01717nas a2200157 4500008004100000245009900041210006900140300001200209490000700221520109500228100002101323700002201344700002601366700002701392856014001419 2021 eng d00aA Comparative Study of Machine Learning Models for Spreading Factor Selection in LoRa Networks0 aComparative Study of Machine Learning Models for Spreading Facto a100-1210 v103 aLow 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.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/comparative-study-machine-learning-models-spreading-factor-selection-lora-networks02470nas a2200133 4500008004100000245006700041210006700108520195000175100002102125700002202146700002402168700002702192856011702219 2021 eng d00aPerformance Evaluation of Monitoring IoT Systems using LoRaWan0 aPerformance Evaluation of Monitoring IoT Systems using LoRaWan3 aThe 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.1 aBouras, Christos1 aGkamas, Apostolos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/performance-evaluation-monitoring-iot-systems-using-lorawan01478nas a2200157 4500008004100000245007200041210006900113260002100182300001200203520089400215100002101109700002201130700002401152700002701176856011701203 2021 eng d00aReal - Time Geolocation Approach through LoRa on Internet of Things0 aReal Time Geolocation Approach through LoRa on Internet of Thing cJanuary 13 - 16, a186-1913 aInternet of Things (IoT) and wireless technologies like LoRa brought more opportunities for application development in a plethora of different fields. One of these is location estimation of real-time objects and people. In this study, we focus on monitoring user’s location through a wearable IoT device with LoRa connectivity. The paper presents the development and integration of an loT ecosystem (Hardware and Software) which can be used in Search and Rescue (SAR) use cases. The proposed IoT ecosystem is evaluated and deployed inreal-scenarios with established gateways. After that we compare the existed location-estimation methods in terms of attenuation problem, cost and operation as well to conclude to the most suitable solution that can be integrated in LoRaWAN environments. Finally, the conclusions of this work and improvements for possible future activity are described.1 aBouras, Christos1 aGkamas, Apostolos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/real-time-geolocation-approach-through-lora-internet-things01726nas a2200133 4500008004100000245008000041210006900121520118000190100002101370700002201391700002601413700002701439856012601466 2021 eng d00aSpreading Factor Analysis for LoRa networks: A supervised learning approach0 aSpreading Factor Analysis for LoRa networks A supervised learnin3 aToday, the Internet of Things (IoT) has been introduced in our lives, giving a variety of solutions and applications. The critical requirements for de-vices connected to the IoT are long battery life, long coverage, and low de-ployment cost. Some applications require the transmission of data over long distances, thus Low Power Wide Area Networks (LPWAN) have emerged, with LoRa being one of the most popular players of the market. In order, to improve energy consumption and connectivity problems, machine learning can be used in LoRa networks. In this paper, we intend to improve the energy consumption of end nodes by using machine learning models. For this reason, we present a comparison of classification algorithms, specifically, the k-NN, the Naïve Bayes, and Support Vector Machines (SVM), for the Spreading Factor (SF) as-signment in LoRa networks. The simulation results indicate that, both energy efficiency and reliability in IoT communications could be significantly im-proved using the proposed learning approach. These promising results, which are achieved using lightweight learning, make our solution favorable in many low-cost low-power IoT applications.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/spreading-factor-analysis-lora-networks-supervised-learning-approach01713nas a2200145 4500008004100000245007700041210006900118300001200187520114600199100002101345700002201366700002601388700002701414856012601441 2021 eng d00aSpreading Factor Selection Mechanism for Transmission over LoRa Networks0 aSpreading Factor Selection Mechanism for Transmission over LoRa  a344-3533 aThis paper presents a mechanism for Spreading Factor (SF) prediction in LoRa networks for more optimized data transmissions. The proposed mechanism is based on Machine Learning (ML) algorithms and assigns the node’s SF value based on prior transmission data. This paper examines three different approaches for the selection of the SF during LoRa transmissions a) Random SF assignment b) Adaptive Data Rate (ADR) and c) ML based SF selection. The main target is to study and determine the most efficient approach, as well as to investigate the exploitation of ML techniques in the context of LoRa networks. We created a simple library based on ML libraries, such as Scikit Learn that can be used with the FLoRa an OMNeT++ based LoRa simulator. With the use of this library, it is possible to predict the node’s SF using ML techniques. Two classification algorithms were tested, the k Nearest Neighbors (k-NN) and Naïve Bayes classifier. Finally, we compared the ML mechanisms with two variants of the ADR mechanism. The approaches performance is evaluated for different scenarios, using the delivery ratio and energy consumption metrics.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/spreading-factor-selection-mechanism-transmission-over-lora-networks02112nas a2200133 4500008004100000245005500041210005500096520162900151100002101780700002201801700002401823700002701847856010401874 2020 eng d00aGeolocation analysis for SAR systems using LoRaWAN0 aGeolocation analysis for SAR systems using LoRaWAN3 aLow 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.1 aBouras, Christos1 aGkamas, Apostolos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/geolocation-analysis-sar-systems-using-lorawan01061nas a2200133 4500008004100000245004600041210004600087520060100133100002100734700002200755700002400777700002700801856009900828 2020 eng d00aIoT Geolocation Performance Using LoRaWAN0 aIoT Geolocation Performance Using LoRaWAN3 aLow Power Wide Area Network (LPWAN) technologies aiming to provide power-efficient solutions to the world of IoT. This paper describes a solution based on the Long Range Wide Area Network (LoRaWAN) technology to geolocalise IoT modules such as wearables used from vulnerable groups. Through estimation of the behavior of a LoRaWAN channel and using trilateration and RSSI information, the localization of an IoT wearable can be obtained 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.1 aBouras, Christos1 aGkamas, Apostolos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/iot-geolocation-performance-using-lorawan01333nas a2200145 4500008004100000245006100041210006000102300001200162520080600174100002100980700002201001700002601023700002701049856011101076 2020 eng d00aSearch and Rescue System Based on NB-IoT Wearable Device0 aSearch and Rescue System Based on NBIoT Wearable Device a195-2223 aThis chapter presents the design and development of a search and rescue (SAR) system, for the location and provision of aid to people who are missing or in imminent danger, especially those belonging to population groups with a particularly high probability of getting lost. With the use of Low-Power Wide Area Network (LPWAN) technology, such as Narrow Band Internet of Things (NB-IoΤ), authors are able to provide search and rescue solutions for individuals, especially those belonging to groups of people who are more likely to get lost. The central part of the system is a modular “wearable (portable)” device, while in the framework of the implementation of this system authors have seriously taken into consideration the aspects of energy efficiency in order to provide better battery life.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/search-and-rescue-system-based-nb-iot-wearable-device01450nas a2200133 4500008004100000245007900041210006900120520090800189100002101097700002201118700002401140700002701164856012501191 2020 eng d00aTime Difference of Arrival Localization Study for SAR Systems over LoRaWAN0 aTime Difference of Arrival Localization Study for SAR Systems ov3 aOver the last years we have seen a rapid expansion within the area of Internet of Things (IoT) applications. For many applications’ use cases, such as rescue monitor systems, the problem of localization (i.e. determine the physical location of nodes) is critical. This paper studies and evaluates the usage of mathematical model of multilateration algorithms using Time Difference of Arrival (TDoA) as a solution for positioning over Long Range Wide Area Network (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.1 aBouras, Christos1 aGkamas, Apostolos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/time-difference-arrival-localization-study-sar-systems-over-lorawan01932nas a2200157 4500008004100000245005300041210005300094260001800147300001200165520140100177100002101578700002201599700002401621700002701645856010201672 2019 eng d00aUsing LoRa Technology for IoT Monitoring Systems0 aUsing LoRa Technology for IoT Monitoring Systems cOctober 1 - 3 a134-1373 aThis paper presents technology comparison scenarios for Internet of Things (IoT) concepts on rescue monitoring. The study starts by comparing WiFi & LoRa as wireless technologies able to be used by smart devices for data transmission. The IoT end-devices used in these concepts have high requirements in battery saving and for this reason the usage of low-power modules is advisable. This paper focus in rescue monitoring and the goal in the current study is the usage of the two wireless technologies used for data transmission from IoT devices: the already known WiFi and the upcoming LoRa technology. During rescue monitoring, important concepts are the identification and individuals' rescue of particularly vulnerable groups or individuals belonging to population groups with a high probability of being lost. A LoRa based gateway and WiFi Router is used to connect the end-devices used in our scenarios to the Internet. The collected data on server application as captured from installed sensors on the IoT modules can be displayed to authorized users through a web or mobile application. The results through simulation and real time experiments indicate that LoRa could be an ideal candidate for rescue monitoring. This study is a first step in creating a more general ecosystem for rescue concepts including all the hardware and software using the LoRa technology as transmission method.1 aBouras, Christos1 aGkamas, Apostolos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/using-lora-technology-iot-monitoring-systems01689nas a2200169 4500008004100000245007100041210006800112300000900180490000600189520109900195100001801294700002101312700002401333700002701357700001901384856011601403 2019 eng d00aWiFiMon - A Tool for Wi-Fi Performance Monitoring and Verification0 aWiFiMon A Tool for WiFi Performance Monitoring and Verification a1-180 v83 aMeasuring network quality of a wireless network as experienced by end-users is quite difficult, as there isn’t a single tool available that can record measurements on all sides of the system. The approach presented in this research work is based on the end-user feedback, giving the opportunity of visualization of network performance in real time. We initially present an overview of the developed tool, called WiFiMon, which has the ability to capture, record measurements and export statistics on the quality of Wi-Fi network as perceived by the end-users. The measurements are initiated by the end-users - without their intervention – after they visit a web page or use a mobile application. WiFiMon aims to give a clear understanding of the Wi-Fi network conditions by measuring specific parameters of the network, such as download/upload throughput, and correlate these measurements with raw data from various log files to obtain additional information regarding the performance of specific access points. The results reveal the functionality of the proposed tool and its scalability.1 aBaumann, Kurt1 aBouras, Christos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos1 aStamos, Kostas uhttp://telematics.upatras.gr/telematics/publications/wifimon-tool-wi-fi-performance-monitoring-and-verification01690nas a2200157 4500008004100000245007900041210006900120490000700189520108500196100002101281700002201302700002401324700002701348700002801375856012901403 2018 eng d00aMCS Selection Exploiting Femtocells Utilization in Multicast Transmissions0 aMCS Selection Exploiting Femtocells Utilization in Multicast Tra0 v313 aMulticast-Broadcast over Single Frequency Network (MBSFN) technology, as introduced by the Long Term Evolution Advanced (LTE-A) group, is expected to be part of the upcoming cellular systems offering resource efficiency to broadcast services. MBSFN transmission is suitable to serve multicast groups searching the same content. In addition, the fast emerging technology of femtocells networks and their hybrid nature can lead to efficient resource sharing between non-subscribed users when located inside their coverage. The focus of this manuscript is twofold; firstly, we have contacted simulation experiments to compare the MBSFN transmission with the traditional PTP transmission for various femtocell distributions and network topology changes; secondly, a novel multicast transmissions mechanism is proposed from non-subscribed users who exploit femtocells resources for broadcast services, without limiting user’s data requirements. The simulation results lead to a significant system’s performance in terms of average throughput, total capacity and energy consumption.1 aBouras, Christos1 aKanakis, Nikolaos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos1 aVouyioukas, Demosthenes uhttp://telematics.upatras.gr/telematics/publications/mcs-selection-exploiting-femtocells-utilization-multicast-transmissions01518nas a2200121 4500008004100000245008000041210006900121520100700190100002101197700002401218700002701242856012701269 2018 eng d00aPerformance evaluation of LoraWan physical layer integration on IoT devices0 aPerformance evaluation of LoraWan physical layer integration on 3 aDue to the constant motion of wireless devices in the Internet of Things (IoT), infrastructure wireless networks cannot provide connectivity at all times, in comparison with ad hoc networks, which are more easy to use and are based on abstract and continuously altering topologies. LoraWan, as a Long Range Wide Area Network specification recommended by the LoRa Alliance, is a low power and long distance communication protocol suitable for IoT environments and applications to different domains such as healthcare and smart farming. This IoT concept is gaining a rapid growth on the IoT market and is simultaneously improving our living environment. In this paper, we first briefly introduce LoRa as an efficient solution of physical layer integration on the IoT devices. We then conduct a performance evaluation taking into consideration metrics such as bit error rate, time on air transmission based on Signal to Noise Ratio (SNR) and Spreading Factors modifications for different bandwidth values.1 aBouras, Christos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/performance-evaluation-lorawan-physical-layer-integration-iot-devices01359nas a2200169 4500008004100000245007900041210006900120260001800189520072700207100002100934700002300955700002400978700002401002700002001026700002701046856011601073 2017 eng d00aExtension to Middleware for IoT Devices, with Applications in Smart Cities0 aExtension to Middleware for IoT Devices with Applications in Sma cApril 20 - 213 a

This work proposes extensions toWubby (a device-level software platform for IoT devices, a technology developed by Econais A.E.) to support wireless modules for mobile networks (4G / LTE-A, and also supporting the forthcoming 5G). The proposed extension leverages the use of such modules, as it allows easy programming and existing code re-use. It thus adds a compatibility layer across the di erent modules as it a common set of classes for the wireless modules. The system can be used to support the networking aspects of a variety of IoT applications, including applications for Smart Cities, using a variety of IoT devices. This work suggests such a case focusing on air quality monitoring.

1 aBouras, Christos1 aKapoulas, Vaggelis1 aKokkinos, Vasileios1 aLeonardos, Dimitris1 aPipilas, Costas1 aPapachristos, Nikolaos uhttp://telematics.upatras.gr/telematics/publications/extension-middleware-iot-devices-applications-smart-cities01575nas a2200157 4500008004100000245007400041210006900115260001400184520099100198100001801189700002101207700002401228700002701252700001901279856011901298 2017 eng d00aWiFiMon App Measuring Wi-Fi Performance as Experienced by End - Users0 aWiFiMon App Measuring WiFi Performance as Experienced by End Use cMay 3 - 53 a

The measurement of quality and efficiency of a wireless Wi-Fi network is particularly difficult, as there is not a single tool that can record measurements from all sides of the system, i.e. from both the access point and the end-user. Existing tools are able to monitor the overall quality of the wireless network; although they cannot determine how end-users experience the quality of Wi-Fi in a particular part of the network at a given time. In this paper we present a novel tool, named WiFiMon, which enables measuring, recording and exporting statistics regarding the quality of a Wi-Fi network as experienced by the end-users. The measurements are triggered by the end-users when they visit WiFiMon-enabled websites and/or run WiFiMon-enabled mobile applications and are recorded without users’ intervention. Main goal of WiFiMon is to give network administrators a better overview on how the endusers experience the conditions of the Wi-Fi network.

1 aBaumann, Kurt1 aBouras, Christos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos1 aStamos, Kostas uhttp://telematics.upatras.gr/telematics/publications/wifimon-app-measuring-wi-fi-performance-experienced-end-users01409nas a2200169 4500008004100000245009200041210006900133260002100202300001200223520074900235100002100984700001901005700002401024700002701048700002801075856013601103 2016 eng d00aComparison of Point to Point and MBSFN transmissions in Next Generation Mobile Networks0 aComparison of Point to Point and MBSFN transmissions in Next Gen cNovember 13 - 17 a169-1723 a

Multicast/Broadcast Multicast Service over Single Frequency Network (MBSFN) technology has introduced advanced broadcast capabilities to cellular systems. In Long Term Evolution Advanced (LTE-A) systems, MBSFN transmission accommodates multicast groups in search of the same data. In this paper we compare the traditional Point-to-Point (PTP) communication with the MBSFN services through simulation experiments for various femtocell distributions and network configurations. The comparison takes into account the average throughput, overhead cost, energy consumption and capacity gain, concluding that MBSFN through multicast transmission may guarantee performance improvement even for users in the cell boundaries.

1 aBouras, Christos1 aKanakis, Nikos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos1 aVouyioukas, Demosthenes uhttp://telematics.upatras.gr/telematics/publications/comparison-point-point-and-mbsfn-transmissions-next-generation-mobile-networks01723nas a2200169 4500008004100000245009400041210006900135260001700204300001200221520105700233100002101290700002201311700002401333700002701357700002801384856014101412 2016 eng d00aUtilization of Hybrid Access Femtocells During Multicast Transmissions in Mobile Networks0 aUtilization of Hybrid Access Femtocells During Multicast Transmi cJune 27 - 30 a190-1943 a

Femtocells enhance indoor coverage of mobile services using the owner’s broadband connection. They were initially designed to serve a number of subscribed User Equipments within their range. This design however, resulted in underutilization of the femtocells resources, and simultaneously in high interference levels for nearby non-subscribed users. Nowadays, femtocells can support multicast transmissions, while their hybrid operation allows non-subscribed users to use a portion of their resources. In this paper we propose a novel mechanism that is based on the selection of the appropriate Modulation and Coding Scheme. The mechanism allows non-subscribed users to utilize a portion of the femtocells’ resources for multicast transmissions when located inside their coverage, without affecting the owners’ satisfaction. The simulation results show that depending on the portion of the femtocells’ resources allocated to non-subscribed users, the mechanism may significantly increase the average user throughput.

1 aBouras, Christos1 aKanakis, Nikolaos1 aKokkinos, Vasileios1 aPapachristos, Nikolaos1 aVouyioukas, Demosthenes uhttp://telematics.upatras.gr/telematics/publications/utilization-hybrid-access-femtocells-during-multicast-transmissions-mobile-networks