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4th international conference on Information Systems Design and intelligent Applications (INDIA)

作者： Maheswaran, M. Asirvatham, David Management & Sci Univ Univ DrSeksyen 13 Shah Alam 40100 Selangor Malaysia Taylors Univ Sch Comp & IT Subang Malaysia

ISBN: (纸本)9789811075124;9789811075117

The volume of data is growing exponentially. By 2020, about 1.7 MB of new information will be created every second for every human being on the planet. There will also be about 6 billion smartphone users and over 50 billion smart connected devices in the world. The traditional data analysis techniques will not be scalable to match the storage and processing capabilities of such high volume of data. Moreover, it becomes important to analyse these data at real-time speed. Distributed computing and platforms, such as Hadoop, will play a vital role to process these data at real-time speed to provide users with real-time reports to help users to make critical decisions. Telecommunication industry will be one of the first industries that will need to handle big data. Most of the users are connected all the time creating multiple sessions per user as well as communicating with multiple devices creating the complex high volume of data that need to be analysed. This paper will highlight the conceptual design of a real-time business intelligence model that provides insights into the telecommunication industry.

关键词： Telecommunication industry

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An Edge Based smart Parking Solution Using Camera Networks and Deep Learning

An Edge Based Smart Parking Solution Using Camera Networks a...

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IEEE international conference on Cognitive computing (ICCC) Part of the IEEE World Congress on Services

作者： Bura, Harshitha Lin, Nathan Kumar, Naveen Malekar, Sangram Nagaraj, Sushma Liu, Kaikai San Jose State Univ Comp Engn Dept San Jose CA 95192 USA

ISBN: (纸本)9781538672419

The smart parking industry continues to evolve as an increasing number of cities struggle with traffic congestion and inadequate parking availability. For urban dwellers, few things are more irritating than anxiously searching for a parking space. Research results show that as much as 30% of traffic is caused by drivers driving around looking for parking spaces in congested city areas. There has been considerable activity among researchers to develop smart technologies that can help drivers find a parking spot with greater ease, not only reducing traffic congestion but also the subsequent air pollution. Many existing solutions deploy sensors in every parking spot to address the automatic parking spot detection problems. However, the device and deployment costs are very high, especially for some large and old parking structures. A wide variety of other technological innovations are beginning to enable more adaptable systems including license plate number detection, smart parking meter, and vision-based parking spot detection. In this paper, we propose to design a more adaptable and affordable smart parking system via distributed cameras, edge computing, data analytics, and advanced deep learning algorithms. Specifically, we deploy cameras with zoom-lens and motorized head to capture license plate numbers by tracking the vehicles when they enter or leave the parking lot;cameras with wide angle fish-eye lens will monitor the large parking lot via our custom designed deep neural network. We further optimize the algorithm and enable the real-time deep learning inference in an edge device. Through the intelligent algorithm, we can significantly reduce the cost of existing systems, while achieving a more adaptable solution. For example, our system can automatically detect when a car enters the parking space, the location of the parking spot, and precisely charge the parking fee and associate this with the license plate number.

关键词： Deep learning edge devices smart cities smart parking

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Overview Access and Control Considerations for Internet of Things

Overview Access and Control Considerations for Internet of T...

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international conference on Advances in Big data, computing and data Communication Systems (icABCD)

作者： Gomba, M. Nleya, Bakhe DUT Fac Engn Elect Engn Durban South Africa

ISBN: (纸本)9781538630600

Current IP and other networks such as Power smart Grids are fast evolving thus resulting in diverse connectivity methodologies. This has led to the emergence of "the Internet of Things (IoT) methodology whose goal is to transform the current IP and related networks to Machine-to-Machine (M-2-M) basis. It will seamlessly interconnect the globe and cyberspace via physical objects that embed with intelligent sensors of varying types, this resulting in voluminous generation and exchange of data by an excess of 20 billion Internet-connected objects and sensors (things) by 2020 [ 1]. The resultant structure will benefit mankind by helping us make tough decisions as well as be provisioned of beneficial services. In this paper, we overview both IoT architecture as well as security for IoT associated objects and devices. We will commence with a description of a generalized IoT and security architecture as well as how the various elements constituting them interact. We describe an approach that allows the protection of both constrained and unconstrained IoT devices through robust encryption as well as authentication, so that both can equally leverage from the same security framework, but still maintaining low computational loads, by avoiding excessive computational operations.

关键词： IP Network Encryption Federated Clouds Information Security Internet of Things smart Grid smart Objects

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A Cloud computing Architecture for Eco Route Planning of Heavy Duty Vehicles 14

A Cloud Computing Architecture for Eco Route Planning of Hea...

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14th IEEE international conference on Automation Science and Engineering (IEEE CASE)

作者： Fanti, Maria Pia Mangini, Agostino M. Rotunno, Giuliana Fiume, Giambattista Favenza, Alfredo Gaetani, Manuel Polytech Bari Dept Elect & Informat Engn Bari Italy Univ Trieste Dept Engn & Architecture Trieste Italy Ist Super Mario Boella Turin Italy

ISBN: (纸本)9781538635933

This paper deals with the problem of reducing fuel consumption and pollutant emissions of Heavy Duty Vehicles (HDVs). The overall objective of improving the efficiency of the HDVs can be obtained by employing additional information about road topography, altitude or slope, traffic and weather conditions. To this aim, a cloud computing architecture is proposed to support the fleet companies to manage the HDV route planning. The cloud system receives the transport mission data (departure, destination, waypoints, maximum mission duration time, etc.) and calculates the best eco route and the optimal velocity profiles minimizing fuel consumptions by a cloud-based optimizer. Some case studies show the efficiency (fuel consumption savings and travel times) of the proposed smart technology.

关键词： Eco-routing intelligent route selection heavy duty vehicles emission savings

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Predictive repair and support of engineering systems based on distributed data processing model within an IoT concept 6

Predictive repair and support of engineering systems based o...

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6th IEEE Int Conf on Future Internet of Things and Cloud (W-FiCloud) / 15th Int Conf on Mobile Web and intelligent Information Systems (MobiWis) / 4th Int Conf on Big data Innovations and Applications (Innovate-data)

作者： Kireev, Vasiliy S. Filippov, Stanislav A. Guseva, Anna I. Bochkaryov, Pyotr V. Kuznetsov, Igor A. Migalin, Vladimir Filin, Sergey S. Natl Res Nucl Univ MEPhI Moscow Engn Phys Ins Moscow Russia Konnekt Ltd Dept Sci Res Moscow Russia

ISBN: (纸本)9781538678107

The development of cloud technologies, miniaturization of computing and sensor devices has led to an explosive growth in the field of the Internet of Things. One of the promising research areas within the framework of this concept is smart homes, and, more broadly, smart cities, associated with increasing the values of such parameters of housing and utility services as energy efficiency, resistance to failures, failing and efficiency in general. This article is devoted to the development of an information system for monitoring, remote management and maintenance of engineering systems at the housing infrastructure facilities. The functions of information system include the operational status control of engineering systems on housing infrastructure objects, support, maintenance, repair, prediction and alerts on routine, unplanned and critical situations. This system is based on the concept of " Dew computing - Fog computing - Cloud computing" and is designed to collect and process Big data, collected via the Internet of Things.

关键词： Big data IoT cloud computing fog computing dew computing sensors information systems for monitoring

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2nd international Congress on Information and Communication Technology, ICICT 2016

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2nd international Congress on Information and Communication Technology, ICICT 2016

ISBN: (纸本)9789811055072

The proceedings contain 32 papers. The special focus in this conference is on Information and Communication Technology. The topics include: Preface;automation of railway engine pilot security system using multimodal biometric identification;restricted turn model fault tolerant routing techniques for 3D mesh network-on-chip: An evaluation;power issues of MANET;social media for enhanced e-education at Namibian schools;fifth-level second-generation wavelet-based image fusion algorithm for visual quality enhancement of digital image data;advanced teaching materials of inverted pendulum system by the PLC sequence method;intelligent locker system;precision agriculture system design using wireless sensor network;optimal tree search by a swarm of mobile robots;achieving guaranteed service with fault-tolerant resources in grid;a smart air pollution analytics framework;extracting hidden patterns within road accident data using machine learning techniques;an investigation of the classifiers to detect android malicious apps;a case-based reasoning framework for prediction of stroke;cognitive radio: A network structure perspective;comparative study of N-tier and cloud-based web application using automated load testing tool;the design of ultra-high frequency (UHF) radio frequency identification (RFID) reader antenna;provisioning of healthcare service in cloud;academic analytics implemented for students performance in terms of canonical correlation analysis and chi-square analysis;a pairwise alignment algorithm for long sequences of high similarity;information extraction approaches: A survey;the role of IoT-based devices for the better world;implementation of smart job first dynamic round robin (SJFDRR) scheduling algorithm with smart time quantum in multi-core processing system;feature extraction of protein contact maps from protein 3D-coordinates.

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Cloud computing in housing and utility services monitoring systems 6

Cloud computing in housing and utility services monitoring s...

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作者： Kireev, Vasiliy S. Filippov, Stanislav A. Guseva, Anna I. Bochkaryov, Pyotr V. Kuznetsov, Igor A. Migalin, Vladimir Natl Res Nucl Univ MEPhI Moscow Engn Phys Inst Moscow Russia Konnekt Ltd Dept Sci Res Moscow Russia

ISBN: (纸本)9781538678107

The development of cloud technologies, miniaturization of computing and sensor devices has led to an explosive growth in the field of the Internet of Things. One of the promising research areas within the framework of this concept is smart homes, and, more broadly, smart cities, associated with increasing the values of such parameters of housing and utility services as energy efficiency, resistance to failures, failing and efficiency in general. This article is devoted to the development of an information system for monitoring, remote management and maintenance of engineering systems at the housing infrastructure facilities. The functions of information system include the operational status control of engineering systems on housing infrastructure objects, support, maintenance, repair, prediction and alerts on routine, unplanned and critical situations. data from engineering objects is transferred over a network to the cloud for processing and subsequent analysis. The IoT infrastructure is used for collecting data from engineering objects. The article presents the results of a comparative analysis of technologies and protocols, and substantiates the proposed architectural solution based on the Raspberry and MQTT.

关键词： IoT cloud computing smart home sensors information systems

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南通国际会展中心智慧会展设计的探讨

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智能建筑电气技术 2020年第5期14卷 16-21页

作者：董艺北京市建筑设计研究院有限公司北京100045

现有传统会展智能化系统相对独立,容易形成信息孤岛、信息壁垒,不利于会展建筑的运维管理、资源整合,也不便于展商的信息采集、归纳整理。本文结合工程实例,详述了会展建筑的智能化设计和智慧化转换,将物联网、大数据、云计算、移动互... 详细信息

现有传统会展智能化系统相对独立,容易形成信息孤岛、信息壁垒,不利于会展建筑的运维管理、资源整合,也不便于展商的信息采集、归纳整理。本文结合工程实例,详述了会展建筑的智能化设计和智慧化转换,将物联网、大数据、云计算、移动互联网、地理信息系统等前沿技术进行综合集成,使整个建筑更好地融入智慧城市网络中。

关键词：会展智能化智慧会展三维可视化运维系统智慧指挥调度系统

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Ride: A Resilient IoT data Exchange Middleware Leveraging SDN and Edge Cloud Resources 3

Ride: A Resilient IoT Data Exchange Middleware Leveraging SD...

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3rd ACM/IEEE international conference on Internet of Things Design and Implementation (IoTDI)

作者： Benson, Kyle E. Wang, Guoxi Venkatasubramanian, Nalini Kim, Young-Jin Univ Calif Irvine Donald Bren Sch Informat & Comp Sci Irvine CA 92717 USA Nokia Bell Labs Murray Hill NJ USA

ISBN: (纸本)9781538663127

Internet of Things (IoT) deployments rely on data exchange middleware to manage communications between constrained devices and cloud resources that provide analytics, data storage, and serve user applications. In this paper, we propose the Resilient IoT data Exchange (Ride) middleware that enables resilient operation of IoT applications despite prevalent network failures and congestion. It leverages programmable Software-Defined Networking (SDN)-enabled infrastructure along with both localized edge and cloud services. The two-phase Ride middleware extends existing publish-subscribe-oriented IoT data exchanges according to application-specified resilience requirements and without IoT device client modifications. The first phase, Ride-C, improves IoT data collection by gathering network-awareness via a novel resource-aware adaptive probing mechanism and dynamically redirecting IoT data flows across multiple public and local (edge) cloud data exchange connections. The second phase, Ride-D, uses this information to disseminate time-critical alerts via an intelligent network-aware resilient multicast mechanism. Results from our prototype smart campus testbed implementation, Mininet-based emulated experiments, and larger-scale simulations show that Ride enables network awareness for greater cloud connection up-times, timely fail-over to edge services, and more resilient local alert dissemination.

关键词： IoT data exchange resilience SDN multicast seismic alerting pub-sub failure-detection edge cloud fail-over

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SYSTOR 2018 - Proceedings of the 11th ACM international Systems and Storage conference

SYSTOR 2018 - Proceedings of the 11th ACM International Syst...

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11th ACM international Systems and Storage conference, SYSTOR 2018

ISBN: (纸本)9781450358491

The proceedings contain 23 papers. The topics discussed include: Lerna: parallelizing dependent loops using speculation;chaperone - runtime system for instrumenting applications via partial binary translation;DLIRS: improving low inter-reference recency set cache replacement policy with dynamics;the quick migration of file servers;how to build an insecure system out of perfectly good cryptography;how to best share a big secret;Inkpack: a secure, data-exposure resistant storage system;seamless fail-over for PCIe switched networks;Memomania: from huge to huge-huge pages;collusion in cloud computing auctions;shared cloud object store, governed by permissioned blockchain;space efficient elephant flow detection;Hyplets - multi exception level kernel towards Linux RTOS;towards serverless NFV for 5G media applications;an intelligent recycle bin for smart cities;RestAssured: securing cloud analytics;efficient analytics on encrypted data;accelerating unmodified databases using persistent memory and flash storage tiers;PM aware storage engine for MongoDB;privacy enforcement at a large scale for GDPR compliance;Teechain: reducing storage costs on the blockchain with offline payment channels;applying deep learning to object store caching;and distributed fault-tolerant backup-placement in overloaded wireless sensor networks.

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