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A Survey on Edge Intelligence

arXiv.org Artificial Intelligence

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence. The aim of edge intelligence is to enhance the quality and speed of data processing and protect the privacy and security of the data. 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 paper, we present a thorough and comprehensive survey on the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, namely 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 analyse the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, etc. This survey article provides a comprehensive introduction to edge intelligence and its application areas. In addition, we summarise the development of the emerging research field and the current state-of-the-art and discuss the important open issues and possible theoretical and technical solutions.


Computa\c{c}\~ao Urbana da Teoria \`a Pr\'atica: Fundamentos, Aplica\c{c}\~oes e Desafios

arXiv.org Artificial Intelligence

The growing of cities has resulted in innumerable technical and managerial challenges for public administrators such as energy consumption, pollution, urban mobility and even supervision of private and public spaces in an appropriate way. Urban Computing emerges as a promising paradigm to solve such challenges, through the extraction of knowledge, from a large amount of heterogeneous data existing in urban space. Moreover, Urban Computing correlates urban sensing, data management, and analysis to provide services that have the potential to improve the quality of life of the citizens of large urban centers. Consider this context, this chapter aims to present the fundamentals of Urban Computing and the steps necessary to develop an application in this area. To achieve this goal, the following questions will be investigated, namely: (i) What are the main research problems of Urban Computing?; (ii) What are the technological challenges for the implementation of services in Urban Computing?; (iii) What are the main methodologies used for the development of services in Urban Computing?; and (iv) What are the representative applications in this field?


Combo of machine vision and edge computing opens new IoT

#artificialintelligence

Right now sorting boxes onto the appropriate pallet as these goods move through a supply chain is a time-consuming, error-prone manual process. But it doesn't have to be. During the recent PACK Expo in Las Vegas, ADLINK demonstrated how a combination of readily-available technologies can streamline the palletization process. Broadly speaking, using sensing technology to derive new value from physical assets is the entire premise of the internet of things. But beyond sensors, achieving this new level of value from a digitized world requires localized data analysis on top of edge computing infrastructure.


The Making of the Global Datasphere - Connected World

#artificialintelligence

I really think the internet of everything or as we all call the IoT (Internet of Things), continues to surround us by smart devices and smart systems that are constantly sensing, monitoring, listening, and watching everything we do. Many of these systems are also constantly learning from what they sense, see, and hear in their environment, as well as from the feedback they receive from other smart devices and systems. This opens the door to some really helpful insights in life and business. Because so many enterprises recognize the value of data in today's connected world, data centers are a growing sector of the technology space. What can we expect in terms of data in the coming years?


Network Effects: In 2019 IoT And 5G Will Push AI To The Very Edge

#artificialintelligence

Almost thirty years ago, when the internet was launched onto an unsuspecting world, even inventor Tim Berners-Lee and colleagues at CERN could not have predicted the upheaval that would follow. It has been the greatest technology revolution since the industrial original. The combination of Cloud, IoT and AI is driving opportunity and threat in equal measure. Decisions made within organizations will have an impact for years to come. The way in which IoT-Edge links to the broader cloud backend, and the way in which AI integrates across the full processing chain, will be the key to unlocking material innovation and value. After many years of rationalization and stretched infrastructure investments, the IoT represents a tipping point for telcos, the cellular networks on whose backbones the new IoT offerings will be delivered.


Secure Mobile Edge Computing in IoT via Collaborative Online Learning

arXiv.org Machine Learning

To accommodate heterogeneous tasks in Internet of Things (IoT), a new communication and computing paradigm termed mobile edge computing emerges that extends computing services from the cloud to edge, but at the same time exposes new challenges on security. The present paper studies online security-aware edge computing under jamming attacks. Leveraging online learning tools, novel algorithms abbreviated as SAVE-S and SAVE-A are developed to cope with the stochastic and adversarial forms of jamming, respectively. Without utilizing extra resources such as spectrum and transmission power to evade jamming attacks, SAVE-S and SAVE-A can select the most reliable server to offload computing tasks with minimal privacy and security concerns. It is analytically established that without any prior information on future jamming and server security risks, the proposed schemes can achieve ${\cal O}\big(\sqrt{T}\big)$ regret. Information sharing among devices can accelerate the security-aware computing tasks. Incorporating the information shared by other devices, SAVE-S and SAVE-A offer impressive improvements on the sublinear regret, which is guaranteed by what is termed "value of cooperation." Effectiveness of the proposed schemes is tested on both synthetic and real datasets.


Industry 4.0: the fourth industrial revolution - guide to Industrie 4.0

#artificialintelligence

IoT (Internet of Things), the convergence of IT and OT, rapid application development, digital twin simulation models, cyber-physical systems, advanced robots and cobots, additive manufacturing, autonomous production, consistent engineering across the entire value chain, thorough data collection and provisioning, horizontal and vertical integration, the cloud, big data analytics, virtual/augmented reality and edge computing amidst a shift of intelligence towards the edge (artificial intelligence indeed): these are some of the essential technological components of the fourth industrial revolution. Those are quite a lot of terms and components indeed. Yet, Industry 4.0 is a rather vast vision and, increasingly, vast reality that also stretches beyond merely these technological aspects. It is an end-to-end industrial transformation. What makes it all the more fascinating (and at first sight complex) is that convergence of two worlds which have been disconnected thus far: Information ...


Helping automakers drive innovation through connected cars - Internet of Things

#artificialintelligence

Last year the average American spent more than 290 hours behind the wheel of a car – that's roughly equivalent to seven 40-hour weeks – according to a report published by the AAA Foundation. When you expand that globally, the amount of time we spend driving is staggering. That's why automakers like Renault-Nissan, Volvo, BMW and Toyota are embracing the Internet of Things (IoT) to provide new ways to help drivers stay safe, connected and productive during their time on the road.


Predictions: AI, IoT, and blockchain will dominate headlines in 2018

#artificialintelligence

Information technology in 2018 is expected to be more exciting as technologies that were just a concept or in the trial stages in the past years will become a reality, according to technology companies.


IoT - Macro Convergence and Emergence of Markets

@machinelearnbot

In a prior article, we talked about IoT being the connection of the physical and the digital worlds. That is, connecting those things that were physical in nature hitherto and now find a need to be connected to the digital world. This phenomenon about things/objects/entities is also influencing the enterprises in how they are transforming and shaping themselves to survive and thrive in the fast evolving world. The enterprises across consumer, commercial, public, and industrial sectors that were born in the pre-Internet era (Honeywell, ABB, GE, Philips, Siemens, and so on) are making moves to position themselves as digitally transformed companies. More subtle are the moves being made by the Internet era companies (Google, Amazon, etc.) to integrate themselves with the physical world.