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-networks02076nas a2200145   4500008004100000245004900041210004900090300000900139490000700148520160800155100002101763700002201784700002601806856009801832       2021                        eng d00aEnergy efficient mechanism for LoRa networks0 aEnergy efficient mechanism for LoRa networks  a1-130 v133 aInternet 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.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/energy-efficient-mechanism-lora-networks01587nas a2200121   4500008004100000245007300041210006900114520109100183100002101274700002201295700002601317856012201343       2021                        eng d00aEnergy Efficient Mechanism over LoRa for Search and Reuse operations0 aEnergy Efficient Mechanism over LoRa for Search and Reuse operat3 aSearch and Rescue (SAR) operations can be vastly benefited by the use of IoT and especially by Low Power Wide Area Networks (LPWAN) technologies, such as Long Range (LoRa). In this framework, the wearable device-based Search And Rescue system (WeSAR) project has been created. The main goals that WeSAR tries to improve are the localization accuracy and the energy efficiency of the wearable device. In this paper, the authors propose an energy-efficient mechanism for LoRa networks, taking into consideration the energy of a real wearable device, containing multiple sensors in a SAR scenario. In this work, we simulate the LoRa network, taking into consideration the various states of a wearable device and the impact of the sensors on the energy consumption, in order to have insights into the mechanism’s efficiency with multiple nodes, up to 500 nodes. The experiment results reveal significant reductions in the energy consumption of the wearable device and improvement of battery life, in urban and suburban conditions, and in stationary and no stationary node mobility models.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/energy-efficient-mechanism-over-lora-search-and-reuse-operations01485nas a2200133   4500008004100000245007900041210006900120260001800189520095100207100002101158700002201179700002601201856012401227       2021                        eng d00aExploring the energy efficiency for Search and Rescue operations over LoRa0 aExploring the energy efficiency for Search and Rescue operations  cApril 19 - 213 aThe Internet of Things (IoT) is one of the pioneering domains of Computer Science and Engineering, that comes to solve a plethora of real-life problems. One of the most promising technologies that aim to provide long-distance transmission while retaining energy consumption at low levels, is Long Range (LoRa). In this paper, a thorough study of the energy efficiency in LoRa based Search and Rescue (SAR) project for people with special needs, called Wearable based Search And Rescue system (WeSAR) is presented. After research the authors propose a LoRa based system, taking into consideration the energy efficiency. The results of the proposed mechanism are encouraging in terms of energy consumption, and the battery can last enough for the majority of the SAR operations, even when the battery is not fully charged. Also, there is no deterioration in terms of the delivery ratio of the network which is important for localization algorithms.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/exploring-energy-efficiency-search-and-rescue-operations-over-lora01828nas a2200133   4500008004100000245005800041210005700099520134700156100001801503700002101521700002201542700002601564856010401590       2021                        eng d00aGuideMe: A system for Indoor Orientation and Guidance0 aGuideMe A system for Indoor Orientation and Guidance3 aThe demand for indoor navigational systems is increasing daily. The use of navigational systems is ranging from smart cities and robots to visually impaired people support to navigate safely. The GuideMe Project aims to provide guidance and security for people suffering from blindness, and in the time being it is in the final development stage. This paper presents GuideMe Project goals GuideMe Project architecture and GuideMe final prototype. GuideMe Project architecture consists of the wearable device curried the user has, the anchors with which the wearable device works to determine the position of the user, the smartphone that is informed by the system for the route the user must follow and converts the message into audio information through the user’s headset. The headset in order to guide the user in indoor places and the local server who controls the protocols, and the information are the last parts of the architecture. It is clear that the system is quite complex, it consists of several entities and requires them to work together harmoniously to provide the prescribed functionality, in real-time. All the technologies developed to this final system, each of which has multiple sub-entities as mentioned, handle the required functionality that is the provision orientation of users who are located and moving indoors.1 aBarri, Eirini1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/guideme-system-indoor-orientation-and-guidance01580nas a2200133   4500008004100000245005800041210005700099520109700156100001801253700002101271700002201292700002601314856010601340       2021                        eng d00aGuideMe: A system for Indoor Orientation and Guidance0 aGuideMe A system for Indoor Orientation and Guidance3 aThe interest for indoor navigational systems is expanding daily, and concerns among others visually impaired people that cannot navigate safely indoors. The main goal of such systems is to localize and direct the individual that has a wearable device and provide voice commands to navigate indoor buildings. This paper's aims to present the design and the implementation of the GuideMe project. GuideMe project’s goal is the design, implementation and evaluation of a navigation system focused on people that 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. We present the architecture and the details of the various modules which consist of the proposed indoor navigation system, and finally, some initial evaluations of the proposed system yield promising results.1 aBarri, Eirini1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/guideme-system-indoor-orientation-and-guidance-001249nas a2200121   4500008004100000245007300041210006900114520075500183100002100938700002200959700002600981856012001007       2021                        eng d00aHCI preliminary study and implementation for a LoRa based SAR system0 aHCI preliminary study and implementation for a LoRa based SAR sy3 aThe subject of this paper is the study and implementation of a Long Range (LoRa) based Search and Rescue system that can help in the localization of people having a high risk of going missing. These people may suffer from dementia, attention disturbance, and distraction, or disease in the autism spectrum, and it is of great importance to be found in a specific time frame, as their life can be in danger. The system is based on LoRa network architecture that enables both long-range communication and low energy consumption. In this paper aspects of the human-computer interaction were taken into consideration in contrast to the majority of the related papers, and is the proposed system is evaluated using heuristic evaluation and questionnaires.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/hci-preliminary-study-and-implementation-lora-based-sar-system01726nas 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-networks01654nas a2200157   4500008004100000245006700041210006600108300001000174490000600184520110600190100001801296700002101314700002201335700002601357856011301383       2020                        eng d00aGuideMe: A Complete System for Indoor Orientation and Guidance0 aGuideMe A Complete System for Indoor Orientation and Guidance  a36-530 v13 aThe 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.1 aBarri, Eirini1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/guideme-complete-system-indoor-orientation-and-guidance01911nas a2200157   4500008004100000245007300041210006900114520131600183100002101499700001801520700002201538700002401560700002201584700002601606856012101632       2020                        eng d00aGuideMe: A Networked Application for Indoor Orientation and Guidance0 aGuideMe A Networked Application for Indoor Orientation and Guida3 aToday’s indoor navigational systems are more and more in demand, commonly used for applications such as smart cities, robots and visually impaired people. As far as outdoor navigation is concerned, the Global Positioning System (GPS) technology is still one of the most (if not the most) commonly used approaches. Even though it is still considered an ideal solution for navigating in outdoor areas, challenges and problems arise when GPS is considered for navigation inside buildings due to obstacles (e.g., shopping malls, hospitals, etc.) and because signals cannot be absorbed by the building walls. To tackle the aforementioned issue, other technologies have emerged aimed at indoor navigation, such as Wireless-Fidelity (Wi-Fi), Bluetooth and sensors. This paper’s contribution is towards indoor navigation and, more specifically, it targets designing and developing a tracking and navigation system aimed at people that experience difficulties in indoor orientation using a wearable device. The user takes direction from the wearable device for the indoor orientation through voice commands helping him to avoid obstacles. The central part of the system is a device that provides the ability to navigate and find a route by voice commands, based on the device's location and orientation capabilities.1 aBouras, Christos1 aBarri, Eirini1 aGkamas, Apostolos1 aKoulouri, Christina1 aMichos, Evangelos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/guideme-networked-application-indoor-orientation-and-guidance-001903nas a2200157   4500008004100000245007300041210006900114520131000183100001801493700002101511700002201532700002401554700002201578700002601600856011901626       2020                        eng d00aGuideMe: A Networked Application for Indoor Orientation and Guidance0 aGuideMe A Networked Application for Indoor Orientation and Guida3 aToday’s indoor navigational systems are more and more in demand, commonly used for applications such as smart cities, robots and visually impaired people. As far as outdoor navigation is consider, the Global Positioning System (GPS) technology is still one of the most (if not the most) commonly used approaches. Even though it is still considered an ideal solution for navigating in outdoor areas, challenges and problems arise when GPS is considered for navigation inside buildings due to obstacles (e.g., shopping malls, hospitals, etc.) and because signals cannot be absorbed by the building walls. To tackle the aforementioned issue, other technologies have emerged aimed at indoor navigation, such as Wireless-Fidelity (Wi-Fi), Bluetooth and sensors. This paper’s contribution is towards indoor navigation and more specifically, it targets at designing and developing a tracking and navigation system aimed at people that experience difficulties in indoor orientation using a wearable device. The user takes direction from the wearable device for the indoor orientation through voice commands helping him to avoid obstacles. The central part of the system is a device that provides the ability to navigate and route by voice commands, based on the device's location and orientation capabilities.1 aBarri, Eirini1 aBouras, Christos1 aGkamas, Apostolos1 aKoulouri, Christina1 aMichos, Evangelos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/guideme-networked-application-indoor-orientation-and-guidance01333nas 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-device02020nas a2200157   4500008004100000245007800041210006900119520142200188100001801610700002101628700002201649700002401671700002201695700002601717856011901743       2020                        eng d00aText to Speech through Bluetooth for People with Special Needs Navigation0 aText to Speech through Bluetooth for People with Special Needs N3 aAs far as outdoor navigation is considered, the Global Positioning System (GPS) technology is still one of the most (if not the most) commonly used approaches. Even though it is still considered an ideal solution for navigating in outdoor areas, challenges and problems arise when GPS is considered for navigation inside buildings due to the fact that GPS signals cannot penetrate walls/ceilings (e.g., shopping malls, hospitals, etc.) and because signals can be absorbed by the building walls. This paper’s contribution is navigation system that assists people with special needs using an audio guidance system that incorporates input from a voice recognition system. The central part of the system is a device that is able to identify the position and orientation of the person that carries it and provide the ability to navigate and route by voice commands. The suggested voice synthesis system is used, so as to guide the user through obstacles in indoor locations. The information of the precise location and.orientation of the device is made available to the whole system, through the building’s network infrastructure, so that the user’s mobile phone, been connected to the same network and also to the user’s headset through BLE, is able to send audio commands. For the voice commands, Google Cloud Text-ToSpeech (TTS) will be used, supposed that an online connection is active on the user’s device.1 aBarri, Eirini1 aBouras, Christos1 aGkamas, Apostolos1 aKoulouri, Christina1 aMichos, Evangelos1 aKatsampiris, Spyridon  uhttp://telematics.upatras.gr/telematics/publications/text-speech-through-bluetooth-people-special-needs-navigation01475nas a2200157   4500008004100000245004700041210004700088260001900135300001200154520096100166100002101127700002201148700002601170700002401196856009701220       2019                        eng d00aComparison of LoRa Simulation Environments0 aComparison of LoRa Simulation Environments  cNovember 7 - 9  a374-3853 aInternet of Things (IoT) is used more and more in our everyday life, connecting different wireless devices, and their distance can vary from some centimeters to many kilometers. New IoT technologies such as Long Range (LoRa) are emerging enabling power efficient wireless communication over very long distances. Simulation of LoRa networks is quite important, because can be used for the design and the evaluation of LoRa based application without the need of costly implementations or before to proceed to the actual implementation of the system. Choosing the right parameters of the systems like spreading factor can improve the energy consumption of the wireless devices. This paper presents the most important LoRa simulation environments available in the literature and after that, we present a comparative evaluation of LoRa simulation environments. The benefits, the disadvantages and the highlights of each LoRa simulation environment is presented.1 aBouras, Christos1 aGkamas, Apostolos1 aKatsampiris, Spyridon1 aKokkinos, Vasileios  uhttp://telematics.upatras.gr/telematics/publications/comparison-lora-simulation-environments