity protection at all stages of wind farms’ lifecycle in three participating countries, namely Greece, Latvia, and Poland. The results indicate that although available technological solutions are already being exploited worldwide, in these countries, there is still room for improvement. To address this gap, a set of policy recommendations is proposed to accomplish the wind energy targets in the near future while simultaneously mitigating the pertinent biodiversity risks.
Bouras, Christos; Gkamas, Apostolos; Salgado, Spyridon Aniceto Katsampiris
Long Range Based IoT Search and Rescue System, a Human- Computer Interaction Preliminary Study and Implementation Journal Article
In: Computer Networks and Communications, Universal Wiser, pp. 2 - 16, 2023.
Abstract | Links | BibTeX | Tags:
@article{4670,
title = {Long Range Based IoT Search and Rescue System, a Human- Computer Interaction Preliminary Study and Implementation},
author = {Christos Bouras and Apostolos Gkamas and Spyridon Aniceto Katsampiris Salgado},
url = {https://telematics.upatras.gr/wp-content/uploads/2024/06/CNC2023_Bouras1.pdf},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {Computer Networks and Communications, Universal Wiser},
pages = {2 - 16},
abstract = {Nowadays, IoT has been introduced in different aspects of our lives giving solutions to several problems, one of which is the Search and Rescue (SAR) operations. People that suffer from dementia or people with disease in the autism spectrum tend to elope from their caretaker’s attention, a fact that can lead to serious problems. Thus, a system that takes into consideration of the multiple requirements is of paramount importance. In this paper, a LoRa based SAR system is proposed in order to help in the localization of people with high risk of going missing. In contrast to most of the related systems, in this research article a different approach has been followed. Instead of focusing on the technology, in our approach a human-centered design has been used, leveraging the knowledge of Human-Computer Interaction (HCI) domain. Thus, the technologies used, are an outcome of the initial study. Finally, the system is evaluated using heuristic evaluation and questionnaires},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Nowadays, IoT has been introduced in different aspects of our lives giving solutions to several problems, one of which is the Search and Rescue (SAR) operations. People that suffer from dementia or people with disease in the autism spectrum tend to elope from their caretaker’s attention, a fact that can lead to serious problems. Thus, a system that takes into consideration of the multiple requirements is of paramount importance. In this paper, a LoRa based SAR system is proposed in order to help in the localization of people with high risk of going missing. In contrast to most of the related systems, in this research article a different approach has been followed. Instead of focusing on the technology, in our approach a human-centered design has been used, leveraging the knowledge of Human-Computer Interaction (HCI) domain. Thus, the technologies used, are an outcome of the initial study. Finally, the system is evaluated using heuristic evaluation and questionnaires
Bouras, Christos; Kollia, Anastasia
Analyzing mmWave Bands from a techno – economic perspective in 5G networks Journal Article
In: International Journal of Business Data Communications and Networking (IJBDCN), IGI Global, pp. 1 - 26, 2023.
Abstract | Links | BibTeX | Tags:
@article{4671,
title = {Analyzing mmWave Bands from a techno – economic perspective in 5G networks},
author = {Christos Bouras and Anastasia Kollia},
url = {https://telematics.upatras.gr/wp-content/uploads/2024/06/IJBDCN2023_Bouras.pdf},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {International Journal of Business Data Communications and Networking (IJBDCN), IGI Global},
pages = {1 - 26},
abstract = {The data rates used by mobile network subscribers have been augmented the last few years either via excessive social media usage or video-streams. Thus, most traffic is exchanged in video form online. The next decade almost 7-10 devices per person will be connected via the Internet. The Internet of Things (IoT) is a technology contributing in this direction, as simplistic domestic devices such as cookers, fridges etc. are going to be connected in the Internet and will offer the chance of remote managing of these appliances via applications in mobile phones.
Nowadays, mobile subscribers require augmented demands in terms of mobile service experience, which require large network resources. Users are not extremely content by network’s efficiency and ask for better services in lower prices. They also require coverage on the most remote places, such as high mountains, beaches etc. as social media are a huge part of the everyday life and thus, users want to stay connected as much as possible},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The data rates used by mobile network subscribers have been augmented the last few years either via excessive social media usage or video-streams. Thus, most traffic is exchanged in video form online. The next decade almost 7-10 devices per person will be connected via the Internet. The Internet of Things (IoT) is a technology contributing in this direction, as simplistic domestic devices such as cookers, fridges etc. are going to be connected in the Internet and will offer the chance of remote managing of these appliances via applications in mobile phones.
Nowadays, mobile subscribers require augmented demands in terms of mobile service experience, which require large network resources. Users are not extremely content by network’s efficiency and ask for better services in lower prices. They also require coverage on the most remote places, such as high mountains, beaches etc. as social media are a huge part of the everyday life and thus, users want to stay connected as much as possible
Nowadays, mobile subscribers require augmented demands in terms of mobile service experience, which require large network resources. Users are not extremely content by network’s efficiency and ask for better services in lower prices. They also require coverage on the most remote places, such as high mountains, beaches etc. as social media are a huge part of the everyday life and thus, users want to stay connected as much as possible
Bouras, Christos; Kalogeropoulos, Rafail
Prediction Mechanisms to Improve 5G Network User allocation and Resource management Journal Article
In: Wireless Personal Communications, Springer Verlang, pp. 1 - 25, 2022.
Abstract | Links | BibTeX | Tags: Internet of Things, Machine Learning
@article{4547,
title = {Prediction Mechanisms to Improve 5G Network User allocation and Resource management},
author = {Christos Bouras and Rafail Kalogeropoulos},
url = {https://telematics.upatras.gr/bouras-kalogeropoulos2022_article_predictionmechanismstoimprove5/},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Wireless Personal Communications, Springer Verlang},
pages = {1 - 25},
abstract = {As technology rapidly advances, the number of devices constantly communicating, transmitting and receiving data through the cellular networks keeps rising, posing an unprecedented load on them. Such an increase calls for establishing new methods to manage these devices as well as utilize the data produced by them to establish network architectures that can prevent cellular networks from overloading. To achieve the desired results, we need to optimally allocate network resources to existing users. Resource allocation has traditionally been considered an optimization problem where proposed solutions are hard to implement in real time, resulting in the use of inferior solutions with reduced produced performance. With the introduction of Machine Learning, we propose three mechanisms, intending to utilize network data to improve real time network performance. The first mechanism, a Decision Trees based mechanism aims to improve real time decision making by predicting the optimal matching of users and Base Stations. The second mechanism, a K-means based mechanism intends to tackle network congestion and ensure uninterrupted Quality of Service by predicting the optimal coordinates for placing Base Stations along the network based on traffic data. Finally, a Regression based mechanism manages to predict user movement along the network, resulting in improved resource management and reduced energy waste. These mechanisms can work cooperatively, essentially establishing a network architecture that utilizes prediction to efficiently allocate users and manage available resources.},
keywords = {Internet of Things, Machine Learning},
pubstate = {published},
tppubtype = {article}
}
As technology rapidly advances, the number of devices constantly communicating, transmitting and receiving data through the cellular networks keeps rising, posing an unprecedented load on them. Such an increase calls for establishing new methods to manage these devices as well as utilize the data produced by them to establish network architectures that can prevent cellular networks from overloading. To achieve the desired results, we need to optimally allocate network resources to existing users. Resource allocation has traditionally been considered an optimization problem where proposed solutions are hard to implement in real time, resulting in the use of inferior solutions with reduced produced performance. With the introduction of Machine Learning, we propose three mechanisms, intending to utilize network data to improve real time network performance. The first mechanism, a Decision Trees based mechanism aims to improve real time decision making by predicting the optimal matching of users and Base Stations. The second mechanism, a K-means based mechanism intends to tackle network congestion and ensure uninterrupted Quality of Service by predicting the optimal coordinates for placing Base Stations along the network based on traffic data. Finally, a Regression based mechanism manages to predict user movement along the network, resulting in improved resource management and reduced energy waste. These mechanisms can work cooperatively, essentially establishing a network architecture that utilizes prediction to efficiently allocate users and manage available resources.
Stefas, Dimitris; Gyftokostas, Nikolaos; Kourelias, Panagiotis; Nanou, Eleni; Tananaki, Chrysoula; Kanelis, Dimitrios; Liolios, Vasileios; Kokkinos, Vasileios; Bouras, Christos; Couris, Stelios
Honey discrimination based on the bee feeding by Laser Induced Breakdown Spectroscopy Journal Article
In: Food Control, Elsevier Science, pp. 1 - 9 , 2022.
Abstract | Links | BibTeX | Tags:
@article{4568,
title = {Honey discrimination based on the bee feeding by Laser Induced Breakdown Spectroscopy},
author = {Dimitris Stefas and Nikolaos Gyftokostas and Panagiotis Kourelias and Eleni Nanou and Chrysoula Tananaki and Dimitrios Kanelis and Vasileios Liolios and Vasileios Kokkinos and Christos Bouras and Stelios Couris},
url = {https://telematics.upatras.gr/honey-discrimination-based-on-the-bee-feeding-by-libs/},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Food Control, Elsevier Science},
pages = {1 - 9 },
abstract = {In the present work, the effects of artificial feeding of bees on the honey are investigated by employing for the first time, Laser Induced Breakdown Spectroscopy (LIBS) by analyzing the emission spectral characteristics of the plasma created on the surface of honey samples. Correlation plots indicating the importance of spectral lines of elements as e.g., Calcium (Ca), Magnesium (Mg), Sodium (Na) and Potassium (K) are constructed, while machine learning algorithms based on Linear Discriminant Analysis (LDA) and Random Forest Classifiers (RFC) are employed to classify the honey samples in terms of the bee food used. The constructed machine learning
models were validated by both cross-validation and external validation, while the obtained accuracies exceeded 90% of correct classification, indicating the potential of LIBS technique for honey discrimination. The obtained results by LIBS were also validated by HPLC-RID, which is the standard technique used for the analysis of the main honey sugars.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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In the present work, the effects of artificial feeding of bees on the honey are investigated by employing for the first time, Laser Induced Breakdown Spectroscopy (LIBS) by analyzing the emission spectral characteristics of the plasma created on the surface of honey samples. Correlation plots indicating the importance of spectral lines of elements as e.g., Calcium (Ca), Magnesium (Mg), Sodium (Na) and Potassium (K) are constructed, while machine learning algorithms based on Linear Discriminant Analysis (LDA) and Random Forest Classifiers (RFC) are employed to classify the honey samples in terms of the bee food used. The constructed machine learning
models were validated by both cross-validation and external validation, while the obtained accuracies exceeded 90% of correct classification, indicating the potential of LIBS technique for honey discrimination. The obtained results by LIBS were also validated by HPLC-RID, which is the standard technique used for the analysis of the main honey sugars.
models were validated by both cross-validation and external validation, while the obtained accuracies exceeded 90% of correct classification, indicating the potential of LIBS technique for honey discrimination. The obtained results by LIBS were also validated by HPLC-RID, which is the standard technique used for the analysis of the main honey sugars.
Bouras, Christos; Stefas, Dimitrios; Gyftokostas, Nikolaos; Kourelias, Panagiotis; Nanou, Eleni; Kokkinos, Vasileios; Couris, Stelios
In: Food Control, Elsevier Science, vol. 130, pp. 1-8, 2021.
Abstract | Links | BibTeX | Tags:
@article{4538,
title = {Discrimination of olive oils based on the olive cultivar origin by machine learning employing the fusion of emission and absorption spectroscopic data},
author = {Christos Bouras and Dimitrios Stefas and Nikolaos Gyftokostas and Panagiotis Kourelias and Eleni Nanou and Vasileios Kokkinos and Stelios Couris},
url = {https://telematics.upatras.gr/1-s2-0-s0956713521004564-main-1/},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Food Control, Elsevier Science},
volume = {130},
pages = {1-8},
abstract = {In this work Laser-Induced Breakdown Spectroscopy (LIBS) and absorption spectroscopy aided by machine learning are employed for discriminating some extra virgin Greek olive oils of different olive cultivars for the first time. LIBS and absorption spectra of extra virgin olive oils belonging to Kolovi and Koroneiki cultivars, as well as mixtures of them, were collected, analyzed, and used to develop classification schemes employing Linear Discriminant Analysis and Gradient Boosting, the latter allowing the determination of the most important spectral features. Both algorithms were found to provide efficient classification of the olive oil spectra with accuracies exceeding 90%. Furthermore, for the first time, the emission spectra of LIBS were fused with the absorption spectra to create predictive models and their accuracies were found to be significantly improved. This work demonstrates the enhanced capabilities of LIBS and absorption spectroscopy and the potential of their combination for olive oil quality monitoring and control.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this work Laser-Induced Breakdown Spectroscopy (LIBS) and absorption spectroscopy aided by machine learning are employed for discriminating some extra virgin Greek olive oils of different olive cultivars for the first time. LIBS and absorption spectra of extra virgin olive oils belonging to Kolovi and Koroneiki cultivars, as well as mixtures of them, were collected, analyzed, and used to develop classification schemes employing Linear Discriminant Analysis and Gradient Boosting, the latter allowing the determination of the most important spectral features. Both algorithms were found to provide efficient classification of the olive oil spectra with accuracies exceeding 90%. Furthermore, for the first time, the emission spectra of LIBS were fused with the absorption spectra to create predictive models and their accuracies were found to be significantly improved. This work demonstrates the enhanced capabilities of LIBS and absorption spectroscopy and the potential of their combination for olive oil quality monitoring and control.
Gyftokostas, Nikolaos; Stefas, Dimitrios; Kokkinos, Vasileios; Bouras, Christos; Couris, Stelios
Laser-Induced Breakdown Spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination Journal Article
In: Scientific Reports, Nature Research Journals, vol. 11, pp. 1 - 11, 2021.
Abstract | Links | BibTeX | Tags:
@article{4520,
title = {Laser-Induced Breakdown Spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination},
author = {Nikolaos Gyftokostas and Dimitrios Stefas and Vasileios Kokkinos and Christos Bouras and Stelios Couris},
url = {https://telematics.upatras.gr/s41598-021-84941-z/},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Scientific Reports, Nature Research Journals},
volume = {11},
pages = {1 - 11},
abstract = {Olive oil is a basic element of the Mediterranean diet and a key product for the economies of the Mediterranean countries. Thus, there is an added incentive in the olive oil business for fraud through practices like adulteration and mislabeling. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning is used for the classification of 139 virgin olive oils in terms of their geographical origin. The LIBS spectra of these olive oil samples were used to train different machine learning algorithms, namely LDA, ERTC, RFC, XGBoost, and to assess their classification performance. In addition, the variable importance of the spectral features was calculated, for the identification of the most important ones for the classification performance and to reduce their number for the algorithmic training. The algorithmic training was evaluated and tested by means of classification reports, confusion matrices and by external validation procedure as well. The present results demonstrate that machine learning aided LIBS can be a powerful and efficient tool for the rapid authentication of the geographic origin of virgin olive oil.},
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pubstate = {published},
tppubtype = {article}
}
Olive oil is a basic element of the Mediterranean diet and a key product for the economies of the Mediterranean countries. Thus, there is an added incentive in the olive oil business for fraud through practices like adulteration and mislabeling. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning is used for the classification of 139 virgin olive oils in terms of their geographical origin. The LIBS spectra of these olive oil samples were used to train different machine learning algorithms, namely LDA, ERTC, RFC, XGBoost, and to assess their classification performance. In addition, the variable importance of the spectral features was calculated, for the identification of the most important ones for the classification performance and to reduce their number for the algorithmic training. The algorithmic training was evaluated and tested by means of classification reports, confusion matrices and by external validation procedure as well. The present results demonstrate that machine learning aided LIBS can be a powerful and efficient tool for the rapid authentication of the geographic origin of virgin olive oil.
Bouras, Christos; Gkamas, Apostolos; Katsampiris, Spyridon
Energy efficient mechanism for LoRa networks Journal Article
In: Internet of Things: Engineering Cyber Physical Human Systems, Elsevier Science, 2021, vol. 13, pp. 1-13, 2021.
Abstract | Links | BibTeX | Tags:
@article{4510,
title = {Energy efficient mechanism for LoRa networks},
author = {Christos Bouras and Apostolos Gkamas and Spyridon Katsampiris},
url = {https://telematics.upatras.gr/1-s2-0-s2542660521000044-main/},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Internet of Things: Engineering Cyber Physical Human Systems, Elsevier Science, 2021},
volume = {13},
pages = {1-13},
abstract = {Internet of Things (IoT) is the ability of communication between objects and refers to a wide range of applications, such as the Search and Rescue (SAR) operations. SAR applications need long distance connectivity, thus can be benefited by Low Power Wide Area Networks (LPWAN). One LPWAN technology is called LoRa (Long Range). In this context, the WeSAR project has been created that provides a system for locating and rescuing people, especially those who belong to population groups with a very high probability of getting lost. The energy consumption of the wearable devices is important factor in the SAR operations, as the battery should last more than 45 50 hours. Therefore, the proposed system is based on LoRa technology, the user localization is based on LoRa using trilateration and Time Difference of Arrival (TDoA) instead of Geolocation Positioning System (GPS), as GPS increases the energy consumption, and we created an energy-efficient mechanism to tackle the problem of energy consumption. In this paper, an energy efficient mechanism for LoRa networks is presented, that is based on the user’s state and the battery level of the wearable device. Realistic simulations have been conducted to evaluate the system for both one wearable device, and multiple wearable devices, using different mobility models. The results from the simulations have shown a decrease in the energy consumption in various node mobility models that were tested, without compromising the delivery ratio of the network, something important as the LoRa packets are used for the localization of the lost person.},
keywords = {},
pubstate = {published},
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Internet of Things (IoT) is the ability of communication between objects and refers to a wide range of applications, such as the Search and Rescue (SAR) operations. SAR applications need long distance connectivity, thus can be benefited by Low Power Wide Area Networks (LPWAN). One LPWAN technology is called LoRa (Long Range). In this context, the WeSAR project has been created that provides a system for locating and rescuing people, especially those who belong to population groups with a very high probability of getting lost. The energy consumption of the wearable devices is important factor in the SAR operations, as the battery should last more than 45 50 hours. Therefore, the proposed system is based on LoRa technology, the user localization is based on LoRa using trilateration and Time Difference of Arrival (TDoA) instead of Geolocation Positioning System (GPS), as GPS increases the energy consumption, and we created an energy-efficient mechanism to tackle the problem of energy consumption. In this paper, an energy efficient mechanism for LoRa networks is presented, that is based on the user’s state and the battery level of the wearable device. Realistic simulations have been conducted to evaluate the system for both one wearable device, and multiple wearable devices, using different mobility models. The results from the simulations have shown a decrease in the energy consumption in various node mobility models that were tested, without compromising the delivery ratio of the network, something important as the LoRa packets are used for the localization of the lost person.
Kokoris, Ioannis; Kokkinos, Vasileios; Michos, Evangelos; Kalogeropoulos, Rafail; Charalambides, Marios; Kounelis, Agisilaos; Iliadou, Eleni; Damianidis, Christos K.; Mallinis, Giorgos; Bouras, Christos; Dimopoulos, Panayotis
MAES_GR: A Web-Based, Spatially Enabled Field Survey Platform for the MAES Implementation in Greece Journal Article
In: Land, MDPI 2021, vol. 10, pp. 1 - 18, 2021.
Abstract | Links | BibTeX | Tags:
@article{4524,
title = {MAES_GR: A Web-Based, Spatially Enabled Field Survey Platform for the MAES Implementation in Greece},
author = {Ioannis Kokoris and Vasileios Kokkinos and Evangelos Michos and Rafail Kalogeropoulos and Marios Charalambides and Agisilaos Kounelis and Eleni Iliadou and Christos K. Damianidis and Giorgos Mallinis and Christos Bouras and Panayotis Dimopoulos},
url = {https://telematics.upatras.gr/land-10-00381/},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Land, MDPI 2021},
volume = {10},
pages = {1 - 18},
abstract = {This study presents a standardized approach to collecting, registering, and reporting field-survey data for baseline MAES (Mapping and Assessment of Ecosystems and their Services) information in Greece. This is accomplished through a web-based platform (MAES_GR) exclusively developed under the relevant, nation-wide LIFE-IP 4 NATURA project. Based on the European Commission’s guidance for ecosystem condition (EC) and ecosystem services (ES) MAES studies, we conceptualized and structured an online platform to support EC and ES assessments, integrating all relevant fields of information needed for registering EC and ES parameters. A novel algorithm calculating EC was also developed and it is available as an integral part of the platform. The use of the MAES_GR platform was evaluated during nationwide field surveys efforts, increasing time efficiency and reducing costs. Field recording of EC and ES pinpoint spatial priorities for ecosystem restoration, conservation and sustainable development. This work highlights that MAES implementation can be favored by the use of technology tools such as mobile survey platforms, developed according to scientific needs and policy guidelines. Such tools, apart from the data inventory phase, can be used for data analysis, synthesis and extraction, providing timely, standardized information suitable for reporting at the local, regional, national and European Union scale.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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This study presents a standardized approach to collecting, registering, and reporting field-survey data for baseline MAES (Mapping and Assessment of Ecosystems and their Services) information in Greece. This is accomplished through a web-based platform (MAES_GR) exclusively developed under the relevant, nation-wide LIFE-IP 4 NATURA project. Based on the European Commission’s guidance for ecosystem condition (EC) and ecosystem services (ES) MAES studies, we conceptualized and structured an online platform to support EC and ES assessments, integrating all relevant fields of information needed for registering EC and ES parameters. A novel algorithm calculating EC was also developed and it is available as an integral part of the platform. The use of the MAES_GR platform was evaluated during nationwide field surveys efforts, increasing time efficiency and reducing costs. Field recording of EC and ES pinpoint spatial priorities for ecosystem restoration, conservation and sustainable development. This work highlights that MAES implementation can be favored by the use of technology tools such as mobile survey platforms, developed according to scientific needs and policy guidelines. Such tools, apart from the data inventory phase, can be used for data analysis, synthesis and extraction, providing timely, standardized information suitable for reporting at the local, regional, national and European Union scale.
Gyftokostas, Nikolaos; Nanou, Eleni; Stefas, Dimitrios; Kokkinos, Vasileios; Bouras, Christos; Couris, Stelios
In: Open Access Journal, MDPI, Special Issue Characterization of Olive Products from Greece, vol. 26, pp. 1 - 19, 2021.
Abstract | Links | BibTeX | Tags:
@article{4521,
title = {Classification of Greek olive from different regions by machine learning - aided Laser - Induced Breakdown Spectroscopy and Absorption Spectroscopy},
author = {Nikolaos Gyftokostas and Eleni Nanou and Dimitrios Stefas and Vasileios Kokkinos and Christos Bouras and Stelios Couris},
url = {https://telematics.upatras.gr/s41598-021-84941-z_0/},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Open Access Journal, MDPI, Special Issue Characterization of Olive Products from Greece},
volume = {26},
pages = {1 - 19},
abstract = {In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided by machine learning algorithms, were employed for the discrimination/classification of olive oils regarding their geographical origin. Both emission and absorption spectra were initially preprocessed by means of Principal Component Analysis (PCA) and were subsequently used for the construction of predictive models, employing Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). All
data analysis methodologies were validated by both “k-fold” cross-validation and external validation methods. In all cases, very high classification accuracies were found, up to 100%. The present results demonstrate the advantages of machine learning implementation for improving the capabilities of these spectroscopic techniques as tools for efficient olive oil quality monitoring and control.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided by machine learning algorithms, were employed for the discrimination/classification of olive oils regarding their geographical origin. Both emission and absorption spectra were initially preprocessed by means of Principal Component Analysis (PCA) and were subsequently used for the construction of predictive models, employing Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). All
data analysis methodologies were validated by both “k-fold” cross-validation and external validation methods. In all cases, very high classification accuracies were found, up to 100%. The present results demonstrate the advantages of machine learning implementation for improving the capabilities of these spectroscopic techniques as tools for efficient olive oil quality monitoring and control.
data analysis methodologies were validated by both “k-fold” cross-validation and external validation methods. In all cases, very high classification accuracies were found, up to 100%. The present results demonstrate the advantages of machine learning implementation for improving the capabilities of these spectroscopic techniques as tools for efficient olive oil quality monitoring and control.
Bouras, Christos; Gkamas, Apostolos; Katsampiris, Spyridon; Papachristos, Nikolaos
A Comparative Study of Machine Learning Models for Spreading Factor Selection in LoRa Networks Journal Article
In: Journal of Wireless Networks and Broadband Technologies (IJWNBT), IGI Global, vol. 10, pp. 100-121, 2021.
Abstract | Links | BibTeX | Tags:
@article{4519,
title = {A Comparative Study of Machine Learning Models for Spreading Factor Selection in LoRa Networks},
author = {Christos Bouras and Apostolos Gkamas and Spyridon Katsampiris and Nikolaos Papachristos},
url = {https://telematics.upatras.gr/a-comparative-study-of-machine-learning-models-for-spreading-factor-selection-in-lora-networks/},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Journal of Wireless Networks and Broadband Technologies (IJWNBT), IGI Global},
volume = {10},
pages = {100-121},
abstract = {Low Power Wide Area Networks (LPWAN) technologies offer reasonably priced connectivity to a large number of low-power devices spread over great geographical ranges. Long Range (LoRa) is a LPWAN technology that empowers energy-efficient communication. In LoRaWAN networks collisions are strongly correlated with Spreading Factor (SF) assignment of end-nodes which affects network performance. In this work, SF assignment using Machine Learning models in simulation environment is presented. This work examines three approaches for the selection of the SF during LoRa transmissions a) random SF assignment b) Adaptive Data Rate (ADR) and c) SF selection through Machine Learning (ML). The main target is to study and determine the most efficient approach as well as to investigate the benefits of using ML techniques in the context of LoRa networks. In this research a library that enables the communication between ML libraries and OMNeT++ simulator was created. The performance of the approaches is evaluated for different scenarios, using the delivery ratio and energy consumption metrics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Low Power Wide Area Networks (LPWAN) technologies offer reasonably priced connectivity to a large number of low-power devices spread over great geographical ranges. Long Range (LoRa) is a LPWAN technology that empowers energy-efficient communication. In LoRaWAN networks collisions are strongly correlated with Spreading Factor (SF) assignment of end-nodes which affects network performance. In this work, SF assignment using Machine Learning models in simulation environment is presented. This work examines three approaches for the selection of the SF during LoRa transmissions a) random SF assignment b) Adaptive Data Rate (ADR) and c) SF selection through Machine Learning (ML). The main target is to study and determine the most efficient approach as well as to investigate the benefits of using ML techniques in the context of LoRa networks. In this research a library that enables the communication between ML libraries and OMNeT++ simulator was created. The performance of the approaches is evaluated for different scenarios, using the delivery ratio and energy consumption metrics.
Bouras, Christos; Gkamas, Apostolos; Kokkinos, Vasileios; Papachristos, Nikolaos
Performance Evaluation of Monitoring IoT Systems using LoRaWan Journal Article
In: Telecommunication Systems, Springer Verlang, pp. 295 - 308 , 2021.
Abstract | Links | BibTeX | Tags:
@article{4576,
title = {Performance Evaluation of Monitoring IoT Systems using LoRaWan},
author = {Christos Bouras and Apostolos Gkamas and Vasileios Kokkinos and Nikolaos Papachristos},
url = {https://telematics.upatras.gr/telecommunicationssystems2021/},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Telecommunication Systems, Springer Verlang},
pages = {295 - 308 },
abstract = {The proliferation of smart devices, or even better, IoT devices, has led to the widespread development of applications that take advantage of these devices. Of particular interest is the precise localization of such a device. However, these use cases become extremely difficult when connectivity to end-devices is required even in areas where the signal is too low or different technologies co-exist for the transmission of the data. In this research work, we study LoRaWan and Wi-Fi as two possible candidates for data transmission. We are particularly focused on the study of the above technologies in terms of performance as well as application development that can be used as rescue monitoring systems. For this reason, we start by describing LoRa as an ideal low power and long-distance communication protocol on the IoT devices compared to the Wi-Fi network. We perform various simulations in terms of time on air transmission, bit error rate by changing important metrics to study the behavior of the whole mechanism. Based on our simulations, the main findings highlight that the contribution of a Spreading Factor (SF) and bandwidth (BW) optimizations can be applied to real hardware for real Search and Rescue (SAR) cases giving improved results in case of coverage and battery extension applications. As a continuation of our research, we developed a monitor application that collects and visualizes data from end-nodes (wearables). These data are processed gateway and network server to The Things Network (TTN) for further analysis. The proposed solution can be used in different rescue monitor scenarios such as identifying and find individuals of vulnerable groups or those belonging to group of people with a high probability of being lost. The purpose of the above solution is to overcome monitor problems on SAR cases, compare with WiFi and suggest a module supporting both technologies in order to be used in real experiments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The proliferation of smart devices, or even better, IoT devices, has led to the widespread development of applications that take advantage of these devices. Of particular interest is the precise localization of such a device. However, these use cases become extremely difficult when connectivity to end-devices is required even in areas where the signal is too low or different technologies co-exist for the transmission of the data. In this research work, we study LoRaWan and Wi-Fi as two possible candidates for data transmission. We are particularly focused on the study of the above technologies in terms of performance as well as application development that can be used as rescue monitoring systems. For this reason, we start by describing LoRa as an ideal low power and long-distance communication protocol on the IoT devices compared to the Wi-Fi network. We perform various simulations in terms of time on air transmission, bit error rate by changing important metrics to study the behavior of the whole mechanism. Based on our simulations, the main findings highlight that the contribution of a Spreading Factor (SF) and bandwidth (BW) optimizations can be applied to real hardware for real Search and Rescue (SAR) cases giving improved results in case of coverage and battery extension applications. As a continuation of our research, we developed a monitor application that collects and visualizes data from end-nodes (wearables). These data are processed gateway and network server to The Things Network (TTN) for further analysis. The proposed solution can be used in different rescue monitor scenarios such as identifying and find individuals of vulnerable groups or those belonging to group of people with a high probability of being lost. The purpose of the above solution is to overcome monitor problems on SAR cases, compare with WiFi and suggest a module supporting both technologies in order to be used in real experiments.
Stefas, Dimitrios; Gyftokostas, Nikolaos; Kourelias, Panagiotis; Nanou, Eleni; Kokkinos, Vasileios; Bouras, Christos; Couris, Stelios
A Laser-Based Method for the Detection of Honey Adulteration Journal Article
In: Applied Sciences, MPDI, Special Issue Chemical Composition, Properties and Applications of Honey, pp. 1 - 14 , 2021.
Abstract | Links | BibTeX | Tags:
@article{4546,
title = {A Laser-Based Method for the Detection of Honey Adulteration},
author = {Dimitrios Stefas and Nikolaos Gyftokostas and Panagiotis Kourelias and Eleni Nanou and Vasileios Kokkinos and Christos Bouras and Stelios Couris},
url = {https://telematics.upatras.gr/applsci-11-06435/},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Applied Sciences, MPDI, Special Issue Chemical Composition, Properties and Applications of Honey},
pages = {1 - 14 },
abstract = {In the present work, laser-induced breakdown spectroscopy, aided by some machine learning algorithms (i.e., linear discriminant analysis (LDA) and extremely randomized trees (ERT)), is used for the detection of honey adulteration with glucose syrup. In addition, it is shown that instead of the entire LIBS spectrum, the spectral lines of inorganic ingredients of honey (i.e., calcium, sodium, and potassium) can be also used for the detection of adulteration providing efficient discrimination. The constructed predictive models attained high classification accuracies exceeding 90% correct classification.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In the present work, laser-induced breakdown spectroscopy, aided by some machine learning algorithms (i.e., linear discriminant analysis (LDA) and extremely randomized trees (ERT)), is used for the detection of honey adulteration with glucose syrup. In addition, it is shown that instead of the entire LIBS spectrum, the spectral lines of inorganic ingredients of honey (i.e., calcium, sodium, and potassium) can be also used for the detection of adulteration providing efficient discrimination. The constructed predictive models attained high classification accuracies exceeding 90% correct classification.
Bouras, Christos; Michos, Evangelos
A Resource - efficient Approach on User Association in 5G Networks using Downlink and Uplink Decoupling Journal Article
In: International Journal of Wireless Networks and Broadband Technologies (IJWNBT), IGI Global, vol. 9, pp. 43 - 59, 2020.
Abstract | Links | BibTeX | Tags:
@article{4439,
title = {A Resource - efficient Approach on User Association in 5G Networks using Downlink and Uplink Decoupling},
author = {Christos Bouras and Evangelos Michos},
url = {https://telematics.upatras.gr/a-resource-efficient-approach-on-user-association-in-5g-networks-using-downlink-and-uplink-decoupling/},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {International Journal of Wireless Networks and Broadband Technologies (IJWNBT), IGI Global},
volume = {9},
pages = {43 - 59},
abstract = {A user-centered network model can significantly optimize connectivity issues between a user and the corresponding Base Station (BS). This paper shall evaluate the User Centric (UC) model targeted for Fifth Generation telecommunication systems and will attempt to optimize communication between users and BSs. The authors suggest a resource-aware mechanism that targets at improving coverage through the network decoupling into two separate and independent uplink and downlink networks. Our mechanism shall fully respect each user’s initially requested throughput demands and aims to solve the network user – BS association problem with efficient resource management techniques. Simulations revealed that the mechanism perfectly preserves Quality of Service (QoS) and offers increased data rates in favor of ultimate user coverage, in both scenarios. Additionally, Frequency Range 2 offers an increased amount of resources, both increased data rates and higher amounts of devices that are covered by the overall network.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A user-centered network model can significantly optimize connectivity issues between a user and the corresponding Base Station (BS). This paper shall evaluate the User Centric (UC) model targeted for Fifth Generation telecommunication systems and will attempt to optimize communication between users and BSs. The authors suggest a resource-aware mechanism that targets at improving coverage through the network decoupling into two separate and independent uplink and downlink networks. Our mechanism shall fully respect each user’s initially requested throughput demands and aims to solve the network user – BS association problem with efficient resource management techniques. Simulations revealed that the mechanism perfectly preserves Quality of Service (QoS) and offers increased data rates in favor of ultimate user coverage, in both scenarios. Additionally, Frequency Range 2 offers an increased amount of resources, both increased data rates and higher amounts of devices that are covered by the overall network.
Bouras, Christos; Kollia, Anastasia; Maligianni, Eleftheria
Techno - economic comparison of Cognitive Radio and Software Defined Network (SDN) cost models in 5G networks Journal Article
In: Wireless Personal Communications, Springer Verlang, vol. 114, pp. 1403–1430, 2020.
Abstract | Links | BibTeX | Tags:
@article{4468,
title = {Techno - economic comparison of Cognitive Radio and Software Defined Network (SDN) cost models in 5G networks},
author = {Christos Bouras and Anastasia Kollia and Eleftheria Maligianni},
url = {https://telematics.upatras.gr/bouras2020_article_techno-economiccomparisonofcog/},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Wireless Personal Communications, Springer Verlang},
volume = {114},
pages = {1403–1430},
abstract = {5G is anticipated in 2020. In this generation of mobile networks, a great deal of requirements have been set. Although, there are many strong technologies in the telecommunications’ sector they do not respond to the 5G goals. On the other hand, telecommunication operators and providers do not want to invest in new equipment/architectures. Cognitive Radio (CR) and Software Defined Networking (SDN) are two technologies with special and vigorous advantages. In this paper, several technical and economic models are developed. The CR is combined with the Stackelberg game. A Sensitivity Analysis (SA) is implemented and the parameters that impact mostly on the model are pinpointed. It is shown that the CR technology could offer all its fundamental cognitive advantages and even financial profits to the telecommunication companies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
5G is anticipated in 2020. In this generation of mobile networks, a great deal of requirements have been set. Although, there are many strong technologies in the telecommunications’ sector they do not respond to the 5G goals. On the other hand, telecommunication operators and providers do not want to invest in new equipment/architectures. Cognitive Radio (CR) and Software Defined Networking (SDN) are two technologies with special and vigorous advantages. In this paper, several technical and economic models are developed. The CR is combined with the Stackelberg game. A Sensitivity Analysis (SA) is implemented and the parameters that impact mostly on the model are pinpointed. It is shown that the CR technology could offer all its fundamental cognitive advantages and even financial profits to the telecommunication companies.
Bouras, Christos; Kokkalis, Stylianos; Kollia, Anastasia; Papazois, Andreas
Techno-economic comparison of MIMO and DAS cost models in 5G networks Journal Article
In: Wireless Networks, Springer Verlang, vol. 26, pp. 1-15, 2020.
Abstract | Links | BibTeX | Tags:
@article{4311,
title = {Techno-economic comparison of MIMO and DAS cost models in 5G networks},
author = {Christos Bouras and Stylianos Kokkalis and Anastasia Kollia and Andreas Papazois},
url = {https://telematics.upatras.gr/bouras2020_article_techno-economiccomparisonofmim/},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Wireless Networks, Springer Verlang},
volume = {26},
pages = {1-15},
abstract = {High communicational standards have been set for the 5G mobile networks. Therefore, it is of great importance that technological solutions that include all the significant features, such as the high coverage and capacity and low round-trip delays, are adopted for the next generation of mobile networks. Except for their technical efficiency, these technologies should be profitable for providers as well. As a result, the need for limiting the costs spent for the development of these technologies emerges. In this papers, four models two for each one of the two solutions for 5G networks are developed, namely the Multiple Input Multiple Output (MIMO) and the Distributed Antenna System. The architectural models assumed for the techno-economic analyses are presented. The mathematical models for both technologies are developed. Experiments are conducted using prices of the Greek market and also Sensitivity Analysis (SA) is used to pinpoint, which cost parameters are the most expensive ones and therefore it is likely that they discourage providers to invest in them. To our knowledge there are not many studies comparing and contrasting these technologies and there is no SA for MIMO. Therefore, it is considered that research for these models is of vital importance for the next generation of mobile communication networks, as they are foundation stonesfor the formation of 5G.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
High communicational standards have been set for the 5G mobile networks. Therefore, it is of great importance that technological solutions that include all the significant features, such as the high coverage and capacity and low round-trip delays, are adopted for the next generation of mobile networks. Except for their technical efficiency, these technologies should be profitable for providers as well. As a result, the need for limiting the costs spent for the development of these technologies emerges. In this papers, four models two for each one of the two solutions for 5G networks are developed, namely the Multiple Input Multiple Output (MIMO) and the Distributed Antenna System. The architectural models assumed for the techno-economic analyses are presented. The mathematical models for both technologies are developed. Experiments are conducted using prices of the Greek market and also Sensitivity Analysis (SA) is used to pinpoint, which cost parameters are the most expensive ones and therefore it is likely that they discourage providers to invest in them. To our knowledge there are not many studies comparing and contrasting these technologies and there is no SA for MIMO. Therefore, it is considered that research for these models is of vital importance for the next generation of mobile communication networks, as they are foundation stonesfor the formation of 5G.
Bouras, Christos; Kokkinos, Vasileios; Michos, Evangelos
An online tool on sustainable water management Journal Article
In: Tourism: An International Interdisciplinary Journal, Institute for Tourism, Zagreb, Croatia, 2020, vol. 68, Νο4, pp. 450-465, 2020.
Abstract | Links | BibTeX | Tags:
@article{4502,
title = {An online tool on sustainable water management},
author = {Christos Bouras and Vasileios Kokkinos and Evangelos Michos},
url = {https://telematics.upatras.gr/450-465-paper-06-tourism-2020-04eng/},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Tourism: An International Interdisciplinary Journal, Institute for Tourism, Zagreb, Croatia, 2020},
volume = {68, Νο4},
pages = {450-465},
abstract = {Water demand strains supply capacity in the Mediterranean coastal areas, affecting negatively the maintenance of natural and cultural heritage. Tackling this subject, the “Coastal areas sustainable tourism water management in the Mediterranean - CASTWATER” project aims to support sustainable tourism water management in Mediterranean (MED) coastal areas, by improving the monitoring and assessment of the water sustainability performance of tourism. To this end, the elaboration of an online tool to monitor and assess sustainable tourism water management was envisaged and developed, primarily addressed to tourism sector small and medium-sized enterprises (SMEs). The CASTWATER online tool was designed to so as to provide two different functionalities. On the one hand, SMEs can self-evaluate their performance in sustainable water management and efficiently acknowledge possible actions that promote water efficiency in their tourism establishments. On the other hand, the tool measures, at both regional and local level, the levels of good governance and the effectiveness of water-tourism policies in order to improve sustainable water management. The approach presented in this work is heavily based on the initial technical specifications and end-user feedback, aiding SMEs in understanding, comparing, assessing and rating their performance regarding water efficiency and sustainable water manag},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Water demand strains supply capacity in the Mediterranean coastal areas, affecting negatively the maintenance of natural and cultural heritage. Tackling this subject, the “Coastal areas sustainable tourism water management in the Mediterranean - CASTWATER” project aims to support sustainable tourism water management in Mediterranean (MED) coastal areas, by improving the monitoring and assessment of the water sustainability performance of tourism. To this end, the elaboration of an online tool to monitor and assess sustainable tourism water management was envisaged and developed, primarily addressed to tourism sector small and medium-sized enterprises (SMEs). The CASTWATER online tool was designed to so as to provide two different functionalities. On the one hand, SMEs can self-evaluate their performance in sustainable water management and efficiently acknowledge possible actions that promote water efficiency in their tourism establishments. On the other hand, the tool measures, at both regional and local level, the levels of good governance and the effectiveness of water-tourism policies in order to improve sustainable water management. The approach presented in this work is heavily based on the initial technical specifications and end-user feedback, aiding SMEs in understanding, comparing, assessing and rating their performance regarding water efficiency and sustainable water manag
Bouras, Christos; Diles, Georgios; Gkamas, Apostolos; Zacharopoulos, Andreas
A comparative study of 4G and 5G Network Simulators Journal Article
In: International Journal on Advances in Networks and Services, IARIA, vol. 13, pp. 11-20, 2020.
Abstract | Links | BibTeX | Tags:
@article{4467,
title = {A comparative study of 4G and 5G Network Simulators},
author = {Christos Bouras and Georgios Diles and Apostolos Gkamas and Andreas Zacharopoulos},
url = {https://telematics.upatras.gr/netser_v13_n12_2020_paged/},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {International Journal on Advances in Networks and Services, IARIA},
volume = {13},
pages = {11-20},
abstract = {Network simulation is a technique of utmost importance to evaluate new network performance, verify new algorithms and analyze various network topologies. It is used to find results to be expected from a hardware setup without the need for actual implementation. For this reason, there is a plethora of Network Simulation Software applied to different scenarios to evaluate theories and hypotheses. A cellular network is an example of an extremely complex system in which different components impact the overall performance in different ways. The aim of this paper is to study the most common Simulators regarding the deployment of 4G and 5G networks, provide a detailed comparison featuring their main advantages and showcasing potential defects and support the academic community, offering the required data to help choose the necessary one.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Network simulation is a technique of utmost importance to evaluate new network performance, verify new algorithms and analyze various network topologies. It is used to find results to be expected from a hardware setup without the need for actual implementation. For this reason, there is a plethora of Network Simulation Software applied to different scenarios to evaluate theories and hypotheses. A cellular network is an example of an extremely complex system in which different components impact the overall performance in different ways. The aim of this paper is to study the most common Simulators regarding the deployment of 4G and 5G networks, provide a detailed comparison featuring their main advantages and showcasing potential defects and support the academic community, offering the required data to help choose the necessary one.
Bouras, Christos; Gkamas, Apostolos; Kokkinos, Vasileios; Papachristos, Nikolaos
Geolocation analysis for SAR systems using LoRaWAN Journal Article
In: International Journal of Communication Systems, Wiley InterScience, pp. 1 - 16, 2020.
Abstract | Links | BibTeX | Tags:
@article{4487,
title = {Geolocation analysis for SAR systems using LoRaWAN},
author = {Christos Bouras and Apostolos Gkamas and Vasileios Kokkinos and Nikolaos Papachristos},
url = {https://telematics.upatras.gr/dac-4593/},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {International Journal of Communication Systems, Wiley InterScience},
pages = {1 - 16},
abstract = {Low Power Wide Area Network (LPWAN) technologies aiming to provide power-efficient solutions to the field of Internet of Things (IoT). Over the last years we have seen a significant development within the area of IoT applications. For many applications, the problem of localization (i.e. determine the physical location of nodes) is critical. An area study of such use case is also the rescue monitor systems. In this study, we start by describing a solution designed for the Long Range Wide Area Network (LoRaWAN) to localize position of IoT modules such as wearables used from vulnerable groups. Through performance study of the behavior of a LoRaWAN channel and using trilateration and RSSI information, the localization of an IoT wearable can be acquired within a small range. Routing people in need is one of the use cases the above mechanism could be integrated so as to be able to be tracked by familiar people. After that, we evaluate the usage of mathematical model of multilateration algorithms using Time Difference of Arrival (TDoA) as a solution for positioning over LoRaWAN. The research is carried out using simulations in Python by configuring the constant positions of the Gateways inside an outdoor area. The proposed algorithms can be integrated in application for tracking people at any time and especially routing people from vulnerable groups. Through multilateration and algorithm’s prediction, we can have an accuracy of 40-60m in location positioning, ideal for search and rescue use cases. We finally summarize the above algorithms’ estimation and general behavior in a SAR system.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Low Power Wide Area Network (LPWAN) technologies aiming to provide power-efficient solutions to the field of Internet of Things (IoT). Over the last years we have seen a significant development within the area of IoT applications. For many applications, the problem of localization (i.e. determine the physical location of nodes) is critical. An area study of such use case is also the rescue monitor systems. In this study, we start by describing a solution designed for the Long Range Wide Area Network (LoRaWAN) to localize position of IoT modules such as wearables used from vulnerable groups. Through performance study of the behavior of a LoRaWAN channel and using trilateration and RSSI information, the localization of an IoT wearable can be acquired within a small range. Routing people in need is one of the use cases the above mechanism could be integrated so as to be able to be tracked by familiar people. After that, we evaluate the usage of mathematical model of multilateration algorithms using Time Difference of Arrival (TDoA) as a solution for positioning over LoRaWAN. The research is carried out using simulations in Python by configuring the constant positions of the Gateways inside an outdoor area. The proposed algorithms can be integrated in application for tracking people at any time and especially routing people from vulnerable groups. Through multilateration and algorithm’s prediction, we can have an accuracy of 40-60m in location positioning, ideal for search and rescue use cases. We finally summarize the above algorithms’ estimation and general behavior in a SAR system.
Barri, Eirini; Bouras, Christos; Gkamas, Apostolos; Katsampiris, Spyridon
GuideMe: A Complete System for Indoor Orientation and Guidance Journal Article
In: International Journal of Smart Sensor Technologies and Applications (IJSSTA), IGI Global, vol. 1, pp. 36-53, 2020.
Abstract | Links | BibTeX | Tags:
@article{4567,
title = {GuideMe: A Complete System for Indoor Orientation and Guidance},
author = {Eirini Barri and Christos Bouras and Apostolos Gkamas and Spyridon Katsampiris},
url = {https://telematics.upatras.gr/guideme-a-complete-system-for-indoor-orientation-and-guidance-2/},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {International Journal of Smart Sensor Technologies and Applications (IJSSTA), IGI Global},
volume = {1},
pages = {36-53},
abstract = {The interest for indoor navigational systems is expanding daily with concerns among visually impaired people who cannot navigate safely indoors. The main goal of such systems is the localization and direction of the individual who has a wearable device that provides voice commands to navigate indoor buildings. This paper aims to present the design and the implementation of the GuideMe project. The GuideMe project’s goal is the design, implementation, and evaluation of a navigation system focused on people who face troubles in indoor moving utilizing a wearable device. Specifically, the focus group is people suffering from visual impairment. The person carrying the wearable device takes guidelines about the location from indoor ultrawide band (UWB) anchors. The commands provided are about indoor direction through voice commands, assisting him to avoid obstacles in his route. The authors present the architecture and the details of the various modules, which consist of the proposed indoor navigation system, and some initial evaluations of the proposed system yielding promising results.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The interest for indoor navigational systems is expanding daily with concerns among visually impaired people who cannot navigate safely indoors. The main goal of such systems is the localization and direction of the individual who has a wearable device that provides voice commands to navigate indoor buildings. This paper aims to present the design and the implementation of the GuideMe project. The GuideMe project’s goal is the design, implementation, and evaluation of a navigation system focused on people who face troubles in indoor moving utilizing a wearable device. Specifically, the focus group is people suffering from visual impairment. The person carrying the wearable device takes guidelines about the location from indoor ultrawide band (UWB) anchors. The commands provided are about indoor direction through voice commands, assisting him to avoid obstacles in his route. The authors present the architecture and the details of the various modules, which consist of the proposed indoor navigation system, and some initial evaluations of the proposed system yielding promising results.