Remote biometrical monitoring system via IoT

Os sistemas de Internet of Things (IoT) estão a experienciar um rápido crescimento devido à sua aplicabilidade em vários domínios, desde cidades inteligentes até aos cuidados de saúde. Nestes sistemas, os dispositivos comunicam entre si, ou com a infraestrutura, recorrendo a comunicações machine-to-machine (M2M). Uma vez que muitos destes dispositivos são simples, com escassa capacidade de processamento, foram desenvolvidos protocolos M2M como o Constrained Application Protocol (CoAP) e o Messaging Queue Telemetry Transport (MQTT), bem como frameworks de suporte de comunicações M2M. Apesar dos desenvolvimentos nesta tecnologia, ainda são encontrados desafios no desenvolvimento de aplicações M2M e IoT a nível da interoperabilidade, escalabilidade e padronização, por exemplo. Consequentemente, vários standards M2M foram desenvolvidos para superar estes desafios, sendo o oneM2M um deles. Atualmente, existem vários dispositivos disponíveis com uma interface WiFi embebida, o que significa que quando inseridos num sistema IoT, não necessitam de uma gateway (GW) para o acesso à Internet, uma vez que o WiFi é uma tecnologia omnipresente na sociedade atual. Esta é uma característica fundamental visto que diminui o custo global do sistema. Além disso, estes dipositivos, como o módulo ESP32, oferecem modos de poupança de energia que permitem explorar recursos de gestão de energia definidos pelo standard IEEE 802.11. As instituições de cuidados de saúde procuram oferecer os melhores serviços em termos de confiabilidade, segurança e conforto aos seus pacientes. Recentemente, tecnologias IoT foram abordadas, desenvolvidas e utilizadas para melhorar o serviço aos pacientes. O trabalho proposto nesta dissertação é um sistema de monitorização contínua via IoT capaz de monitorizar os sinais vitais de um paciente e apresentá-los aos profissionais de saúde. Para além disso, o sistema pode ser utilizado em diversos cenários desde salas de emergência, uso doméstico até à competição desportiva. O sistema possui dois componentes principais: um dispositivo wearable com uma antena WiFi e um sistema de monitorização orientado ao profissional de saúde. O wearable é composto por um sensor fotopletismográfico (PPG) MAX30100/MAX30102 para medir o ritmo cardíaco e os níveis de saturação de oxigénio no sangue, um ESP32 com uma antena WiFi incorporada para processar e enviar os dados do sensor para o sistema de monitorização e, finalmente, uma bateria de Lítio Polímero (LiPo) para fornecer energia aos dois componentes mencionados. No que refere ao sistema de monitorização, este é composto por uma base de dados orientada a eventos temporais para armazenar todos os dados necessários, um software de visualização gráfica para a visualização dos sinais vitais do paciente e, por fim, uma Interface Gráfica com o objetivo de ser um painel de controlo para todo o sistema. Para além disso, o sistema segue a norma oneM2M devido a questões de interoperabilidade relativas à arquitetura, e implementa o modelo de comunicação publisher-subscriber pois este é eficiente em termos de sensorização e monitorização remota. Por último, o objetivo desta dissertação é desenvolver um sistema de monitorização de baixo custo focado na gestão energética e que ao mesmo tempo não comprometa a sua confiabilidade e robustez.Internet of Things (IoT) systems are experiencing rapid growth due to their applicability in several domains, from smart cities to healthcare among many. In these systems, devices communicate with each other, or with infrastructure, resorting to machine-to-machine (M2M) communications. Since many of these devices are simple systems, with weak processing capacity, lightweight M2M protocols were developed such as Constrained Application Protocol (CoAP) and Messaging Queue Telemetry Transport (MQTT) as well as frameworks to support M2M communications. As expected, there are challenges when developing M2M and IoT applications: interoperability, scalability, standardisation, among others. Therefore, several M2M standards were created to overcome these issues, with oneM2M being one of them. Nowadays, there are multiple devices available that have an embedded WiFi interface, thus, when inserted in an IoT system, these devices do not need a gateway (GW) to access the Internet since WiFi is one of the most common technologies at Internet boundary. This is a key feature because it increases the system's pervasiveness as well as the overall cost of the system. Additionally, these devices, such as the ESP32 module, offer sleep modes that allow exploiting the power management features by the IEEE 802.11 standard. Healthcare institutions always strive to provide the best services concerning the reliability, safety and comfort of the patients. To do so, IoT technologies have been embraced and developed in recent years to improve these services. The work proposed in this dissertation is an end-to-end continuous monitoring system via IoT capable of monitoring a patient's vital signs and displaying them to the medical personnel. Moreover, the system can be applied to a wide range of application scenarios from emergency wards and home environment to sports training and competition. The system has two major components, a low-cost and low-power WiFi-enabled wearable device for the user and, at the upper end, a monitoring interface for the medical personnel. The wearable is composed by a MAX30100/MAX30102 PhotoPletysmoGraphy (PPG) sensor to measure the heart rate and oxygen saturation levels, an ESP32 with a built-in WiFi antenna to process and send the sensor data to the monitoring system and, finally, a Lithium Polymer (LiPo) battery to power-up the previous two components. At the upper end, the monitoring interface is composed of a time-series database to store all the data, a graphics visualisation software of patient's vital signs and a Graphic User Interface (GUI) serving as a control panel. Additionally, the system relies on the oneM2M standard for the interoperability concerning the architecture and follows a publish-subscribe communication model due to its efficiency in sensing and remote monitoring. Furthermore, the goal of this dissertation is to develop a low-cost and energy-efficient monitoring system while not compromising the reliability and robustness of traditional machines and systems

IoT Data Processing for Smart City and Semantic Web Applications

The world has been experiencing rapid urbanization over the last few decades, putting a strain on existing city infrastructure such as waste management, water supply management, public transport and electricity consumption. We are also seeing increasing pollution levels in cities threatening the environment, natural resources and health conditions. However, we must realize that the real growth lies in urbanization as it provides many opportunities to individuals for better employment, healthcare and better education. However, it is imperative to limit the ill effects of rapid urbanization through integrated action plans to enable the development of growing cities. This gave rise to the concept of a smart city in which all available information associated with a city will be utilized systematically for better city management. The proposed system architecture is divided in subsystems and is discussed in individual chapters. The first chapter introduces and gives overview to the reader of the complete system architecture. The second chapter discusses the data monitoring system and data lake system based on the oneM2M standards. DMS employs oneM2M as a middleware layer to achieve interoperability, and DLS uses a multi-tenant architecture with multiple logical databases, enabling efficient and reliable data management. The third chapter discusses energy monitoring and electric vehicle charging systems developed to illustrate the applicability of the oneM2M standards. The fourth chapter discusses the Data Exchange System based on the Indian Urban Data Exchange framework. DES uses IUDX standard data schema and open APIs to avoid data silos and enable secure data sharing. The fifth chapter discusses the 5D-IoT framework that provides uniform data quality assessment of sensor data with meaningful data descriptions

Interoperability in IoT

Interoperability refers to the ability of IoT systems and components to communicate and share information among them. This crucial feature is key to unlock all of the IoT paradigm´s potential, including immense technological, economic, and social benefits. Interoperability is currently a major challenge in IoT, mainly due to the lack of a reference standard and the vast heterogeneity of IoT systems. IoT interoperability has also a significant importance in big data analytics because it substantively eases data processing. This chapter analyzes the critical importance of IoT interoperability, its different types, challenges to face, diverse use cases, and prospective interoperability solutions. Given that it is a complex concept that involves multiple aspects and elements of IoT, for a deeper insight, interoperability is studied across different levels of IoT systems. Furthermore, interoperability is also re-examined from a global approach among platforms and systems.González-Usach, R.; Yacchirema-Vargas, DC.; Julián-Seguí, M.; Palau Salvador, CE. (2019). Interoperability in IoT. Handbook of Research on Big Data and the IoT. 149-173. http://hdl.handle.net/10251/150250S14917

Medical application of the Internet of Things (IoT): prototyping a telemonitoring system

The Internet of Things (IoT) is a technological paradigm that can be perceived as an evolution of the internet. It is a shift from the traditional way of connecting devices to the internet, both in number and diversity of connected devices. This significant and marked growth in the number and diversity of devices connected to the internet has prompted a rethink of approaches to interconnect devices. The growth in the number of connected devices is driven by emerging applications and business models and supported by falling device costs while the growth in the diversity is driven by the reduction in the cost of manufacturing these devices. This has led to an increase in the number of users (not limited to people) of the internet. According to statistics by the ITU, by the end of 2015, about 3.2 billion people were using the Internet. Significantly, 34% of households in developing countries had Internet access, with more than 80% of households in developed countries. This indicates that it is realistic to leverage the IoT in living spaces. Appreciating this potential, many sectors of society are already positioning themselves to reap the benefits of this great promise. Hence the health sector would do well to adopt this technological paradigm to enhance service delivery. One specific area where the health sector can benefit from the adoption of the IoT is in telemonitoring and the associated early response to medical emergencies. Statistics and research show that there are areas in the medical field, that still need improvement to enhance service delivery. The Nursing Times has summed up these areas into four categories. The first one is a need to have a regular observation of patients and their vital signs. Here, health service providers (SPs) need to adopt creative and non-obtrusive methods that will encourage patients' participation in the monitoring of these vital signs. As much as possible, vital signs readings should be taken at convenient locations and times. Therefore, devices that have consistent internet access and are usually a part of daily life for most patients, such as the mobile phones would prove to be a key enabler of regular observation of vital signs. Furthermore, miniaturization of the vital signs monitoring or sensing devices would be a key step towards realizing this scenario. A lot of work is already being done to miniaturize these devices and make them as much a part of daily life as possible, as evidenced by advancements in the field of fitness and wearables. To map this use to the medical field, a system needs to be created that would allow for the aggregation of these disparate measuring and monitoring devices with medical information management systems. The second potential area of improvement is in the early recognition of deterioration of the patients. With regular observation of patients, it is possible to recognize deterioration at its early stage. Taking cognizance of the different needs of the various stakeholders is important to achieve the intended results. The third potential area of improvement is in the communication among stakeholders. This has to do with identifying the relevant data that must be delivered to the stakeholders during the monitoring and management process. Lastly, effective response to medical concerns is the other potential area of improvement. It is noted that patients do not generally get the right response at the right time because the information does not reach the rightly qualified personnel in good time. The regular and real-time capture of vital signs data coupled with added analytics can enable IoT SPs to design solutions that automate the management and transmission of medical data in a timely manner. This work addresses how the medical sector can adopt IoT-based solutions to improve service delivery, while utilizing existing resources such as smartphones, for the transmission and management of vital signs data, availing it to stakeholders and improve communication among them. It develops a telemonitoring system based on IoT design approaches. The developed system captures readings of vital signs from monitoring devices, processes and manages this data to serve the needs of the various stakeholders. Additionally, intelligence was added to enable the system to interpret the data and make decisions that will help medical practitioners and other stakeholders (patients, caregivers, etc.) to more timely, consistently and reliably provide and receive medical services/assistance. Two end user applications were developed. A cloud-based web application developed using PHP, HTML, and JavaScript and an Android mobile application developed using Java programming language in Android studio. An ETSI standards-compliant M2M middleware is used to aggregate the system using M2M applications developed in Python. This is to leverage the benefits of the standards-compliant middleware while offering flexibility in the design of applications. The developed system was evaluated to assess whether it meets the requirements and expectations of the various stakeholders. Finally, the performance of the proposed telemonitoring system was studied by analyzing the delay on the delivery of messages (local notifications, SMS, and email) to various stakeholders to assess the contribution towards reducing the overall time of the cardiac arrest chain of survival. The results obtained showed a marked improvement (over 28 seconds) on previous work. In addition to improved performance in monitoring and management of vital signs, telemonitoring systems have a potential of decongesting health institutions and saving time for all the stakeholders while bridging most of the gaps discussed above. The captured data can also provide the health researchers and physicians with most of the prerequisite data to effectively execute predictive health thereby improving service delivery in the health sector

ETSI SmartM2M Technical Report 103714: Study for oneM2M Discovery and Query use cases and requirements

The oneM2M system has implemented basic native discovery capabilities. In order to enhance the semantic capabilities of the oneM2M architecture by providing solid contributions to the oneM2M standards, four Technical Reports have been developed. Each of them is the outcome of a special study phase: requirements, study, simulation and standardization phase. The present document covers the first phase and provides the basis for the other documents.The use cases specified in the present document lead to potential requirements, which extend the existing requirements of the use case documented in oneM2M TR-0001 [i.19], clause 12.9 with a focus on the discovery and query capabilities, introducing a direct relation with the semantic aspects and enabling more sophisticated semantic queries as e.g. a capability in the CSE, that takes routing decisions for forwarding a received Advanced Semantic Discovery Query.oneM2M has currently native discovery capabilities that work properly only if the search is related to specific known sources of information (e.g. searching for the values of a known set of containers) or if the discovery is well scoped and designed (e.g. the lights in a house). When oneM2M is used to discover wide sets of data or unknown sets of data, the functionality is typically integrated by ad hoc applications that are expanding the oneM2M functionality. This means that this core function may be implemented with different flavours and this is not optimal for interworking and interoperability.The objective of the present document [i.1] in conjunction with three other ones [i.2], [i.3] and [i.4] is the study and development of semantic Discovery and Query capabilities for oneM2M and its contribution to the oneM2M standard.The goal is to enable an easy and efficient discovery of information and a proper interworking with external source/consumers of information (e.g. a distributed data base in a smart city or in a firm), or to directly search information in the oneM2M system for big data purposes

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

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

Digitising the Industry Internet of Things Connecting the Physical, Digital and VirtualWorlds

This book provides an overview of the current Internet of Things (IoT) landscape, ranging from the research, innovation and development priorities to enabling technologies in a global context. A successful deployment of IoT technologies requires integration on all layers, be it cognitive and semantic aspects, middleware components, services, edge devices/machines and infrastructures. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC - Internet of Things European Research Cluster from research to technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster and the IoT European Platform Initiative (IoT-EPI) and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in the next years. The IoT is bridging the physical world with virtual world and requires sound information processing capabilities for the "digital shadows" of these real things. The research and innovation in nanoelectronics, semiconductor, sensors/actuators, communication, analytics technologies, cyber-physical systems, software, swarm intelligent and deep learning systems are essential for the successful deployment of IoT applications. The emergence of IoT platforms with multiple functionalities enables rapid development and lower costs by offering standardised components that can be shared across multiple solutions in many industry verticals. The IoT applications will gradually move from vertical, single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organisations and people, being one of the essential paradigms of the digital economy. Many of those applications still have to be identified and involvement of end-users including the creative sector in this innovation is crucial. The IoT applications and deployments as integrated building blocks of the new digital economy are part of the accompanying IoT policy framework to address issues of horizontal nature and common interest (i.e. privacy, end-to-end security, user acceptance, societal, ethical aspects and legal issues) for providing trusted IoT solutions in a coordinated and consolidated manner across the IoT activities and pilots. In this, context IoT ecosystems offer solutions beyond a platform and solve important technical challenges in the different verticals and across verticals. These IoT technology ecosystems are instrumental for the deployment of large pilots and can easily be connected to or build upon the core IoT solutions for different applications in order to expand the system of use and allow new and even unanticipated IoT end uses. Technical topics discussed in the book include: • Introduction• Digitising industry and IoT as key enabler in the new era of Digital Economy• IoT Strategic Research and Innovation Agenda• IoT in the digital industrial context: Digital Single Market• Integration of heterogeneous systems and bridging the virtual, digital and physical worlds• Federated IoT platforms and interoperability• Evolution from intelligent devices to connected systems of systems by adding new layers of cognitive behaviour, artificial intelligence and user interfaces.• Innovation through IoT ecosystems• Trust-based IoT end-to-end security, privacy framework• User acceptance, societal, ethical aspects and legal issues• Internet of Things Application

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business