A use case of low power wide area networks in future 5G healthcare applications

Abstract. The trend in all cellular evolution to the Long-Term Evolution (LTE) has always been to offer users continuously increasing data rates. However, the next leap forwards towards the 5th Generation Mobile Networks (5G) will be mainly addressing the needs of devices. Machines communicating with each other, sensors reporting to a server, or even machines communicating with humans, these are all different aspects of the same technology; the Internet of Things (IoT). The key differentiator between Machine-to-Machine (M2M) communications and IoT will be the added -feature of connecting devices and sensors not only to themselves, but also to the internet. The appropriate communications network is the key to allow this connectivity. Local Area Networks (LANs) and Wide Area Networks (WANs) have been thought of as enablers for IoT, but since they both suffered from limitations in IoT aspects, the need for a new enabling technology was evident. LPWANs are networks dedicated to catering for the needs of IoT such as providing low energy consumption for wireless devices. LPWANs can be categorized into proprietary LPWANs and cellular LPWANs. Proprietary LPWANs are created by an alliance of companies working together on creating a communications standard operating in unlicensed frequency bands. An example of proprietary LPWANs is LoRa. Whereas cellular LPWANs are standardized by the 3rd Partnership Project (3GPP) and they are basically versions of the LTE standard especially designed for machine communications. An example of cellular LPWANs is Narrowband IoT (NB IoT). This diploma thesis documents the usage of LoRa and NB IoT in a healthcare use case of IoT. It describes the steps and challenges of deploying an LTE network at a target site, which will be used by the LoRa and NB IoT sensors to transmit data through the 5G test network (5GTN) to a desired server location for storing and later analysis.Matalan tehonkulutuksen ja pitkänkantaman teknologian käyttötapaus tulevaisuuden 5G:tä hyödyntävissä terveydenhoidon sovelluksissa. Tiivistelmä. Pitemmän aikavälin tarkastelussa matkaviestintäteknologian kehittyminen nykyisin käytössä olevaan Long-Term Evolution (LTE) teknologiaan on tarkoittanut käyttäjille yhä suurempia datanopeuksia. Seuraavassa askeleessa kohti 5. sukupolven matkaviestintäverkkoja (5G) lähestytään kehitystä myös laitteiden tarpeiden lähtökohdista. Toistensa kanssa kommunikoivat koneet, palvelimille dataa lähettävät anturit tai jopa ihmisten kanssa kommunikoivat koneet ovat kaikki eri puolia samasta teknologisesta käsitteestä; esineiden internetistä (IoT). Oleellisin ero koneiden välisessä kommunikoinnissa (M2M) ja IoT:ssä on, että erinäiset laitteet tulevat olemaan yhdistettyinä paitsi toisiinsa myös internettiin. Tätä kytkentäisyyttä varten tarvitaan tarkoitukseen kehitetty matkaviestinverkko. Sekä lähiverkkoja (LAN) että suuralueverkkoja (WAN) on pidetty mahdollisina IoT mahdollistajina, mutta näiden molempien käsitteiden alle kuuluvissa teknologioissa on rajoitteita IoT:n vaatimusten lähtökohdista, joten uuden teknologian kehittäminen oli tarpeellista. Matalan tehonkulutuksen suuralueverkko (LP-WAN) on käsite, johon luokitellaan eri teknologioita, joita on kehitetty erityisesti IoT:n tarpeista lähtien. LP-WAN voidaan jaotella ainakin itse kehitettyihin ja matkaviestinverkkoihin perustuviin teknologisiin ratkaisuihin. Itse kehitetyt ratkaisut on luotu lukuisten yritysten yhteenliittymissä eli alliansseissa ja nämä ratkaisut keskittyvät lisensoimattomilla taajuuksilla toimiviin langattomiin ratkaisuihin, joista esimerkkinä laajasti käytössä oleva LoRa. Matkaviestinverkkoihin perustuvat lisensoiduilla taajuuksilla toimivat ratkaisut on puolestaan erikseen standardoitu 3GPP-nimisessä yhteenliittymässä, joka nykyisellään vastaa 2G, 3G ja LTE:n standardoiduista päätöksistä. Esimerkki 3GPP:n alaisesta LPWAN-luokkaan kuuluvasta teknologiasta on kapea kaistainen IoT-teknologia, NB-IoT. Tässä diplomityössä keskitytään terveydenhoidon käyttötapaukseen, missä antureiden mittaamaa tietoa siirretään langattomasti käyttäen sekä LoRa että NB-IoT teknologioita. Työssä kuvataan eri vaiheet ja haasteet, joita liittyi kun rakennetaan erikseen tiettyyn kohteeseen LTE-verkon radiopeitto, jotta LoRa:a ja NB-IoT:a käyttävät anturit saadaan välittämään mitattua dataa halutulle palvelimelle säilytykseen ja myöhempää analysointia varten. LTE-radiopeiton rakensi Oulun yliopiston omistama 5G testiverkko, jonka tarkoitus on tukea sekä tutkimusta että ympäröivää ekosysteemiä tulevaisuuden 5G:n kehityksessä

A Survey of Using Machine Learning in IoT Security and the Challenges Faced by Researchers

The Internet of Things (IoT) has become more popular in the last 15 years as it has significantly improved and gained control in multiple fields. We are nowadays surrounded by billions of IoT devices that directly integrate with our lives, some of them are at the center of our homes, and others control sensitive data such as military fields, healthcare, and datacenters, among others. This popularity makes factories and companies compete to produce and develop many types of those devices without caring about how secure they are. On the other hand, IoT is considered a good insecure environment for cyber thefts. Machine Learning (ML) and Deep Learning (DL) also gained more importance in the last 15 years; they achieved success in the networking security field too. IoT has some similar security requirements such as traditional networks, but with some differences according to its characteristics, some specific security features, and environmental limitations, some differences are made such as low energy resources, limited computational capability, and small memory. These limitations inspire some researchers to search for the perfect and lightweight security ways which strike a balance between performance and security. This survey provides a comprehensive discussion about using machine learning and deep learning in IoT devices within the last five years. It also lists the challenges faced by each model and algorithm. In addition, this survey shows some of the current solutions and other future directions and suggestions. It also focuses on the research that took the IoT environment limitations into consideration

Law in the present future : approaching the legal imaginary of smart cities with science (and) fiction

This doctoral research concerns smart cities, describing digital solutions and social issues related to their innovative technologies, adopted models, and major projects around the world. The many perspectives mentioned in it were identified by online tools used for the textual analysis of two databases that were built from relevant publications on the main subject by authors coming from media and academia. Expected legal elements emerged from the applied process, such as privacy, security, transparency, participation, accountability, and governance. A general review was produced on the information available about the public policies of Big Data in the two municipal cases of Rio de Janeiro and Montréal, and their regulation in the Brazilian and Canadian contexts. The combined approaches from science and literature were explored to reflect on the normative concerns represented by the global challenges and local risks brought by urban surveillance, climate change, and other neoliberal conditions. Cyberpunk Science Fiction reveals itself useful for engaging with the shared problems that need to be faced in the present time, all involving democracy. The results achieved reveal that this work was, in fact, about the complex network of practices and senses between (post)modern law and the imaginary of the future.Cette recherche doctorale centrée sur les villes intelligentes met en évidence les solutions numériques et les questionnements sociétaux qui ont trait aux technologies innovantes, ainsi qu’aux principaux modèles et projets développés autour d’elles à travers le monde. Des perspectives multiples en lien avec ces développements ont été identifiées à l’aide d’outils en ligne qui ont permis l’analyse textuelle de deux bases de données comprenant des publications scientifiques et des écrits médiatiques. De ce processus analytique ont émergé des éléments juridiques relatifs aux questions de vie privée, de sécurité, de transparence, de participation, d’imputabilité et de gouvernance. De plus, à partir de ces informations a été réalisée une revue des politiques publiques relatives aux mégadonnées dans les villes de Rio de Janeiro et de Montréal, ainsi que des réglementations nationales du Canada et du Brésil en lien avec ce sujet. Finalement, à travers l’exploration d’écrits scientifiques et fictionnels de la littérature, les principaux enjeux normatifs soulevés localement et mondialement par la surveillance urbaine, les changements climatiques et les politiques néolibérales ont pu être mis à jour. Le courant cyberpunk de la science-fiction s’est avéré particulièrement utile pour révéler les principaux problèmes politiques, en lien avec la préservation de la démocratie, auxquelles sont confrontées nos sociétés présentement. Les résultats de la recherche démontrent finalement la présence d’un réseau de pratiques et de significations entre le droit (post)moderne et les représentations imaginaires du futur

Computer-Mediated Communication

This book is an anthology of present research trends in Computer-mediated Communications (CMC) from the point of view of different application scenarios. Four different scenarios are considered: telecommunication networks, smart health, education, and human-computer interaction. The possibilities of interaction introduced by CMC provide a powerful environment for collaborative human-to-human, computer-mediated interaction across the globe

Internet of Things From Hype to Reality

The Internet of Things (IoT) has gained significant mindshare, let alone attention, in academia and the industry especially over the past few years. The reasons behind this interest are the potential capabilities that IoT promises to offer. On the personal level, it paints a picture of a future world where all the things in our ambient environment are connected to the Internet and seamlessly communicate with each other to operate intelligently. The ultimate goal is to enable objects around us to efficiently sense our surroundings, inexpensively communicate, and ultimately create a better environment for us: one where everyday objects act based on what we need and like without explicit instructions

The Cloud-to-Thing Continuum

The Internet of Things offers massive societal and economic opportunities while at the same time significant challenges, not least the delivery and management of the technical infrastructure underpinning it, the deluge of data generated from it, ensuring privacy and security, and capturing value from it. This Open Access Pivot explores these challenges, presenting the state of the art and future directions for research but also frameworks for making sense of this complex area. This book provides a variety of perspectives on how technology innovations such as fog, edge and dew computing, 5G networks, and distributed intelligence are making us rethink conventional cloud computing to support the Internet of Things. Much of this book focuses on technical aspects of the Internet of Things, however, clear methodologies for mapping the business value of the Internet of Things are still missing. We provide a value mapping framework for the Internet of Things to address this gap. While there is much hype about the Internet of Things, we have yet to reach the tipping point. As such, this book provides a timely entrée for higher education educators, researchers and students, industry and policy makers on the technologies that promise to reshape how society interacts and operates

Personalized data analytics for internet-of-things-based health monitoring

The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources. There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements. For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed. This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months