User-Centred Design and Development of an Intelligent Light Switch for Sensor Systems

The aim of the research was the user-centred design of an intelligent light switch with a focus on the definition of the natural and intuitive gestures for its manipulation, and to develop a multi-touch user interface and smart touch-based light switch that could be integrated into existing home environments and electrical wiring, with or without an existing intelligent system. After usability testing a prototype of the switch was constructed. The touch-panel, as the main interface, gave the users the ability to control one or more individual lights or light groups. The intuitive touch gestures for controlling the lighting were acquired with paper prototypes that were used for testing, and then integrated in the physical prototype. The results show that user-centred design is a valuable method for creating an intelligent touch-based light switch with a good user experience design, with or without a multi-touch user interface, and thus an approach that should be implemented in the development of a smart product

A Survey of Positioning Systems Using Visible LED Lights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe

Development and Coverage Evaluation of ZigBee-Based Wireless Network Applications

Network coverage is one of the basic issues for information collection and data processing in ZigBee-based wireless sensor networks. Each node may be randomly distributed in a monitoring area, reflecting the network event of tracking in ZigBee network applications. This paper presents the development and coverage evaluation of a ZigBee-based wireless network application. A stack structure node available for home service integration is proposed, and all data of sensing nodes with an adaptive weighted fusion (AWF) processing are passed to the gateway and through the gateway to reexecute packet processing and then reported to the monitoring center, which effectively optimize the wireless network to the scale of the data processing efficiency. The linear interpolation theory is used for background graphical user interface so as to evaluate the working status of each node and the whole network coverage case. A testbed has been created for validating the basic functions of the proposed ZigBee-based home network system. Network coverage capabilities were tested, and packet loss and energy saving of the proposed system in longtime wireless network monitoring tasks were also verified

A systematic literature review on the use of artificial intelligence in energy self-management in smart buildings

Buildings are one of the main consumers of energy in cities, which is why a lot of research has been generated around this problem. Especially, the buildings energy management systems must improve in the next years. Artificial intelligence techniques are playing and will play a fundamental role in these improvements. This work presents a systematic review of the literature on researches that have been done in recent years to improve energy management systems for smart building using artificial intelligence techniques. An originality of the work is that they are grouped according to the concept of "Autonomous Cycles of Data Analysis Tasks", which defines that an autonomous management system requires specialized tasks, such as monitoring, analysis, and decision-making tasks for reaching objectives in the environment, like improve the energy efficiency. This organization of the work allows us to establish not only the positioning of the researches, but also, the visualization of the current challenges and opportunities in each domain. We have identified that many types of researches are in the domain of decision-making (a large majority on optimization and control tasks), and defined potential projects related to the development of autonomous cycles of data analysis tasks, feature engineering, or multi-agent systems, among others.European Commissio

Assistive technology design and development for acceptable robotics companions for ageing years

© 2013 Farshid Amirabdollahian et al., licensee Versita Sp. z o. o. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs license, which means that the text may be used for non-commercial purposes, provided credit is given to the author.A new stream of research and development responds to changes in life expectancy across the world. It includes technologies which enhance well-being of individuals, specifically for older people. The ACCOMPANY project focuses on home companion technologies and issues surrounding technology development for assistive purposes. The project responds to some overlooked aspects of technology design, divided into multiple areas such as empathic and social human-robot interaction, robot learning and memory visualisation, and monitoring persons’ activities at home. To bring these aspects together, a dedicated task is identified to ensure technological integration of these multiple approaches on an existing robotic platform, Care-O-Bot®3 in the context of a smart-home environment utilising a multitude of sensor arrays. Formative and summative evaluation cycles are then used to assess the emerging prototype towards identifying acceptable behaviours and roles for the robot, for example role as a butler or a trainer, while also comparing user requirements to achieved progress. In a novel approach, the project considers ethical concerns and by highlighting principles such as autonomy, independence, enablement, safety and privacy, it embarks on providing a discussion medium where user views on these principles and the existing tension between some of these principles, for example tension between privacy and autonomy over safety, can be captured and considered in design cycles and throughout project developmentsPeer reviewe

Design and development of smart emergency light

The demand for electricity is increasing day-by-day and frequent power cuts is causing many problems in various areas such as household, domestic, farms, etc. Due to limited amount of power generation at power station and due to shortage of non-renewable sources, uninterruptible power supply being a biggest challenge in the entire world. In this paper, a smart emergency light is designed, developed and tested for use it in various applications such as home, industries, agricultural sector and shops, etc. The developed energy lamp has no running cost and has low initial cost. The main objective of this work is to provide the smart emergency light with solar power to the farmers. This work will help the farmers in many ways such as protecting the fields from yield animals. It can also be used as emergency light and entertainment, etc. The main applications of this work is that it can used as FM radio, USB charging, music by memory card, mini fan, torch light, etc. This can also be controlled by remote. The battery can be used for all these applications. This battery can be charged by two ways using solar energy and AC mains supply. The developed lamp is tested in the real time environment

Perception architecture exploration for automotive cyber-physical systems

2022 Spring.Includes bibliographical references.In emerging autonomous and semi-autonomous vehicles, accurate environmental perception by automotive cyber physical platforms are critical for achieving safety and driving performance goals. An efficient perception solution capable of high fidelity environment modeling can improve Advanced Driver Assistance System (ADAS) performance and reduce the number of lives lost to traffic accidents as a result of human driving errors. Enabling robust perception for vehicles with ADAS requires solving multiple complex problems related to the selection and placement of sensors, object detection, and sensor fusion. Current methods address these problems in isolation, which leads to inefficient solutions. For instance, there is an inherent accuracy versus latency trade-off between one stage and two stage object detectors which makes selecting an enhanced object detector from a diverse range of choices difficult. Further, even if a perception architecture was equipped with an ideal object detector performing high accuracy and low latency inference, the relative position and orientation of selected sensors (e.g., cameras, radars, lidars) determine whether static or dynamic targets are inside the field of view of each sensor or in the combined field of view of the sensor configuration. If the combined field of view is too small or contains redundant overlap between individual sensors, important events and obstacles can go undetected. Conversely, if the combined field of view is too large, the number of false positive detections will be high in real time and appropriate sensor fusion algorithms are required for filtering. Sensor fusion algorithms also enable tracking of non-ego vehicles in situations where traffic is highly dynamic or there are many obstacles on the road. Position and velocity estimation using sensor fusion algorithms have a lower margin for error when trajectories of other vehicles in traffic are in the vicinity of the ego vehicle, as incorrect measurement can cause accidents. Due to the various complex inter-dependencies between design decisions, constraints and optimization goals a framework capable of synthesizing perception solutions for automotive cyber physical platforms is not trivial. We present a novel perception architecture exploration framework for automotive cyber- physical platforms capable of global co-optimization of deep learning and sensing infrastructure. The framework is capable of exploring the synthesis of heterogeneous sensor configurations towards achieving vehicle autonomy goals. As our first contribution, we propose a novel optimization framework called VESPA that explores the design space of sensor placement locations and orientations to find the optimal sensor configuration for a vehicle. We demonstrate how our framework can obtain optimal sensor configurations for heterogeneous sensors deployed across two contemporary real vehicles. We then utilize VESPA to create a comprehensive perception architecture synthesis framework called PASTA. This framework enables robust perception for vehicles with ADAS requiring solutions to multiple complex problems related not only to the selection and placement of sensors but also object detection, and sensor fusion as well. Experimental results with the Audi-TT and BMW Minicooper vehicles show how PASTA can intelligently traverse the perception design space to find robust, vehicle-specific solutions

eXplainable data processing

Seminario realizado en U & P U Patel Department of Computer Engineering, Chandubhai S. Patel Institute of Technology, Charotar University of Science And Technology (CHARUSAT), Changa-388421, Gujarat, India 2021[EN]Deep Learning y has created many new opportunities, it has unfortunately also become a means for achieving ill-intentioned goals. Fake news, disinformation campaigns, and manipulated images and videos have plagued the internet which has had serious consequences on our society. The myriad of information available online means that it may be difficult to distinguish between true and fake news, leading many users to unknowingly share fake news, contributing to the spread of misinformation. The use of Deep Learning to create fake images and videos has become known as deepfake. This means that there are ever more effective and realistic forms of deception on the internet, making it more difficult for internet users to distinguish reality from fictio

Transport Layer solution for bulk data transfers over Heterogeneous Long Fat Networks in Next Generation Networks

Aquesta tesi per compendi centra les seves contribucions en l'aprenentatge i innovació de les Xarxes de Nova Generació. És per això que es proposen diferents contribucions en diferents àmbits (Smart Cities, Smart Grids, Smart Campus, Smart Learning, Mitjana, eHealth, Indústria 4.0 entre d'altres) mitjançant l'aplicació i combinació de diferents disciplines (Internet of Things, Building Information Modeling, Cloud Storage, Ciberseguretat, Big Data, Internet de el Futur, Transformació Digital). Concretament, es detalla el monitoratge sostenible del confort a l'Smart Campus, la que potser es la meva aportació més representativa dins de la conceptualització de Xarxes de Nova Generació. Dins d'aquest innovador concepte de monitorització s'integren diferents disciplines, per poder oferir informació sobre el nivell de confort de les persones. Aquesta investigació demostra el llarg recorregut que hi ha en la transformació digital dels sectors tradicionals i les NGNs. Durant aquest llarg aprenentatge sobre les NGN a través de les diferents investigacions, es va poder observar una problemàtica que afectava de manera transversal als diferents camps d'aplicació de les NGNs i que aquesta podia tenir una afectació en aquests sectors. Aquesta problemàtica consisteix en el baix rendiment durant l'intercanvi de grans volums de dades sobre xarxes amb gran capacitat d'ample de banda i remotament separades geogràficament, conegudes com a xarxes elefant. Concretament, això afecta al cas d'ús d'intercanvi massiu de dades entre regions Cloud (Cloud Data Sharing use case). És per això que es va estudiar aquest cas d'ús i les diferents alternatives a nivell de protocols de transport,. S'estudien les diferents problemàtiques que pateixen els protocols i s'observa per què aquests no són capaços d'arribar a rendiments òptims. Deguda a aquesta situació, s'hipotetiza que la introducció de mecanismes que analitzen les mètriques de la xarxa i que exploten eficientment la capacitat de la mateixa milloren el rendiment dels protocols de transport sobre xarxes elefant heterogènies durant l'enviament massiu de dades. Primerament, es dissenya l’Adaptative and Aggressive Transport Protocol (AATP), un protocol de transport adaptatiu i eficient amb l'objectiu de millorar el rendiment sobre aquest tipus de xarxes elefant. El protocol AATP s'implementa i es prova en un simulador de xarxes i un testbed sota diferents situacions i condicions per la seva validació. Implementat i provat amb èxit el protocol AATP, es decideix millorar el propi protocol, Enhanced-AATP, sobre xarxes elefant heterogènies. Per això, es dissenya un mecanisme basat en el Jitter Ràtio que permet fer aquesta diferenciació. A més, per tal de millorar el comportament del protocol, s’adapta el seu sistema de fairness per al repartiment just dels recursos amb altres fluxos Enhanced-AATP. Aquesta evolució s'implementa en el simulador de xarxes i es realitzen una sèrie de proves. A l'acabar aquesta tesi, es conclou que les Xarxes de Nova Generació tenen molt recorregut i moltes coses a millorar causa de la transformació digital de la societat i de l'aparició de nova tecnologia disruptiva. A més, es confirma que la introducció de mecanismes específics en la concepció i operació dels protocols de transport millora el rendiment d'aquests sobre xarxes elefant heterogènies.Esta tesis por compendio centra sus contribuciones en el aprendizaje e innovación de las Redes de Nueva Generación. Es por ello que se proponen distintas contribuciones en diferentes ámbitos (Smart Cities, Smart Grids, Smart Campus, Smart Learning, Media, eHealth, Industria 4.0 entre otros) mediante la aplicación y combinación de diferentes disciplinas (Internet of Things, Building Information Modeling, Cloud Storage, Ciberseguridad, Big Data, Internet del Futuro, Transformación Digital). Concretamente, se detalla la monitorización sostenible del confort en el Smart Campus, la que se podría considerar mi aportación más representativa dentro de la conceptualización de Redes de Nueva Generación. Dentro de este innovador concepto de monitorización se integran diferentes disciplinas, para poder ofrecer información sobre el nivel de confort de las personas. Esta investigación demuestra el recorrido que existe en la transformación digital de los sectores tradicionales y las NGNs. Durante este largo aprendizaje sobre las NGN a través de las diferentes investigaciones, se pudo observar una problemática que afectaba de manera transversal a los diferentes campos de aplicación de las NGNs y que ésta podía tener una afectación en estos sectores. Esta problemática consiste en el bajo rendimiento durante el intercambio de grandes volúmenes de datos sobre redes con gran capacidad de ancho de banda y remotamente separadas geográficamente, conocidas como redes elefante, o Long Fat Networks (LFNs). Concretamente, esto afecta al caso de uso de intercambio de datos entre regiones Cloud (Cloud Data Data use case). Es por ello que se estudió este caso de uso y las diferentes alternativas a nivel de protocolos de transporte. Se estudian las diferentes problemáticas que sufren los protocolos y se observa por qué no son capaces de alcanzar rendimientos óptimos. Debida a esta situación, se hipotetiza que la introducción de mecanismos que analizan las métricas de la red y que explotan eficientemente la capacidad de la misma mejoran el rendimiento de los protocolos de transporte sobre redes elefante heterogéneas durante el envío masivo de datos. Primeramente, se diseña el Adaptative and Aggressive Transport Protocol (AATP), un protocolo de transporte adaptativo y eficiente con el objetivo maximizar el rendimiento sobre este tipo de redes elefante. El protocolo AATP se implementa y se prueba en un simulador de redes y un testbed bajo diferentes situaciones y condiciones para su validación. Implementado y probado con éxito el protocolo AATP, se decide mejorar el propio protocolo, Enhanced-AATP, sobre redes elefante heterogéneas. Además, con tal de mejorar el comportamiento del protocolo, se mejora su sistema de fairness para el reparto justo de los recursos con otros flujos Enhanced-AATP. Esta evolución se implementa en el simulador de redes y se realizan una serie de pruebas. Al finalizar esta tesis, se concluye que las Redes de Nueva Generación tienen mucho recorrido y muchas cosas a mejorar debido a la transformación digital de la sociedad y a la aparición de nueva tecnología disruptiva. Se confirma que la introducción de mecanismos específicos en la concepción y operación de los protocolos de transporte mejora el rendimiento de estos sobre redes elefante heterogéneas.This compendium thesis focuses its contributions on the learning and innovation of the New Generation Networks. That is why different contributions are proposed in different areas (Smart Cities, Smart Grids, Smart Campus, Smart Learning, Media, eHealth, Industry 4.0, among others) through the application and combination of different disciplines (Internet of Things, Building Information Modeling, Cloud Storage, Cybersecurity, Big Data, Future Internet, Digital Transformation). Specifically, the sustainable comfort monitoring in the Smart Campus is detailed, which can be considered my most representative contribution within the conceptualization of New Generation Networks. Within this innovative monitoring concept, different disciplines are integrated in order to offer information on people's comfort levels. . This research demonstrates the long journey that exists in the digital transformation of traditional sectors and New Generation Networks. During this long learning about the NGNs through the different investigations, it was possible to observe a problematic that affected the different application fields of the NGNs in a transversal way and that, depending on the service and its requirements, it could have a critical impact on any of these sectors. This issue consists of a low performance operation during the exchange of large volumes of data on networks with high bandwidth capacity and remotely geographically separated, also known as Elephant networks, or Long Fat Networks (LFNs). Specifically, this critically affects the Cloud Data Sharing use case. That is why this use case and the different alternatives at the transport protocol level were studied. For this reason, the performance and operation problems suffered by layer 4 protocols are studied and it is observed why these traditional protocols are not capable of achieving optimal performance. Due to this situation, it is hypothesized that the introduction of mechanisms that analyze network metrics and efficiently exploit network’s capacity meliorates the performance of Transport Layer protocols over Heterogeneous Long Fat Networks during bulk data transfers. First, the Adaptive and Aggressive Transport Protocol (AATP) is designed. An adaptive and efficient transport protocol with the aim of maximizing its performance over this type of elephant network.. The AATP protocol is implemented and tested in a network simulator and a testbed under different situations and conditions for its validation. Once the AATP protocol was designed, implemented and tested successfully, it was decided to improve the protocol itself, Enhanced-AATP, to improve its performance over heterogeneous elephant networks. In addition, in order to upgrade the behavior of the protocol, its fairness system is improved for the fair distribution of resources among other Enhanced-AATP flows. Finally, this evolution is implemented in the network simulator and a set of tests are carried out. At the end of this thesis, it is concluded that the New Generation Networks have a long way to go and many things to improve due to the digital transformation of society and the appearance of brand-new disruptive technology. Furthermore, it is confirmed that the introduction of specific mechanisms in the conception and operation of transport protocols improves their performance on Heterogeneous Long Fat Networks

Sensing and Signal Processing in Smart Healthcare

In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive human–computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included