A Review of Indoor Millimeter Wave Device-based Localization and Device-free Sensing Technologies and Applications

The commercial availability of low-cost millimeter wave (mmWave) communication and radar devices is starting to improve the penetration of such technologies in consumer markets, paving the way for large-scale and dense deployments in fifth-generation (5G)-and-beyond as well as 6G networks. At the same time, pervasive mmWave access will enable device localization and device-free sensing with unprecedented accuracy, especially with respect to sub-6 GHz commercial-grade devices. This paper surveys the state of the art in device-based localization and device-free sensing using mmWave communication and radar devices, with a focus on indoor deployments. We first overview key concepts about mmWave signal propagation and system design. Then, we provide a detailed account of approaches and algorithms for localization and sensing enabled by mmWaves. We consider several dimensions in our analysis, including the main objectives, techniques, and performance of each work, whether each research reached some degree of implementation, and which hardware platforms were used for this purpose. We conclude by discussing that better algorithms for consumer-grade devices, data fusion methods for dense deployments, as well as an educated application of machine learning methods are promising, relevant and timely research directions.Comment: 43 pages, 13 figures. Accepted in IEEE Communications Surveys & Tutorials (IEEE COMST

Mobile networks and internet of things infrastructures to characterize smart human mobility

The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches.This work has been supported by FCT–Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. This work has also been supported by national funds through FCT–Fundação para a Ciência e Tecnologia through project UIDB/04728/202

Selected Papers from the 5th International Electronic Conference on Sensors and Applications

This Special Issue comprises selected papers from the proceedings of the 5th International Electronic Conference on Sensors and Applications, held on 15–30 November 2018, on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups. In this 5th edition of the electronic conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Papers which attracted the most interest on the web or that provided a particularly innovative contribution were selected for publication in this collection. These peer-reviewed papers are published with the aim of rapid and wide dissemination of research results, developments, and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications

AI enabled RF sensing of Diversified Human-Centric Monitoring

This thesis delves into the application of various RF signaling techniques in HumanCentric Monitoring (HCM), specifically focusing on WiFi, LoRa, Ultra-wideband (UWB) radars, and Frequency Modulated Continuous Wave (FMCW) radars. Each of these technologies has unique properties suitable for different aspects of HCM. For instance, 77GHz FMCW radar signals demonstrate high sensitivity in detecting subtle human movements, such as heartbeat, contrasting with the capabilities of 2.4GHz/5GHz WiFi signals. The research extends to both large-scale and small-scale Human Activity Recognition (HAR), examining how ubiquitous communication signals like WiFi and LoRa can be utilized for large-scale HAR, while radar signals with higher central frequencies are more effective for small-scale motions, including heartbeat and mouth movements. The thesis also identifies several unresolved challenges in the field. These include the underutilization of spatial spectral information in existing WiFi sensing technologies, the untapped potential of LoRa technology in identity recognition, the sensitivity of millimeterwave radar in detecting breathing and heartbeat against minor movements, and the lack of comprehensive datasets for mouth motion detection in silent speech recognition. Addressing these challenges, the paper proposes several innovative solutions: • A comprehensive analysis of methodologies for RF-based HCM applications, discussing challenges and proposing potential solutions for broader healthcare applications using wireless sensing. • Exploration of communication signals in HCM systems, especially focusing on WiFi and LoRa sensing. It introduces the continuous AoA-ToF maps method to enhance HCM system performance and the LoGait system, which uses LoRa signals for human gait identification, extending the sensing range to 20 meters. • Development of a FMCW radar-based structure for respiration detection, incorporating an ellipse normalization method to adjust distorted IQ signals, reducing the root mean square error by 30% compared to baseline methods. • Collection and analysis of a large-scale multimodal dataset for silent speech recognition and speech enhancement, including designing experiments to validate the dataset’s utility in a multimodal-based speech recognition system

Contribution to the integration, performance improvement, and smart management of data and resources in the Internet of Things

[SPA] Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones.[ENG] This doctoral dissertation has been presented in the form of thesis by publication. The IoT has seen a tremendous growth in the last few years. Not only due to its potential to transform societies, but also as an enabling technology for many other technological advances. Unfortunately, the IoT is a relatively recent paradigm that lacks the maturity of other well-established (not so recent) revolutions like the internet itself or Wireless Sensor Networks; upon which the IoT is built. The presented Thesis contributes to this maturation process by researching on the underlying communication mechanisms that enable a truly ubiquitous and effective IoT. As a Thesis by compilation, 5 relevant articles are introduced and discussed. Each of such articles delve into different key aspects that, in their own way, help closing the gap between what the IoT is expected to bring and what the IoT actually brings. As thoroughly commented throughout the main text, the comprehensive approach taken in this Thesis ensures that multiple angles of the same plane --the communication plane-- are analyzed and studied. From the mathematical analysis of how electromagnetic waves propagate through complex environments to the utilization of recent Machine Learning techniques, this Thesis explore a wide range of scientific and researching tools that are shown to improve the final performance of the IoT. In the first three chapters of this document, the reader will be introduced to the current context and state-of-the-art of the IoT while, at the same time, the formal objectives of this Thesis are outlined and set into such a global context. In the next five chapters, the five corresponding articles are presented and commented. For each and every of these articles: a brief abstract, a methodology summary, a highlight on the results and contributions and final conclusions are also added. Lastly, in the two last chapters, the final conclusions and future lines of this Thesis are commented.Los artículos que componen la tesis son los siguientes: 1. R. M. Sandoval, A.-J. J. Garcia-Sanchez, F. Garcia-Sanchez, and J. Garcia-Haro, \Evaluating the More Suitable ISM Frequency Band for IoT-Based Smart Grids: A Quantitative Study of 915 MHz vs. 2400 MHz," Sensors, vol. 17, no. 1, p. 76, Dec. 2016. 2. R. M. Sandoval, A.-J. J. Garcia-Sanchez, J.-M. M. Molina-Garcia-Pardo, F. Garcia-Sanchez, and J. Garcia-Haro, \Radio-Channel Characterization of Smart Grid Substations in the 2.4-GHz ISM Band," IEEE Trans. Wirel. Commun., vol. 16, no. 2, pp. 1294{1307, Feb. 2017. 3. R. M. Sandoval, A. J. Garcia-Sanchez, and J. Garcia-Haro, \Improving RSSI-based path-loss models accuracy for critical infrastructures: A smart grid substation case-study," IEEE Trans. Ind. Informatics, vol. 14, no. 5, pp. 2230{2240, 2018. 4. R. M. Sandoval, A.-J. Garcia-Sanchez, J. Garcia-Haro, and T. M. Chen, \Optimal policy derivation for Transmission Duty-Cycle constrained LPWAN," IEEE Internet Things J., vol. 5, no. 4, pp. 1{1, Aug. 2018. 5. R. M. Sandoval, S. Canovas-Carrasco, A. Garcia-Sanchez, and J. Garcia-Haro, \Smart Usage of Multiple RAT in IoT-oriented 5G Networks: A Reinforcement Learning Approach," in 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K), 2018, pp. 1-8.Escuela Internacional de Doctorado de la Universidad Politécnica de CartagenaUniversidad Politécnica de CartagenaPrograma de Doctorado en Tecnologías de la Información y las Comunicaciones por la Universidad Politécnica de Cartagen

Smart Monitoring and Control in the Future Internet of Things

The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&