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Cutting Edge IoT Technology for smart Indian Pharma

Cutting Edge IoT Technology for Smart Indian Pharma

引用

Advance computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Pushpendu Rakshit Pramod Kumar Srivastava Amity Business School Mumbai Amity University Maharashtra India

ISBN: (纸本)9781728177427

Indian pharmaceutical industry has been anticipated best over the years across world. It's a larger supplier of medical facilities to entire world and a leading nation in pharma manufacturing. Internet of things provides the pharma industry with a selection of new personalized market opportunities, better controlled environment of pharma manufacturing, prevent maintenance of equipment and improve diversified supply chain management system. Owing to the deficiencies in transparency, the pharmaceutical manufacturing may be unable to warrant innocuous and safe medicinal production and circulation. Adoption of internet of things could represent a new competitive advantage for pharma companies exhibiting pharma IoT. This is a conceptual explorative research demonstrates future of Indian pharma, which is in a verge to become self-reliant nation. The use of internet of things, artificial intelligence, big data analytics and tracking of customers carrying internet connected digital devices (TCCICDD) and sensors implanted in wearables would help to locate the customer medical history with health monitoring. This would also alert both the clinical manufacturers and users resulting in designing personalized based better future of Indian pharma industry. Future Pharma would see the business link paraphernalia across development and dispersal by using better, more reliable larger volumes of data to revolutionize manufacturing.

关键词： Wearable computers Medical services Companies Manufacturing Internet of Things Medical diagnostic imaging intelligent sensors

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Research on smart party building identity online based on blockchain

Research on smart party building identity online based on bl...

引用

2020 international conference on Cyberspace Innovation of Advanced Technologies, CIAT 2020

作者： Yang, Qubo Zhu, Xiaobing Organization Department of Party Committee Wuhan Donghu University Wuhan China School of Computer Science Wuhan Donghu University Wuhan China

ISBN: (纸本)9781450387828

Under the background of 5g mobile communication technology, artificial intelligence technology will drive the upgrading and innovation of Party building. Key technologies such as blockchain, big data, Internet of things, virtual reality, cloud computing and other key technologies will realize the precision of Party building information, the intellectualization of Party building environment, the situational scene of Party member education and the efficient communication between the party and the masses, and construct a new mode of intelligent party building from the four dimensions of technical environment, Party member's own development, intelligent work and intelligent learning. Changing the thinking, tamping the hardware, defining the position and perfecting the mechanism are the important guarantee for the construction of the new mode of the wisdom party construction. © 2020 ACM.

关键词： Blockchain

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intelligent Agriculture - Agricultural Monitoring and Control Management System

Intelligent Agriculture - Agricultural Monitoring and Contro...

引用

international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Chen, Kaifeng Li, Zhuo Ma, Lili Tang, You Electrical and Information Engineering College Jilin Agricultural Science and Technology University Jilin CityJilin132101 China Smart Agricultural Engineering Research Center of Jilin Province Jilin CityJilin132101 China College of Food Science and Technology Hebei Agricultural University Baoding071001 China

ISBN: (纸本)9783030433055

In the past, agricultural production was affected by changes in the farming environment and the weather, and production conditions were also changeable. However, with the continuous development of society, the continuous progress of science and technology, the accumulation of means of subsistence, human beings have a new definition of agriculture, and intelligent agriculture will become the development trend of agricultural production in the future. intelligent agriculture refers to the detection of various important influencing factors in agricultural production, connecting various information through the network, so as to realize the intelligent management, remote monitoring and resource sharing of these factors, improve production and scientific management and control. With the development of the Internet of things (IoT) technology and the great changes in the mobile application market, the present life has gradually developed into a mobile-centered, intelligent and diversified life. People can monitor the status of the field, remotely manage and control the light or water anytime and anywhere through their mobile devices or the Internet. Under this large industry background, in order to expand the application of Internet of things technology in intelligent agriculture and explore the core technology of Internet of things, relying on its three-terminal framework technology: sensor, server and application, the project of "intelligent agriculture - agricultural monitoring and control management system" based on C/S framework is designed and implemented. © Springer Nature Switzerland AG 2020.

关键词： Information management

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The Internet of Renewable Energy: Big data-Driven smart Grid Management with the Reliability and Security Analysis 1st

The Internet of Renewable Energy: Big Data-Driven Smart Grid...

引用

1st international and 4th National conference on Reliability and Safety Engineering, INCRS 2018

作者： Vaishnavi, P. Deenadayalan, V. Department of Computer Applications Anna University Chennai—BIT Campus Tiruchirappalli India Anna University Tiruchirapalli India

ISBN: (纸本)9789811537455

Renewable energy sources as the solar and wind power are transforming the energy landscape across the world, especially in India. As the government is planning to install 80 GW of solar power generation and 50 GW of wind power generation by 2020, we are presently in an era of increasing solar and wind power generation. The solar and wind energy, along with the associated sensor devices, generate huge amount of data that our traditional warehousing system is unable to store, manage and analyze smart grid, and big data technology provides an answer. Big data is a major research and development direction which provides data storage, retrieval, real-time processing, analytical modeling and visualization. In this paper, we propose the renewable energy architecture along with the integration of big data and power grid. This integration realizes high degree of network connectivity, along with complex security vulnerabilities into the grid. These security challenges, as well as reliability of the system in terms of privacy, integrity authentication and third-party protection have also been discussed in this paper. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data analytics computing (IoT) High performance Renewable energy

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Regional value-added trade network: Topological features and its evolution

Regional value-added trade network: Topological features and...

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

作者： Ju, Shan School of International Economics and Trade Shandong University of Finance and Economics JinanShandong250014 China

ISBN: (纸本)9789811525674

Using the OECD-ICIO (2018) database, this paper constructs an ASEAN+3 value-added trade network and calculates its topological features, including the network as a whole and degree centralities of nodes from 2005 to 2015. Among aggregate topological features, the biggest fluctuation is index of average degree with downward trend while the other four indicators of average geodesic distance, reciprocity correlation, average clustering coefficient and degree assortativity are stable. In addition, the values of degree assortativity have been negative. From the perspective of nodes centralities, Japan and China have been top two according to the results of out-degree centrality and out-closeness centrality of nodes while Malaysia, Singapore, Vietnam, and Thailand rank high on the indices of in-degree centrality and in-closeness centrality of nodes. Brunei Darussalam has been less involved in ASEAN+3 value-added trade network during the sample period. The hub countries such as Japan, China, Malaysia and Singapore need to advance the regional economic cooperation based on the advantages of countries and existing production network. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Complex networks

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Sequence Mining-Based Support Vector Machine with Decision Tree Approach for Efficient Time Series data Classification 3rd

Sequence Mining-Based Support Vector Machine with Decision T...

引用

international conference on data Management, analytics and Innovation (ICDMAI)

作者： Senthil, D. Suseendran, G. Vels Inst Sci Technol & Adv Studies VISTAS Dept Comp Sci Chennai Tamil Nadu India Vels Inst Sci Technol & Adv Studies VISTAS Dept Informat & Technol Sch Comp Sci Chennai Tamil Nadu India

ISBN: (纸本)9789811393648;9789811393631

The growing demand for an efficient approach to classify time series data is bringing forth numerous research efforts in data mining field. Popularly known applications like business, medical and meteorology and so on, typically involves majority of data type in the form of time series. Hence, it is crucial to identify and scope out the potential of time series data owing to its importance on understanding the past trend as well as predicting about what would occur in future. To efficiently analyze the time series data, a system design based on Sliding Window Technique-Improved Association Rule Mining (SWT-IARM) with Enhanced Support Vector Machine (ESVM) has been largely adopted in the recent past. However, it does not provide a high accuracy for larger size of the dataset along with huge number of attributes. To solve this problem the proposed system designed a Sequence Mining algorithm-based Support Vector Machine with Decision Tree algorithm (SM-SVM with DT) for efficient time series analysis. In this proposed work, the larger size of the dataset is considered along with huge number of attributes. The preprocessing is performed using Kalman filtering. The hybrid segmentation method is proposed by combining a clustering technique and Particle Swarm Optimization (PSO) algorithm. Based on the sequence mining algorithm, the rule discovery is performed to reduce the computational complexity prominently by extracting the most frequent and important rules. In order to provide better time series classification results, the Support Vector Machine with Decision Tree (SVM-DT) method is utilized. Finally, the Pattern matching-based modified Spearmen's rank correlation coefficient technique is introduced to provide more similarity and classification results for the given larger time series dataset accurately. The experimental results shows that the proposed system achieves better accuracy, time complexity and rule discovery compared with the existing system.

关键词： Classification Time series Hybrid segmentation Pattern matching Accuracy

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intelligent Navigation System for the Visually Impaired - A Deep Learning Approach 4

Intelligent Navigation System for the Visually Impaired - A ...

引用

4th international conference on computing Methodologies and Communication, ICCMC 2020

作者： Yadav, Deepak Kumar Mookherji, Somsankar Gomes, Joanne Patil, Siddhant St. Francis Institute of Technology Mumbai University Department of Information Technology India

ISBN: (纸本)9781728148892

Visually impaired individuals have been gradually claiming a significant stake in the population demographics. The proposed autonomous device aims to provide a holistic solution by engineering a smart navigation system that relentlessly scans the environment, detects and classifies neighboring objects using a 4 layered Convolutional Neural Network (CNN) that has been trained on a data set containing 2513 permutations of various images of household objects that an individual may encounter in daily life. The CNN follows the 80-20 rule for testing and training the self-learning model enabling it to learn recursively from the error rate. The proposed system then calculates distances of neighboring objects from the user and provides adaptive solutions in real time to manoeuvre the user to safety by providing auditory input in a simplistic manner which considers 10-24 frames per second while drafting the kinematic response for the user. The device has achieved an unprecedented success rate of serving within a response time of less than 50 ms. The accuracy of the CNN algorithm being at 94.6%, also sets a distinguished benchmark as an object detection algorithm thereby contributing to the success in simulations of the proposed device in a constrained environment. © 2020 IEEE.

关键词： intelligent systems

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A Study on Big data Processing Frameworks: Spark and Storm 3rd

A Study on Big Data Processing Frameworks: Spark and Storm

引用

3rd international conference on smart computing and Informatics (SCI)

作者： Deshai, N. Venkataramana, S. Sekhar, B. V. D. S. Srinivas, K. Varma, G. P. Saradhi JNTUK SRKR Engn Coll Dept Informat Technol Bhimavaram Andhra Pradesh India

ISBN: (纸本)9789813296909;9789813296893

Today's internet world impose a trade-off between Peta-byte to Exa-byte being created in digital computer world attributable enormous volume of unstructured datasets being generating from diverse social sites, IOT, Google, Twitter, Yahoo, monitoring surroundings through sensors, etc., is big data (BD). Because second to second doubles the datasets volume size but the shortage of smooth dynamic processing, analysis and scalability techniques. Because the recent high-speed decade we applied only extant methods and common tools about the gigabyte data process and perform computations on whole world huge data. Apache open free source Hadoop is the latest BD weapon can process zetta-byte dimensions of databases by its most developed and popular components as HDFS and map reduce (MR), to get done excellent storage features magnificent and reliable processing on zetta-byte of datasets. MR likes more famous software, popular framework for handling BD existing issues with full parallel, highly distributed, and most scalable manner. Despite, Hadoop, map and reduces tasks have more limitations like poor allocating custom resources, stream way processing, shortage of latency, the deficit of efficient performance, imperfection of optimization, the real-time trend of computations and diverse logical elucidation. We significant most modern progressive features computing procedures. This examination paper shows Apache fastest spark tool, world latest and fastest tool is apache storm has efficient frameworks to conquer those limitations.

关键词： Big data Hadoop Mapreduce Yarn Spark Storm

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Evaluation of smart health technologies with hesitant fuzzy MCDM methods

Evaluation of smart health technologies with hesitant fuzzy ...

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international conference on intelligent and Fuzzy Systems, INFUS 2019

作者： Mukul, Esin Güler, Merve Büyüközkan, Gülçin Industrial Engineering Department Galatasaray University Ortaköy Istanbul34349 Turkey

ISBN: (纸本)9783030237554

smart health is applied in many cities around the world as an approach that has a significant potential to solve the problems with smart technologies. smart health technologies provide effective healthcare services such as personalization of treatments through big data, robotics in cure and care, artificial intelligence support to doctors, etc. The mixed structure of the evaluation of smart health technologies involves many various and contradictory criteria. However, when information is in an uncertain nature, it is difficult to decide on and evaluate. Therefore, hesitant fuzzy linguistic term set (HFLTS) approach is applied to overcome the uncertainty of this multi-criteria decision-making (MCDM) problem. This approach can be used to facilitate experts’ decision-making processes in complex and uncertain situations. In this study, integrated hesitant fuzzy linguistic (HFL) MCDM approach is proposed to evaluate smart health technologies. The criteria are weighted with HFL Analytic Hierarchy Process (AHP), and then, smart health technologies are evaluated with the HFL Combinative Distance-based Assessment (CODAS) method. Lastly, the potential of this approach is presented through a case study. © 2020, Springer Nature Switzerland AG.

关键词： Health

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Research on the Application of Artificial Intelligence in Energy Science and Engineering Monitoring Software Engineering Technology under the Background of Big data 5

Research on the Application of Artificial Intelligence in En...

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2019 5th international conference on Environmental Science and Material Application, ESMA 2019

作者： Liu, Hongying Department of Computer Science and Engineering Guangzhou College of Technology and Business Guangzhou China

Artificial intelligence belongs to the world's leading technology and technology, which can make people's work and life become more intelligent and faster. The arrival of the era of big data accelerates the development of artificial intelligence technology, and the artificial intelligence big data platform begins to appear. Through the analysis of the relationship between big data and artificial intelligence, the AI big data platform and its application are comprehensively discussed, aiming to promote the development of artificial intelligence big data platform and improve the overall level of domestic artificial intelligence. The smart grid is artificial. One of the important application areas of intelligence, the advancement and breakthrough of the new generation of artificial intelligence technology, which is mainly represented by advanced machine learning theory, big data and cloud computing, will promote the development of smart grid. Therefore, an energy science and engineering data monitoring software is needed to realize the monitoring and analysis and unified scheduling of energy science. The article details the design and implementation of data monitoring software for power and energy intelligence. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Big data

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