Edge Intelligence : Empowering Intelligence to the Edge of Network

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial intelligence. Edge intelligence aims at enhancing data processing and protects the privacy and security of the data and users. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this article, we present a thorough and comprehensive survey of the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, i.e., edge caching, edge training, edge inference, and edge offloading based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare, and analyze the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, and so on. This article provides a comprehensive survey of edge intelligence and its application areas. In addition, we summarize the development of the emerging research fields and the current state of the art and discuss the important open issues and possible theoretical and technical directions.Peer reviewe

Edge Intelligence : Empowering Intelligence to the Edge of Network

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial intelligence. Edge intelligence aims at enhancing data processing and protects the privacy and security of the data and users. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this article, we present a thorough and comprehensive survey of the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, i.e., edge caching, edge training, edge inference, and edge offloading based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare, and analyze the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, and so on. This article provides a comprehensive survey of edge intelligence and its application areas. In addition, we summarize the development of the emerging research fields and the current state of the art and discuss the important open issues and possible theoretical and technical directions.Peer reviewe

Extending parking assistance for automative user interfaces

Nowadays the trend in the automotive industry is to integrate systems that go beyond the scope of just maneuvering the car. Navigation, communication, and entertainment functions have become usual in most cars. The multitude of sensors present in vehicles today can be used to collect information that can be shared with other drivers in order to make the roads safer and cleaner. A more troubling issue that affects drivers is the search for free parking spots, because of the time waste, fuel consumtion and effort. There are already solutions available that try to help drivers diminish these problems, like crowdsourcing smartphone apps, but they are still far away from being a reliable solution. The overall goal of this thesis is to find new ways of providing parking information to drivers. This information is collected from vehicles which are equipped with latest sensoric hardware capable of detecting parking spaces while driving and distribute these information to the cloud, sharing it with other drivers using smartphones or vehicle's integrated displays. Though the idea is simple, there are many challanges that need to be addressed. The thesis will also look into ways of improving parking surveillance for vehicles to make them less susceptible to vandalism and thefts, by using latest vehicle-integrated video camera systems. A study will be made to see what information drivers want to have related to parking and how this information can be displayed to them. Further, a cloud based-implementation of such a system will be presented in detail and an evaluation will be made to see how the system behaves in the real world.Der aktuelle Trend der Automobilindustrie ist es Systeme zu integrieren, die über das Ziel hinausgehen ein Fahrzeug lediglich zu fahren. Navigations-, Kommunikations- und Entertainmentfunktionen sind inzwischen üblich in vielen Fahrzeugen. Die Vielzahl an verfügbaren Sensoren, die heutzutage in Fahrzeugen verfügbar sind, ermöglichen es Informationen zu sammeln welche mit anderen Fahrern geteilt werden können, um Straßen sicherer und sauberer zu machen. Ein nervenauftreibendes Problem, welches viele Fahrer aufgrund des Zeitverlustes, des Benzinverbrauchs und des Aufwands beeinflusst, ist die Suche nach freien Parkplätzen. Es existieren bereits Lösungen, diese Probleme für den Fahrer verringern, wie z.B. Crowdsourcing Smartphone Apps, aber diese sind immer noch weit davon entfernt zuverlässige Lösungen darzustellen. Das übergreifende Ziel dieser Thesis ist es neue Möglichkeiten zu finden dem Fahrer Parkinformationen zur Verfügung zu stellen. Diese Informationen werden von Fahrzeugen gesammelt, welche mit der neuesten Sensorik ausgestattet sind, die es ermöglicht während der Fahrt Parkplätze zu detektieren und diese Informationen über die Cloud zu verteilen und somit mit anderen Fahrern über Smartphones oder integrierte Displays zu teilen. Obwohl die Idee recht einfach ist gibt es viele Herausforderungen, die bewältigt werden müssen. Dazu wurde auch eine Studie ausgetragen, um zu untersuchen welche Informationen Fahrer im Bezug auf Parken gerne zur Verfügung hätten und wie diese Informationen ihnen angezeigt werden können. Weiterhin werden in dieser Thesis Möglichkeiten evaluiert die Überwachung von Fahrzeugen durch die Verwendung von in Fahrzeug integrierten Videosystemen zu verbessern. Eine Cloud-basierte Implementierung des beschriebenen Systems wird im Detail präsentiert und eine darauf basierende Evaluierung vorgestellt, um zu sehen wie sich derartige Systeme in der realen Welt verhalten

Usability of Urban Air Mobility: Quantitative and Qualitative Assessments of Usage in Emergency Situations

The purpose of these four studies was to determine participants’ willingness to support the use of urban air mobility (UAM) in response to natural disasters, along with the preferred locations to establish vertiports. Study 1 assessed the willingness to support using a mixed factorial design. The findings demonstrated strong, robust support for the use of UAM when responding to natural disasters. Study 2 worked to create and validate a scale that could assess vertiports\u27 current and proposed locations. The Vertiport Usability Scale was developed and shown to have strong psychometric properties to validly assess vertiport locations through a multi-stage process. Study 3 used the Vertiport Usability Scale to understand the most highly preferred locations for vertiports in three conditions from a multi-stage process: temporary disaster locations, permanent disaster locations, and permanent consumer locations. Study 4 was conducted using qualitative methods to complement the earlier quantitative approaches. Through an initial survey and follow-on interview, three themes emerged related to UAM in response to natural disasters and vertiports: 1) human involvement in UAM operations, 2) scenarios for usage, and 3) setup and deployment of vehicles

Integrating vehicle specific power methodology and microsimulation in estimating emissions on urban roundabouts

In this study pollutant emissions were estimated from VSP modal emission rates and the distribution of time spent in each VSP mode obtained from the speed profiles both gathered in the field and simulated in AIMSUN at a sample of urban roundabouts. The versatility of the micro-simulation model for a calibration aimed at improving accuracy of emissions estimates was tested in order to ensure that second-by-second trajectories experienced in the field by a test vehicle through the sampled roundabouts properly reflected the simulated speed profiles. The first results which the thesis will refer, confirmed the feasibility of the smart approach that integrates the use of field-observed and simulated data to estimate emissions at urban roundabouts. It is also revealed friendly in collecting information via smartphone and in the subsequent data analysis and provided suggestions for large-scale data collection through a digital community. Another goal of this research is to investigate about the environmental performance after a conversion of a traditional existing roundabout into a turbo-roundabout. This aspect has been considered a positive approach for a novel attitude in the performance evaluation of road networks to align the infrastructural design with the aim of sustainable and low-emission mobility. The main finding provided from this study is referred to the positive potential of a novel attitude in the conceptualization and performance evaluation of road units in order to align urban infrastructural projects with the worldwide shared long-term ambitions for a low-emission mobility

Proceedings of Abstracts 12th International Conference on Air Quality Science and Application

© 2020 The Author(s). This an open access work distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Final Published versio

Prediction-based techniques for the optimization of mobile networks

Mención Internacional en el título de doctorMobile cellular networks are complex system whose behavior is characterized by the superposition of several random phenomena, most of which, related to human activities, such as mobility, communications and network usage. However, when observed in their totality, the many individual components merge into more deterministic patterns and trends start to be identifiable and predictable. In this thesis we analyze a recent branch of network optimization that is commonly referred to as anticipatory networking and that entails the combination of prediction solutions and network optimization schemes. The main intuition behind anticipatory networking is that knowing in advance what is going on in the network can help understanding potentially severe problems and mitigate their impact by applying solution when they are still in their initial states. Conversely, network forecast might also indicate a future improvement in the overall network condition (i.e. load reduction or better signal quality reported from users). In such a case, resources can be assigned more sparingly requiring users to rely on buffered information while waiting for the better condition when it will be more convenient to grant more resources. In the beginning of this thesis we will survey the current anticipatory networking panorama and the many prediction and optimization solutions proposed so far. In the main body of the work, we will propose our novel solutions to the problem, the tools and methodologies we designed to evaluate them and to perform a real world evaluation of our schemes. By the end of this work it will be clear that not only is anticipatory networking a very promising theoretical framework, but also that it is feasible and it can deliver substantial benefit to current and next generation mobile networks. In fact, with both our theoretical and practical results we show evidences that more than one third of the resources can be saved and even larger gain can be achieved for data rate enhancements.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Albert Banchs Roca.- Presidente: Pablo Serrano Yañez-Mingot.- Secretario: Jorge Ortín Gracia.- Vocal: Guevara Noubi