Combining distributed queuing with energy harvesting to enable perpetual distributed data collection applications

This is the peer reviewed version of the following article: Vazquez-Gallego F, Tuset-Peiró P, Alonso L, Alonso-Zarate J. Combining distributed queuing with energy harvesting to enable perpetual distributed data collection applications. Trans Emerging Tel Tech. 2017;e3195 , which has been published in final form at https://doi.org/10.1002/ett.3195. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.This paper presents, models, and evaluates energy harvesting–aware distributed queuing (EH-DQ), a novel medium access control protocol that combines distributed queuing with energy harvesting (EH) to address data collection applications in industrial scenarios using long-range and low-power wireless communication technologies. We model the medium access control protocol operation using a Markov chain and evaluate its ability to successfully transmit data without depleting the energy stored at the end devices. In particular, we compare the performance and energy consumption of EH-DQ with that of time-division multiple access (TDMA), which provides an upper limit in data delivery, and EH-aware reservation dynamic frame slotted ALOHA, which is an improved variation of frame slotted ALOHA. To evaluate the performance of these protocols, we use 2 performance metrics: delivery ratio and time efficiency. Delivery ratio measures the ability to successfully transmit data without depleting the energy reserves, whereas time efficiency measures the amount of data that can be transmitted in a certain amount of time. Results show that EH-DQ and TDMA perform close to the optimum in data delivery and outperform EH-aware reservation dynamic frame slotted ALOHA in data delivery and time efficiency. Compared to TDMA, the time efficiency of EH-DQ is insensitive to the amount of harvested energy, making it more suitable for energy-constrained applications. Moreover, compared to TDMA, EH-DQ does not require updated network information to maintain a collision-free schedule, making it suitable for very dynamic networks.Peer ReviewedPostprint (author's final draft

Informe bibliomètric bimestral Campus Baix Llobregat. Base de dades Scopus. Maig-juny 2017

Informe bibliomètric bimestral Campus Baix Llobregat. Base de dades Scopus. Data de la cerca 28/06/2017Postprint (author's final draft

Towards zero-power wireless machine-to-machine networks

This thesis aims at contributing to overcome two of the main challenges for the deployment of M2M networks in data collection scenarios for the Internet of Things: the management of massive numbers of end-devices that attempt to get access to the channel; and the need to extend the network lifetime. In order to solve these challenges, two complementary strategies are considered. Firstly, the thesis focuses on the design, analysis and performance evaluation of MAC protocols that can handle abrupt transitions in the traffic load and minimize the energy consumption devoted to communications. And secondly, the use of energy harvesting (EH) is considered in order to provide the network with unlimited lifetime. To this end, the second part of the thesis focuses on the design and analysis of EH-aware MAC protocols. While the Frame Slotted-ALOHA (FSA) protocol has been traditionally adopted in star topology networks for data collection, results show that FSA-based protocols lack of scalability and present synchronization problems as the network density increases. Indeed, the frame length of FSA must be adjusted to the number of contenders, which may be complex to attain in dense networks with large and dynamic number of end-devices. In order to overcome these issues, a tree splitting-based random access protocol, referred to as Low Power Contention Tree-based Access (LP-CTA), is proposed in the first part of this thesis. In LP-CTA, the frame length can be very short and fixed, which facilitates synchronization and provides better network scalability than FSA. While LP-CTA uses data slots for contention, it is possible to use short access requests in minislots, where collisions are resolved using tree splitting, and avoid the contention in data. Since these minislots can be much shorter than the duration of a data packet, the performance can be improved. The Low Power Distributed Queuing (LP-DQ) protocol proposed in this thesis is based on this idea. LP-DQ combines tree splitting with the logic of two distributed queues that manage the contention resolution and the collision-free data transmission. Results show that LP-DQ outperforms LP-CTA and FSA in terms of delay and energy efficiency, and it relaxes the need to know the size of the network and adapts smoothly to any change in the number of end-devices. The approach of LP-DQ is convenient when the messages transmitted by each end-device fit in one single slot, however, if the end-devices generate long messages that have to be fragmented, it is better to add a reservation mechanism in order to boost the performance. In this sense, the LPR-DQ protocol is proposed as an extension of LP-DQ where the concept of reservation is integrated to allow the end-devices reserve as many collision-free slots as needed. The second part of the thesis is devoted to the integration of the MAC layer with the use of energy harvesting. The variability and fluctuations of the harvested energy is considered for the design of EH-aware MAC protocols and three performance metrics are proposed: the probability of delivery, the data delivery ratio and the time efficiency. Previous works on data collection networks with EH focus on DFSA. In this thesis, the EH-CTA protocol is proposed as an adaptation of LP-CTA that takes the energy harvesting process into account. Results show that EH-CTA outperforms DFSA if the energy threshold for an end-device to become active is properly configured. In addition, while DFSA needs to adapt the frame length dynamically, EH-CTA uses a fixed frame length, thus facilitating scalability and synchronization. Finally, the EH-RDFSA and EH-DQ protocols are proposed for scenarios where data must be fragmented. EH-RDFSA is a combination of RFSA and DFSA, and EH-DQ is an extension of LPR-DQ.Esta tesis contribuye a resolver dos de los retos para el despliegue de redes M2M en escenarios de recolección de datos para el Internet de las Cosas: la gestión del acceso al canal de un número masivo de dispositivos; y la necesidad de extender la vida de la red. Para resolverlos se consideran dos estrategias complementarias. En primer lugar, se centra en el diseño, el análisis y la evaluación de protocolos MAC que pueden manejar transiciones abruptas de tráfico y reducen el consumo de energía. Y en segundo lugar, se considera el uso de mecanismos de captura de energía (Energy Harvesters, EH) para ofrecer un tiempo de vida ilimitado de la red. Con este fin, la segunda parte de la tesis se centra en el diseño y el análisis de protocolos MAC de tipo "EH-aware". Mientras que Frame Slotted-ALOHA (FSA) ha sido tradicionalmente adoptado en aplicaciones de recolección de datos, los resultados muestran que FSA presenta problemas de escalabilidad y sincronización cuando aumenta la densidad de la red. De hecho, la longitud de trama de FSA se debe ajustar según sea el número de dispositivos, lo cual puede ser difícil de estimar en redes con un número elevado y dinámico de dispositivos. Para superar estos problemas, en esta tesis se propone un protocolo de acceso aleatorio basado en "tree-splitting" denominado Low Power Contention Tree-based Access (LP-CTA). En LP-CTA, la longitud de trama puede ser corta y constante, lo cual facilita la sincronización y proporciona mejor escalabilidad. Mientras que LP-CTA utiliza paquetes de datos para la contienda, es posible utilizar solicitudes de acceso en mini-slots, donde las colisiones se resuelven utilizando "tree-splitting", y evitar la contención en los datos. Dado que estos mini-slots pueden ser mucho más cortos que la duración de un slot de datos, el rendimiento de LP-CTA puede ser mejorado. El protocolo Low Power Distributed Queuing (LP-DQ) propuesto en esta tesis se basa en esta idea. LP-DQ combina "tree-splitting" con la lógica de dos colas distribuidas que gestionan la resolución de la contienda en la solicitud de acceso y la transmisión de datos libre de colisiones. Los resultados demuestran que LP-DQ mejora LP-CTA y FSA en términos de retardo y eficiencia energética, LP-DQ no requiere conocer el tamaño de la red y se adapta sin problemas a cualquier cambio en el número de dispositivos. LP-DQ es conveniente cuando los mensajes transmitidos por cada dispositivo caben en un único slot de datos, sin embargo, si los dispositivos generan mensajes largos que requieren fragmentación, es mejor añadir un mecanismo de reserva para aumentar el rendimiento. En este sentido, el protocolo LPR-DQ se propone como una extensión de LP-DQ que incluye un mecanismo de reserva para permitir que cada dispositivo reserve el número de slots de datos según sea el número de fragmentos por mensaje. La segunda parte de la tesis está dedicada a la integración de la capa MAC con el uso de "Energy Harvesters". La variabilidad y las fluctuaciones de la energía capturada se consideran para el diseño de protocolos MAC de tipo "EH-aware" y se proponen tres métricas de rendimiento: la probabilidad de entrega, el "Data Delivery Ratio" y la eficiencia temporal. Los trabajos previos en redes de recolección de datos con EH se centran principalmente en DFSA. En esta tesis, el protocolo EH-CTA se propone como una adaptación de LP-CTA que tiene en cuenta el proceso de captura de energía. Los resultados muestran que EH-CTA supera DFSA si el umbral de energía para que un dispositivo se active está configurado correctamente. Además, mientras que en DFSA se necesita adaptar la longitud de trama de forma dinámica, EH-CTA utiliza una longitud de trama fija, facilitando así la escalabilidad y la sincronización. Por último, se proponen los protocolos EH-RDFSA y EH-DQ para escenarios en los que los datos deben ser fragmentados. EH-RDFSA es una combinación de RFSA y DFSA, y EH-DQ es una extensión de LPR-DQ.Aquesta tesi contribueix a resoldre dos dels reptes per al desplegament de xarxes M2M en escenaris de recol·lecció de dades per a l'Internet de les Coses: la gestió de l'accés al canal d'un nombre massiu de dispositius; i la necessitat d'extendre la vida de la xarxa. Per resoldre'ls es consideren dues estratègies complementàries. En primer lloc, es centra en el disseny, l'anàlisi i l'avaluació de protocols MAC que poden manegar transicions abruptes de trànsit i redueixen el consum d'energia. I en segon lloc, es considera l'ús de mecanismes de captura d'energia (Energy Harvesters, EH) per a oferir un temps de vida il·limitat de la xarxa. Amb aquesta finalitat, la segona part de la tesi es centra en el disseny i l'anàlisi de protocols MAC de tipus "EH-aware".Mentre que Frame Slotted-ALOHA (FSA) ha estat tradicionalment adoptat en aplicacions de recol·lecció de dades, els resultats mostren que FSA presenta problemes d'escalabilitat i sincronització quan augmenta la densitat de la xarxa. De fet, la longitud de trama de FSA s'ha d'ajustar segons sigui el nombre de dispositius, la qual cosa pot ser difícil d'estimar en xarxes amb un nombre elevat i dinàmic de dispositius. Per superar aquests problemes, en aquesta tesi es proposa un protocol d'accés aleatori basat en "tree-splitting" denominat Low Power Contention Tree-based Access (LP-CTA). En LP-CTA, la longitud de trama pot ser curta i constant, la qual cosa facilita la sincronització i proporciona millor escalabilitat.Mentre que LP-CTA utilitza paquets de dades per a la contenció, és possible utilitzar sol·licituds d'accés a mini-slots, on les col·lisions es resolen utilitzant "tree-splitting", i evitar la contenció a les dades. Atès que aquests mini-slots poden ser molt més curts que la durada d'un slot de dades, el rendiment de LP-CTA pot ser millorat. El protocol Low Power Distributed Queuing (LP-DQ) proposat en aquesta tesi es basa en aquesta idea. LP-DQ combina "tree-splitting" amb la lògica de dues cues distribuïdes que gestionen la resolució de la contenció en la sol·licitud d'accés i la transmissió de dades lliure de col·lisions. Els resultats demostren que LP-DQ millora LP-CTA i FSA en termes de retard i eficiència energètica, LP-DQ no requereix conèixer la mida de la xarxa i s'adapta sense problemes a qualsevol canvi en el nombre de dispositius.LP-DQ és convenient quan els missatges transmesos per cada dispositiu caben en un únic slot de dades, però, si els dispositius generen missatges llargs que requereixen fragmentació, és millor afegir un mecanisme de reserva per augmentar el rendiment. En aquest sentit, el protocol LPR-DQ es proposa com una extensió de LP-DQ que inclou un mecanisme de reserva per a permetre que cada dispositiu reservi el nombre de slots de dades segons sigui el nombre de fragments per missatge.La segona part de la tesi està dedicada a la integració de la capa MAC amb l'ús de "Energy Harvesters". La variabilitat i les fluctuacions de l'energia capturada es consideren per al disseny de protocols MAC de tipus "EH-aware" i es proposen tres mètriques de rendiment: la probabilitat d'entrega, el "Data Delivery Ratio" i l'eficiència temporal.Els treballs previs en xarxes de recol·lecció de dades amb EH se centren principalment en DFSA. En aquesta tesi, el protocol EH-CTA es proposa com una adaptació de LP-CTA que té en compte el procés de captura d'energia. Els resultats mostren que EH-CTA supera DFSA si el llindar d'energia perquè un dispositiu s'activi s'ajusta correctament. A més, mentre que a DFSA es necessita adaptar la longitud de trama de forma dinàmica, EH-CTA utilitza una longitud de trama fixa, facilitant així l'escalabilitat i la sincronització. Finalment, es proposen els protocols EH-RDFSA i EH-DQ per a escenaris en els quals les dades han de ser fragmentades. EH-RDFSA és una combinació de RFSA i DFSA, i EH-DQ és una extensió de LPR-DQ.Postprint (published version

A Survey on Mobile Charging Techniques in Wireless Rechargeable Sensor Networks

The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the MCTs. Next, we introduce an exhaustive taxonomy of the MCTs based on various design attributes and then review the literature by categorizing it into periodic and on-demand charging techniques. In addition, we compare the state-of-the-art MCTs in terms of objectives, constraints, solution approaches, charging options, design issues, performance metrics, evaluation methods, and limitations. Finally, we highlight some potential directions for future research

Energy Harvesting-Aware Design for Wireless Nanonetworks

Nanotechnology advancement promises to enable a new era of computing and communication devices by shifting micro scale chip design to nano scale chip design. Nanonetworks are envisioned as artifacts of nanotechnology in the domain of networking and communication. These networks will consist of nodes of nanometer to micrometer in size, with a communication range up to 1 meter. These nodes could be used in various biomedical, industrial, and environmental monitoring applications, where a nanoscale level of sensing, monitoring, control and communication is required. The special characteristics of nanonetworks require the revisiting of network design. More specifically, nanoscale limitations, new paradigms of THz communication, and power supply via energy harvesting are the main issues that are not included in traditional network design methods. In this regard, this dissertation investigates and develops some solutions in the realization of nanonetworks. Particularly, the following major solutions are investigated. (I) The energy harvesting and energy consumption processes are modeled and evaluated simultaneously. This model includes the stochastic nature of energy arrival as well as the pulse-based communication model for energy consumption. The model identifies the effect of various parameters in this joint process. (II) Next, an optimization problem is developed to find the best combination of these parameters. Specifically, optimum values for packet size, code weight, and repetition are found in order to minimize the energy consumption while satisfying some application requirements (i.e., delay and reliability). (III) An optimum policy for energy consumption to achieve the maximum utilization of harvested energy is developed. The goal of this scheme is to take advantage of available harvested energy as much as possible while satisfying defined performance metrics. (IV) A communication scheme that tries to maximize the data throughput via a distributed and scalable coordination while avoiding the collision among neighbors is the last problem to be investigated. The goal is to design an energy harvesting-aware and distributed mechanism that could coordinate data transmission among neighbors. (V) Finally, all these solutions are combined together to create a data link layer model for nanonodes. We believe resolving these issues could be the first step towards an energy harvesting-aware network design for wireless nanosensor networks

Virtual Organization Clusters: Self-Provisioned Clouds on the Grid

Virtual Organization Clusters (VOCs) provide a novel architecture for overlaying dedicated cluster systems on existing grid infrastructures. VOCs provide customized, homogeneous execution environments on a per-Virtual Organization basis, without the cost of physical cluster construction or the overhead of per-job containers. Administrative access and overlay network capabilities are granted to Virtual Organizations (VOs) that choose to implement VOC technology, while the system remains completely transparent to end users and non-participating VOs. Unlike alternative systems that require explicit leases, VOCs are autonomically self-provisioned according to configurable usage policies. As a grid computing architecture, VOCs are designed to be technology agnostic and are implementable by any combination of software and services that follows the Virtual Organization Cluster Model. As demonstrated through simulation testing and evaluation of an implemented prototype, VOCs are a viable mechanism for increasing end-user job compatibility on grid sites. On existing production grids, where jobs are frequently submitted to a small subset of sites and thus experience high queuing delays relative to average job length, the grid-wide addition of VOCs does not adversely affect mean job sojourn time. By load-balancing jobs among grid sites, VOCs can reduce the total amount of queuing on a grid to a level sufficient to counteract the performance overhead introduced by virtualization

Modelling and performability evaluation of Wireless Sensor Networks

This thesis presents generic analytical models of homogeneous clustered Wireless Sensor Networks (WSNs) with a centrally located Cluster Head (CH) coordinating cluster communication with the sink directly or through other intermediate nodes. The focus is to integrate performance and availability studies of WSNs in the presence of sensor nodes and channel failures and repair/replacement. The main purpose is to enhance improvement of WSN Quality of Service (QoS). Other research works also considered in this thesis include modelling of packet arrival distribution at the CH and intermediate nodes, and modelling of energy consumption at the sensor nodes. An investigation and critical analysis of wireless sensor network architectures, energy conservation techniques and QoS requirements are performed in order to improve performance and availability of the network. Existing techniques used for performance evaluation of single and multi-server systems with several operative states are investigated and analysed in details. To begin with, existing approaches for independent (pure) performance modelling are critically analysed with highlights on merits and drawbacks. Similarly, pure availability modelling approaches are also analysed. Considering that pure performance models tend to be too optimistic and pure availability models are too conservative, performability, which is the integration of performance and availability studies is used for the evaluation of the WSN models developed in this study. Two-dimensional Markov state space representations of the systems are used for performability modelling. Following critical analysis of the existing solution techniques, spectral expansion method and system of simultaneous linear equations are developed and used to solving the proposed models. To validate the results obtained with the two techniques, a discrete event simulation tool is explored. In this research, open queuing networks are used to model the behaviour of the CH when subjected to streams of traffic from cluster nodes in addition to dynamics of operating in the various states. The research begins with a model of a CH with an infinite queue capacity subject to failures and repair/replacement. The model is developed progressively to consider bounded queue capacity systems, channel failures and sleep scheduling mechanisms for performability evaluation of WSNs. Using the developed models, various performance measures of the considered system including mean queue length, throughput, response time and blocking probability are evaluated. Finally, energy models considering mean power consumption in each of the possible operative states is developed. The resulting models are in turn employed for the evaluation of energy saving for the proposed case study model. Numerical solutions and discussions are presented for all the queuing models developed. Simulation is also performed in order to validate the accuracy of the results obtained. In order to address issues of performance and availability of WSNs, current research present independent performance and availability studies. The concerns resulting from such studies have therefore remained unresolved over the years hence persistence poor system performance. The novelty of this research is a proposed integrated performance and availability modelling approach for WSNs meant to address challenges of independent studies. In addition, a novel methodology for modelling and evaluation of power consumption is also offered. Proposed model results provide remarkable improvement on system performance and availability in addition to providing tools for further optimisation studies. A significant power saving is also observed from the proposed model results. In order to improve QoS for WSN, it is possible to improve the proposed models by incorporating priority queuing in a mixed traffic environment. A model of multi-server system is also appropriate for addressing traffic routing. It is also possible to extend the proposed energy model to consider other sleep scheduling mechanisms other than On-demand proposed herein. Analysis and classification of possible arrival distribution of WSN packets for various application environments would be a great idea for enabling robust scientific research

Enhancing the Performance of Energy Harvesting Sensor Networks for Environmental Monitoring Applications

Fast development in hardware miniaturization and massive production of sensors make them cost efficient and vastly available to be used in various applications in our daily life more specially in environment monitoring applications. However, energy consumption is still one of the barriers slowing down the development of several applications. Slow development in battery technology, makes energy harvesting (EH) as a prime candidate to eliminate the sensor’s energy barrier. EH sensors can be the solution to enabling future applications that would be extremely costly using conventional battery-powered sensors. In this paper, we analyze the performance improvement and evaluation of EH sensors in various situations. A network model is developed to allow us to examine different scenarios. We borrow a clustering concept, as a proven method to improve energy efficiency in conventional sensor network and brought it to EH sensor networks to study its effect on the performance of the network in different scenarios. Moreover, a dynamic and distributed transmission power management for sensors is proposed and evaluated in both networks, with and without clustering, to study the effect of power balancing on the network end-to-end performance. The simulation results indicate that, by using clustering and transmission power adjustment, the power consumption can be distributed in the network more efficiently, which result in improving the network performance in terms of a packet delivery ratio by 20%, 10% higher network lifetime by having more alive nodes and also achieving lower delay by reducing the hop-count

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