A fast and accurate energy source emulator for wireless sensor networks

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Reducing Operation Cost of LPWAN Roadside Sensors Using Cross Technology Communication

Low-Power Wide-Area Network (LPWAN) is an emerging communication standard for Internet of Things (IoT) that has strong potential to support connectivity of a large number of roadside sensors with an extremely long communication range. However, the high operation cost to manage such a large-scale roadside sensor network remains as a significant challenge. In this paper, we propose LOC-LPWAN, a novel optimization framework that is designed to reduce the operation cost using the cross technology communication (CTC). LOC-LPWAN allows roadside sensors to offload sensor data to passing vehicles that in turn forward the data to a LPWAN server using CTC aiming to reduce the data subscription cost. LOC-LPWAN finds the optimal communication schedule between sensors and vehicles to maximize the throughput given an available budget of the user. Furthermore, LOC-LPWAN optimizes the fairness among sensors by allowing sensors to transmit similar amounts of data and preventing certain sensors from dominating the opportunity for data transmissions. LOC-LPWAN also provides an option that allows all sensor to transmit data within a specific delay bound. Extensive numerical analysis performed with real-world taxi data consisting of 40 vehicles with 24-hour trajectories demonstrate that LOC-LPWAN improves the throughput by 72.6%, enhances the fairness by 65.7%, and reduces the delay by 28.8% compared with a greedy algorithm given the same budget

Vibration suppression in multi-body systems by means of disturbance filter design methods

This paper addresses the problem of interaction in mechanical multi-body systems and shows that subsystem interaction can be considerably minimized while increasing performance if an efficient disturbance model is used. In order to illustrate the advantage of the proposed intelligent disturbance filter, two linear model based techniques are considered: IMC and the model based predictive (MPC) approach. As an illustrative example, multivariable mass-spring-damper and quarter car systems are presented. An adaptation mechanism is introduced to account for linear parameter varying LPV conditions. In this paper we show that, even if the IMC control strategy was not designed for MIMO systems, if a proper filter is used, IMC can successfully deal with disturbance rejection in a multivariable system, and the results obtained are comparable with those obtained by a MIMO predictive control approach. The results suggest that both methods perform equally well, with similar numerical complexity and implementation effort

On-chip adaptive power management for WPT-Enabled IoT

Internet of Things (IoT), as broadband network connecting every physical objects, is becoming more widely available in various industrial, medical, home and automotive applications. In such network, the physical devices, vehicles, medical assistance, and home appliances among others are supposed to be embedded by sensors, actuators, radio frequency (RF) antennas, memory, and microprocessors, such that these devices are able to exchange data and connect with other devices in the network. Among other IoT’s pillars, wireless sensor network (WSN) is one of the main parts comprising massive clusters of spatially distributed sensor nodes dedicated for sensing and monitoring environmental conditions. The lifetime of a WSN is greatly dependent on the lifetime of the small sensor nodes, which, in turn, is primarily dependent on energy availability within every sensor node. Predominantly, the main energy source for a sensor node is supplied by a small battery attached to it. In a large WSN with massive number of deployed sensor nodes, it becomes a challenge to replace the batteries of every single sensor node especially for sensor nodes deployed in harsh environments. Consequently, powering the sensor nodes becomes a key limiting issue, which poses important challenges for their practicality and cost. Therefore, in this thesis we propose enabling WSN, as the main pillar of IoT, by means of resonant inductive coupling (RIC) wireless power transfer (WPT). In order to enable efficient energy delivery at higher range, high quality factor RIC-WPT system is required in order to boost the magnetic flux generated at the transmitting coil. However, an adaptive front-end is essential for self-tuning the resonant tank against any mismatch in the components values, distance variation, and interference from close metallic objects. Consequently, the purpose of the thesis is to develop and design an adaptive efficient switch-mode front-end for self-tuning in WPT receivers in multiple receiver system. The thesis start by giving background about the IoT system and the technical bottleneck followed by the problem statement and thesis scope. Then, Chapter 2 provides detailed backgrounds about the RIC-WPT system. Specifically, Chapter 2 analyzes the characteristics of different compensation topologies in RIC-WPT followed by the implications of mistuning on efficiency and power transfer capability. Chapter 3 discusses the concept of switch-mode gyrators as a potential candidate for generic variable reactive element synthesis while different potential applications and design cases are provided. Chapter 4 proposes two different self-tuning control for WPT receivers that utilize switch-mode gyrators as variable reactive element synthesis. The performance aspects of control approaches are discussed and evaluated as well in Chapter 4. The development and exploration of more compact front-end for self-tuned WPT receiver is investigated in Chapter 5 by proposing a phase-controlled switched inductor converter. The operation and design details of different switch-mode phase-controlled topologies are given and evaluated in the same chapter. Finally, Chapter 6 provides the conclusions and highlight the contribution of the thesis, in addition to suggesting the related future research topics.Internet de las cosas (IoT), como red de banda ancha que interconecta cualquier cosa, se está estableciendo como una tecnología valiosa en varias aplicaciones industriales, médicas, domóticas y en el sector del automóvil. En dicha red, los dispositivos físicos, los vehículos, los sistemas de asistencia médica y los electrodomésticos, entre otros, incluyen sensores, actuadores, subsistemas de comunicación, memoria y microprocesadores, de modo que son capaces de intercambiar datos e interconectarse con otros elementos de la red. Entre otros pilares que posibilitan IoT, la red de sensores inalámbricos (WSN), que es una de las partes cruciales del sistema, está formada por un conjunto masivo de nodos de sensado distribuidos espacialmente, y dedicados a sensar y monitorizar las condiciones del contexto de las cosas interconectadas. El tiempo de vida útil de una red WSN depende estrechamente del tiempo de vida de los pequeños nodos sensores, los cuales, a su vez, dependen primordialmente de la disponibilidad de energía en cada nodo sensor. La fuente principal de energía para un nodo sensor suele ser una pequeña batería integrada en él. En una red WSN con muchos nodos y con una alta densidad, es un desafío el reemplazar las baterías de cada nodo sensor, especialmente en entornos hostiles, como puedan ser en escenarios de Industria 4.0. En consecuencia, la alimentación de los nodos sensores constituye uno de los cuellos de botella que limitan un despliegue masivo práctico y de bajo coste. A tenor de estas circunstancias, en esta tesis doctoral se propone habilitar las redes WSN, como pilar principal de sistemas IoT, mediante sistemas de transferencia inalámbrica de energía (WPT) basados en acoplamiento inductivo resonante (RIC). Con objeto de posibilitar el suministro eficiente de energía a mayores distancias, deben aumentarse los factores de calidad de los elementos inductivos resonantes del sistema RIC-WPT, especialmente con el propósito de aumentar el flujo magnético generado por el inductor transmisor de energía y su acoplamiento resonante en recepción. Sin embargo, dotar al cabezal electrónico que gestiona y condicionada el flujo de energía de capacidad adaptativa es esencial para conseguir la autosintonía automática del sistema acoplado y resonante RIC-WPT, que es muy propenso a la desintonía ante desajustes en los parámetros nominales de los componentes, variaciones de distancia entre transmisor y receptores, así como debido a la interferencia de objetos metálicos. Es por tanto el objetivo central de esta tesis doctoral el concebir, proponer, diseñar y validar un sistema de WPT para múltiples receptores que incluya funciones adaptativas de autosintonía mediante circuitos conmutados de alto rendimiento energético, y susceptible de ser integrado en un chip para el condicionamiento de energía en cada receptor de forma miniaturizada y desplegable de forma masiva. La tesis empieza proporcionando una revisión del estado del arte en sistemas de IoT destacando el reto tecnológico de la alimentación energética de los nodos sensores distribuidos y planteando así el foco de la tesis doctoral. El capítulo 2 sigue con una revisión crítica del statu quo de los sistemas de transferencia inalámbrica de energía RIC-WPT. Específicamente, el capítulo 2 analiza las características de diferentes estructuras circuitales de compensación en RIC-WPT seguido de una descripción crítica de las implicaciones de la desintonía en la eficiencia y la capacidad de transferencia energética del sistema. El capítulo 3 propone y explora el concepto de utilizar circuitos conmutados con función de girador como potenciales candidatos para la síntesis de propósito general de elementos reactivos variables sintonizables electrónicamente, incluyendo varias aplicaciones y casos de uso. El capítulo 4 propone dos alternativas para métodos y circuitos de control para la autosintonía de receptores de energíaPostprint (published version

A Review of Current Research Trends in Power-Electronic Innovations in Cyber-Physical Systems.

In this paper, a broad overview of the current research trends in power-electronic innovations in cyber-physical systems (CPSs) is presented. The recent advances in semiconductor device technologies, control architectures, and communication methodologies have enabled researchers to develop integrated smart CPSs that can cater to the emerging requirements of smart grids, renewable energy, electric vehicles, trains, ships, internet of things (IoTs), etc. The topics presented in this paper include novel power-distribution architectures, protection techniques considering large renewable integration in smart grids, wireless charging in electric vehicles, simultaneous power and information transmission, multi-hop network-based coordination, power technologies for renewable energy and smart transformer, CPS reliability, transactive smart railway grid, and real-time simulation of shipboard power systems. It is anticipated that the research trends presented in this paper will provide a timely and useful overview to the power-electronics researchers with broad applications in CPSs.post-print2.019 K

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa