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Smart mobility and public transport:Opportunities and challenges in rural and urban areas

Journal of Traffic and Transportation Engineering(English Edition) 2020年第1期7卷 88-97页

作者： Simone Porru Francesco Edoardo Misso Filippo Eros Pani Cino Repetto T Bridge S.p.A. Genoua 16124Italy

Demographic changes in peripheral areas are pressuring the regional public transport systems to adopt innovative strategies.The employment of internet of things(IoT)technologies has proven to be a valid response to mobility challenges in rural areas,and has brought up the concept of"smart land".Framed within the context of the Interreg Central Europe project RUMOBIL,this study tries to shed light on how the deployment of smart mobility solutions within the rural context compare to that within the urban context.Following a literature review,we compared the ease of implementation of different IoT solutions on the urban and the rural contexts,for planners,travellers,and operators,and the relative complexity of common smart mobility issues.In addition,we identified three major challenges for both rural and urban mobility,namely the need for standardized metrics for optimal routes’detection and a dynamic definition of optimal route,as well as the simplification of investments’planning and programming.Both smart cities and smart land can benefit from smart mobility solutions,even if in most cases,each of the two contexts can gain more advantages than the other from the same solution.Even considering the different levels of population scattering,technological infrastructures,social maturity,and economic opportunities,both rural and urban areas offer comparable advantages.For the future of transport,it is up to all policy levels to consider the challenges deriving from expected trends and leverage the untapped potential of IoT technologies to satisfy future travellers’needs and ensure sustainability.

关键词： Transportation engineering Smart mobility Internet of things Public transport Smart city Smart land

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The Basic Units of Living things:A Cell

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数理天地（高中版） 2019年第7期 48-49页

作者：周越不详

What is a cell?Definition,A cell is the basic unit of all living things.It is the unit of life.Some living things consistof only one cell.They are called unicellular(one-celled).Other living things consist of more thanone cell.They are called multicellular(many-celled).All plants and animals are multicellular.God provided his creation with a great variety of cells.Yet,as you will learn,all cells have somethings in common.Basic parts of a cell.

关键词： Basic Units Living things

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Privacy-preserving edge-assisted image retrieval and classification in IoT

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Frontiers of Computer Science 2019年第5期13卷 1136-1147页

作者： Xuan LI Jin LI Siuming YIU Chongzhi GAO Jinbo XIONG College of Mathematics and Informatics Fujian Normal University Fuzhou 350117 China Department of Computer Science The University of Hong Kong Hong Kong 999077 China Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou 350117 China School of Computational Science and Education Software Guangzhou University Guangzhou 510006 China

Internet of things (IoT) has drawn much attention in recent years. However, the image data captured by IoT terminal devices are closely related to users, personal information, which are sensitive and should be protected. Though traditional privacy-preserving outsourced computing solutions such as homomorphic cryptographic primitives can support privacy-preserving computing, they consume a significant amount of computation and storage resources. Thus, it becomes a heavy burden on IoT terminal devices with limited resources. In order to reduce the resource consumption of terminal device, we propose an edge-assisted privacy-preserving outsourced computing framework for image processing, including image retrieval and classification. The edge nodes cooperate with the terminal device to protect data and support privacy-preserving computing on the semitrusted cloud server. Under this framework, edge-assisted privacy-preserving image retrieval and classification schemes are proposed in this paper. The security analysis and performance evaluation show that the proposed schemes greatly reduce the computational, communication and storage burden of IoT terminal device while ensuring image data security.

关键词： Internet of things outsourced computation privacy protection cryptographic primitive image processing

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Toward the Fourth Industrial Revolution on Real-Time Customization

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Journal of Systems Science and Systems Engineering 2020年第2期29卷 127-142页

作者： James M.Tien College of Engineering University of MiamiCoral GablesFlorida 33146USA

The outputs of a national economy can be partitioned into three sets of products:tangible goods(due to manufacturing,construction,extraction and agriculture),intangible services(due to an act of useful effort),and an integration of services and goods or,as initially defined by Tien(2012),servgoods.Actually,these products can also be considered in terms of their relation to the first three Industrial Revolutions:the First Industrial Revolution(circa 1800)was primarily focused on the production of goods;the Second Industrial Revolution(circa 1900)was primarily focused on the mass production of goods;and the Third Industrial Revolution(circa 2000)has been primarily focused on the mass customization of goods,services or servgoods.In this follow-up paper,the Third Industrial Revolution of mass customization continues to accelerate in its evolution and,in many respects,is subsuming the earlier Industrial Revolutions of production and mass production.More importantly,with the advent of real-time decision making,artificial intelligence,Internet of things,mobile networks,and other advanced digital technologies,customization has been extensively enabled,thereby advancing mass customization into a Fourth Industrial Revolution of real-time customization.Moreover,the moral,ethical,security and employment problems associated with both mass and real-time customization must be carefully assessed and mitigated,especially in regard to unintended consequences.Looking ahead and with the advance of artificial general intelligence,this Fourth Industrial Revolution could be forthcoming in about the middle of the 21st Century;it would allow for multiple activities to be simultaneously tackled in real-time and in a customized manner.

关键词： Industrial revolutions big data goods services servgoods connected production mass customization real-time decision making Internet of things artificial intelligence general

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Optimization RFID-enabled Retail Store Management with Complex Event Processing

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International Journal of Automation and computing 2019年第1期16卷 52-64页

作者： Shang-Lian Peng Ci-Jian Liu Jia He Hong-Nian Yu Fan Li College of Computer Science and Technology Chengdu University of Information Technology The Southwest Jiaotong University(SWJTU)-Leeds Joint School Southwest Jiaotong University School of Computer Science and Network Security Dongguan University of Technology Faculty of Science and Technology Bournemouth University

Radio frequency identification(RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing(CEP) based RFID-enabled retail store management is studied, particularly focusing on automated shelf replenishment decisions. We define different types of event queries to describe retailer store workflow action over the RFID data streams on multiple tagging levels(e.g., item level and container level). Non-deterministic finite automata(NFA)based evaluation models are used to detect event patterns. To manage pattern match results in the process of event detection, optimization algorithm is applied in the event model to share event detection results. A simulated RFID-enabled retail store is used to verify the effectiveness of the method, experiment results show that the algorithm is effective and could optimize retail store management workflow.

关键词： Complex event processing(CEP) radio frequency identification(RFID) Internet of things data stream supply chain retail store

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Call for Papers Special Issue on Privacy-Preserving Data Mining for Artificial Intelligence of things

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Big Data Mining and Analytics 2022年第1期5卷 80-80页

作者： Youyang Qu Pierangela Samarati Abderrahim BENSLIMANE Shui Yu Deakin University Australia University of Milan Italy University of Avignon France University of Technology Australia

Artificial Intelligence of things(AIoT)is experiencing unimaginable fast booming with the popularization of end devices and advanced machine learning and data processing techniques.An increasing volume of data is being collected every single second to enable Artificial Intelligence(AI)on the Internet of things(IoT).The explosion of data brings significant benefits to various intelligent industries to provide predictive services and research institutes to advance human knowledge in data-intensive fields.To make the best use of the collected data,various data mining techniques have been deployed to extract data patterns.In classic scenarios,the data collected from IoT devices is directly sent to cloud servers for processing using diverse methods such as training machine learning models.

关键词： IoT things services

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IoT Based Approach in a Power System Network for Optimizing Distributed Generation Parameters

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Computer Modeling in Engineering & Sciences 2019年第6期119卷 541-558页

作者： P.Shanmugapriya J.Baskaran C.Nayanatara D.P.Kothari Sri SaiRam Engineering College Chennai-600044Tamil Nadu.India Adhiparasakthi Engineering College Melmaruvathur.Kanchipuram DistrictTamil Nadu Dean-Research&Development J.D.College of Engineering and ManagementNagpur

The objective of this paper is to provide a robust Virtual Power Plant(VPP)network collaborated with Internet of things(IoT)which uses a conceptual model to integrate each device in the grid.Based on the functionality all the devices which are purely distributed within the grid are networked initially from residential units to substations and up to service data and demand centres.To ensure the trapping of the available power and the efficient transfer of Distributed Generation(DG)power to the grid Distribution Active Control(DAC)strategy is used.Synchronized optimization of DG parameter which includes DG size,location and type are adopted using Dispatch strategy.The case studies are optimized by rescheduling the generation and with load curtailment.Maximized Customer Benefit(MCB)is taken as an objective function and a straight forward solution is given by heuristic search techniques.This method was vindicated in a practical Indian Utility system.This control proposes better performances,ensures reliability and efficiency even under parameter variations along with disturbances which is justified using IEEE 118 bus system and real time Indian utility 63 bus system.Results reveal that the proposed technique proves advantages of low computational intricacy.

关键词： Customer benefit distributed generation internet of things virtual power plant distribution active control

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Churn-Resilient Task Scheduling in a Tiered IoT Infrastructure

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China Communications 2019年第8期16卷 162-175页

作者： Jianhua Fan Xianglin Wei Tongxiang Wang Tian Lan Suresh Subramaniam Nanjing Telecommunication Technology Research Institute Nanjing210007China George Washington University Washington DC20052US

Cloud-as-the-center computing paradigms face multiple challenges in the 5G and Internet of things scenarios, where the service requests are usually initiated by the end-user devices located at network edge and have rigid time constraints. Therefore, Fog computing, or mobile edge computing, is introduced as a promising solution to the service provision in the tiered IoT infrastructure to compensate the shortage of traditional cloud-only architecture. In this cloud-to-things continuum, several cloudlet or mobile edge server entities are placed at the access network to handle the task offloading and processing problems at the network edge. This raises the resource scheduling problem in this tiered system, which is vital for the promotion of the system efficiency. Therefore, in this paper, a scheduling mechanism for the cloudlets or fog nodes are presented, which takes the mobile tasks’ deadline and resources requirements at the same time while promoting the overall profit of the system. First, the problem at the cloudlet, to which IoT devices offload their tasks, is formulated as a multi-dimensional 0-1 knapsack problem. Second, based on ant colony optimization, a scheduling algorithm is presented which treat this problem as a subset selection problem. Third, to promote the performance of the system in the dynamic environments,a churn-refined algorithm is further put forward. A series of simulation experiments have shown that out proposal outperforms many state-of-the-art algorithms in both profit and guarantee ratio.

关键词： fog computing task scheduling deadline constrained internet of things ant colony optimization

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A 130-nm ferroelectric nonvolatile system-on-chip for internet of things

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Journal of Semiconductors 2019年第2期40卷 6-6页

作者： Zhiyi Yu School of Electronics and Information Technology Sun Yat-Sen University

IEEE J.Solid-State Circuits,2019,doi:10.1109/JSSC.2018.2884349Nonvolatile processor(NVP)is promising for energy-harvesting-powered internet-of-things(IoT)devices,owing to its unique capability to sustain computation p... 详细信息

关键词： NVP A 130-nm ferroelectric nonvolatile system-on-chip for internet of things

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The Way to Apply Machine Learning to IoT Driven Wireless Network from Channel Perspective

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China Communications 2019年第1期16卷 148-164页

作者： Wei Li Jianhua Zhang Xiaochuan Ma Yuxiang Zhang Hua Huang Yongmei Cheng Northwestern Polytechnical University State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Key Laboratory of Universal Wireless Communications Beijing University of Posts and Telecommunications Huawei Technologies Co. Ltd.

Internet of things(IoT) is one of the targeted application scenarios of fifth generation(5 G) wireless communication.IoT brings a large amount of data transported on the network.Considering those data,machine learning(ML) algorithms can be naturally utilized to make network efficiently and reliably.However,how to fully apply ML to IoT driven wireless network is still open.The fundamental reason is that wireless communication pursuits the high capacity and quality facing the challenges from the varying and fading wireless channel.So in this paper,we explore feasible combination for ML and IoT driven wireless network from wireless channel perspective.Firstly,a three-level structure of wireless channel fading features is defined in order to classify the versatile propagation environments.This three-layer structure includes scenario,meter and wavelength levels.Based on this structure,there are different tasks like service prediction and pushing,self-organization networking,self adapting largescale fading modeling and so on,which can be abstracted into problems like regression,classification,clustering,etc.Then,we introduce corresponding ML methods to different levelsfrom channel perspective,which makes their interdisciplinary research promisingly.

关键词： 5G Internet of things machine learning wireless channel

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