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UltraSurfaces: A New Material Design Vision 3rd

UltraSurfaces: A New Material Design Vision

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3rd international conference on intelligent Human Systems Integration (IHSI) - Integrating People and intelligent Systems

作者： Ferrara, Marinella Pasetti, Chiara Politecn Milan Dept Design MADEC Via Durando 38A I-20156 Milan Italy Oslo Sch Architecture & Design AHO Maridalsveien 29 N-0175 Oslo Norway

ISBN: (纸本)9783030395124;9783030395117

We introduce UltraSurfaces (USs), a new material design vision taking advantage of the latest developments in Electronic and smart Materials, and their integration in layered substrates and other materials. The USs can detect phenomena in the environment, record and exchange data while being controlled by remote technologies, interact with users by changing their physical properties, like color, form, sound or light emission, and providing feedback to the user. The USs go a step further than ubiquitous IoT, smart products and environments, enabling new potentialities for any surface to be applied in Future Scenarios of spaces and products. Adopting a Human and User-Centered Design approach, we have been envisioned two Future Scenarios and concepts to convey a better understanding of USs, as well as their potentiality for applications and user's appreciation. We aim to catch the interest of material industries and highlight the challenges design is facing in exploiting the new hybrid materiality of USs.

关键词： UltraSurfaces New material design vision IoT hybrid materiality Materiality smart Aesthetics Experience Full body involvement

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Digidhan Dashboard—Monitoring and Analysis of Digital Payments 1

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4th international conference on ICT for Sustainable Development, ICT4SD 2019

作者： Misra, Deepak Chandra Sethi, Inder Pal Singh Gupta, Om Pradyumana Kapoor, Misha Dwivedi, Ritesh Kumar National Informatics Centre Government of India Block—A CGO Complex Lodhi Road New Delhi110003 India

ISBN: (数字)9789811509360

ISBN: (纸本)9789811509353

In today’s digital era, Government is trying to digitize most of its public services through its e-initiatives to benefit the common man. Digital transactions are taking place for payment of bills, recharge of metro cards, online shopping, and what not. The need of a teller is diminishing from most of the customer interface points. This has resulted in generation of huge transaction data at every service point. After Hon’ble Finance Minister’s announcement of a 2500 crore target of digital transactions in FY 2017–18, many campaigns are being run to promote the growth of digital transactions across the nation. Government is also promoting necessary infrastructure to enable digital transactions in less digitized regions. The Digidhan dashboard is an innovative step taken by the Ministry of Electronics and Information Technology (MeitY) and National Informatics Centre (NIC) to monitor the growth of digital transactions on a central platform. It seamlessly captures the data related with digital payments from various channels like Reserve Bank of India (RBI), National Payments Corporation of India (NPCI), and 110 public sector, private sector, payments, regional rural and foreign banks, ensuring its completeness, accuracy, and relevance. Further, it reveals the potential of data in form of meaningful insights by using data analytics, making it one of most technologically advanced Government portals. The dashboard has paved the way for an advanced mechanism to deal with the volume and variety of digital transactions happening in the nation. It is being further enhanced by development of a chat bot to address user queries. Recently, it was integrated with the smart city portal to capture and promote digital transactions in 100 smart cities. The dashboard has been widely welcomed by all stakeholders and has a lot of scopes to bring in potential change with respect to Government’s idea of digitizing the whole economy. Digidhan dashboard can be accessed at http://***.

关键词： smart city

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Efficient Power Theft Detection using smart Meter data in Advanced Metering Infrastructure

Efficient Power Theft Detection using Smart Meter Data in Ad...

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international conference on intelligent computing and Control Systems (ICICCS)

作者： Manocha, Salil Bansal, Vivek Kaushal, Ishan Bhat, Aruna Delhi Technol Univ Comp Sci Engn New Delhi India Delhi Technol Univ Dept Comp Sci Engn New Delhi India

ISBN: (纸本)9781728148762

Since its discovery, electricity is the basic necessity of human life. It has helped to boost the industrial revolution and any economy, especially the developing ones are highly dependent on a regular and cheap supply of power. But power theft is a major threat to electric companies, it is catastrophic to power distributors and is a reason for financial damage. Regular Manual Inspection of all customers is a solution but it is very time and cost consuming and also leaves scope for corruption. So, AMI (Advanced Metering Infrastructure) has been introduced, which acts as two-way communication between the supplying company and customer via a smart meter which automates the measurement of electric energy usage. But this new technique brings in the possibility of new kinds of thefts and the consumption data compiled from this AMI has the potential to help build a system for fraud detection. Here, a machine learning-based detection methodology is presented, which first applies GMM clustering to categorize data into consumption classes. Then we improve the working of an ANN-based Classification model using a softmax layer and ensembling. The robust dataset used here helps to train the model efficiently and it achieved an astonishing accuracy of 92%. Results indicate the surpassing performance of this method in comparison to other existing detectors.

关键词： AMI ANN Ensembling GMM Power Theft Detection Softmax

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The Application and Research of data Mining Technology in Enterprise Service

The Application and Research of Data Mining Technology in En...

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Wang, Yetong Xing, Kongduo Hainan Vocational University of Science and Technology HaikouHainan China

ISBN: (纸本)9783030627423

The Internet has evolved into a complex of information transmission. Modern computer and information technology as well as the growing network data bring us into the era of big data. Over the years, people have used data mining techniques to analyze and integrate massive amounts of data, discover laws and knowledge from massive amounts of data, and dig out valuable information. This article starts with the research of data mining technology, combing with the features of different fields, analyzes the application of data mining technology in different network platforms. And by the value of data mining in enterprise services to improve business operations, perfect data services on the enterprise platform, and maximize the data mining positive role. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： data mining

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An Approximate Forecasting of Electricity Load and Price of a smart Home Using Nearest Neighbor 13th

An Approximate Forecasting of Electricity Load and Price of ...

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13th international conference on Complex, intelligent, and Software Intensive Systems (CISIS)

作者： Nawaz, Muhammad Javaid, Nadeem Mangla, Fakhar Ullah Munir, Maria Ihsan, Farwa Javaid, Atia Asif, Muhammad COMSATS Univ Islamabad Islamabad 44000 Pakistan Univ Sargodha Sargodha 40100 Pakistan Islamia Univ Bahawalpur Bahawalpur 63100 Pakistan

ISBN: (纸本)9783030223540;9783030223533

In smart Grid, electricity demand and price forecasting literature has focused on Industrial, Buildings, and Residential sector demand, but this paper focuses on short term electricity demand and price forecasting for residential customer. Here we take smart meter data of hourly based from a smart home. First standardize and selected important features by using Recursive Feature Elimination with Linear Support Vector Classifier (RFE-LSVC). Second, do forecasting through K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF) and Support Vector Regression (SVR) models and perform comparative analysis among models against four scenarios and provided best solution among all for individual scenario. This work proposed best solution of smart home's load and price forecasting for smart grid to manage demand response efficiently. We evaluated every Models with Mean Absolute Percentage Error (MAPE).

关键词： Decision trees

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Internet of Things Market Analysis Forecasts, 2020-2030

Internet of Things Market Analysis Forecasts, 2020-2030

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4th World conference on smart Trends in Systems, Security and Sustainability (WorldS4)

作者： Al-Sarawi, Shadi Anbar, Mohammed Abdullah, Rosni Al Hawari, Ahmad B. Univ Sains Malaysia Natl Adv IPv6 Ctr NAv6 George Town 11800 Malaysia Univ Sains Malaysia Sch Comp Sci George Town 11800 Malaysia

ISBN: (数字)9781728168234

ISBN: (纸本)9781728168234

Internet of Things (IoT) environment consists of an enormous smart device that communicate with each other, so they can gather and transmit the sensing information into IoT network. Besides, IoT has now a wide range of live applications such as transportation, smart home, healthcare, industry, smart environment, smart city as well social gaming robots and personal. In parallel, Industrial Internet of Things (IIoT) is empowered by more momentum as businesses integration between Artificial Intelligence (AI), Big-data and IoT technologies. According to the international data Corporation (IDC), the worldwide market for IoT solutions including intelligent systems, connectivity services, infrastructure, applications, security, analytics, and professional services has observed an annual growth rate of 20% CAGR (Compound Annual Growth Rate). Furthermore, IoT will play a crucial role in the near future as per the worldwide statistics. It is expected that there will be a considerable amount of cash flow through the worldwide market in the upcoming years for IoT. At the same time, this paper explicitly provides forecast statistics between 2020 till 2030, as it helps organizations and decision makers in many areas, such as industrial and manufacturing, healthcare and lifestyle, energy and utilization, and many other areas related to IoT spending by sector that show expected growth forecasted in this paper.

关键词： Internet of Things Industrial Internet of Things international data Corporation Internet of Things Artificial Intelligence Compound Annual Growth Rate

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Computational Intelligence Techniques in Vehicle to Everything Networks: A Review 6th

Computational Intelligence Techniques in Vehicle to Everythi...

引用

6th international conference on Advanced intelligent Systems and Informatics, AISI 2020

作者： Sayedahmed, Hamdy A. M. Mohamed, Emadeldin Hefny, Hesham A. Cairo Egypt Faculty of Graduate Studies for Statistical Research Cairo University Giza Egypt

ISBN: (纸本)9783030586683

The remarkable developments in wireless communication technologies in recent years along with the anticipation of further advances in these technologies have stimulated the efforts to investigate vehicle to everything (V2X) communication to increase road safety, improve traffic management, and facilitate infotainment applications. V2X communication is based either on cellular infrastructures such as 4G and 5G, or wireless LAN technologies such as the IEEE 802 protocol family. Several challenges, however, face the deployment of V2X. Examples of these challenges are routing, security, and analysis of collected data. Several research efforts have investigated computational intelligence methods to tackle these issues. In this paper, we review recent advances in computational intelligence in V2X communications. First, we provide preliminaries of V2X communication. Second, we discuss classical and computational intelligence solutions in V2X communication. Last, we present open problems and research challenges that need to be addressed to realize the full potential of V2X systems. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： smart city

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intelligent production logistics system based on internet of things

Intelligent production logistics system based on internet of...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Wang, Haiqin Lu, Guangqiu Liu, Jiahui Qingdao Binhai University QingdaoShandong266555 China

ISBN: (纸本)9789811525674

Internet of things technology is the basis of transformation and upgrading of manufacturing industry and it is also the basis of realization of intelligent manufacturing. The introduction of Internet of things technology in the production workshop can promote the transformation of manufacturing and logistics business models, as well as collaborative production scheduling and logistics scheduling. This paper discusses the goal setting of intelligent workshop production logistics system, the structure of intelligent workshop production logistics system and the key technologies to be solved in constructing intelligent workshop production logistics system. On this basis, the paper analyzes the characteristics of production logistics of tire enterprises, puts forward the train of thought of constructing intelligent production logistics system in rubber refining workshop, component workshop, molding workshop and vulcanization workshop of tire enterprises, and finally analyzes the expected effect. intelligent workshop production logistics system can realize the integration of intelligent manufacturing and intelligent logistics, improve the production efficiency and logistics efficiency of manufacturing enterprises. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Internet of things

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intelligent outlet based on ZMCT103C and GSM

Intelligent outlet based on ZMCT103C and GSM

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Zhao, Hongyu Liu, Zhongfu Liu, Ziyang Zhao, Kaixuan Shi, Yuqi College of Information and Communication Engineering Dalian Minzu University DalianLiaoning116600 China

ISBN: (纸本)9789811525674

With the increasing number of electrical equipment in the home, the safety of household appliances, electricity statistics and remote transmission of information are becoming more and more important. In order to solve this problem, this paper uses STM32F103C8T6 single chip microcomputer as the main control chip to design an intelligent socket system which can measure the power consumption, and display the power consumption information locally, and control the wireless communication with the mobile phone through GSM. The intelligent socket system adopts low power supply, and the collection of power consumption is completed by current transformer ZMCT103C. The communication mode of the system is GSM communication, and the user can plug in the intelligent plug through the mobile phone APP at any place. The system sends text messages to control on-off and timing, so as to achieve the need to save electricity. In this paper, the system software is designed, and the mainstream diagram of the system and the flow chart of the main control modules are given. Finally, the measurement and actual power consumption data of the system are given, and the physical diagram of the system is given. After various tests, the system has the advantages of high reliability and strong measurement and control function, and can be widely used in smart home control system. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Cellular telephones

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2020 international conference on computing and Information Technology, ICCIT 2020

2020 International Conference on Computing and Information T...

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2020 international conference on computing and Information Technology, ICCIT 2020

ISBN: (纸本)9781728126807

The proceedings contain 121 papers. The topics discussed include: using machine learning algorithms for prediction of diabetes mellitus;performance evaluation of the cepstral-based STPS features with Res-TCNetworks for ASR in adverse environments;fingerprint spoofing detection using machine learning;normal/abnormal magnetic resonant brain images detection based on supervised classifiers;cybersecurity and data privacy in the cloudlet for preliminary healthcare big data analytics;improving throughput using cooperating TDMA scheduling of wireless sensor networks;authentication scheme for IoT;IoT security: review and future directions for protection models;comparative study based on reduced kernel monitoring methods using air quality nonlinear process;a database for speech processing based Qur'anic recitation correction;and IoT: security challenges and issues of smart homes/cities.

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