Big data is a term which is nowaday's mostly used in almost all sectors like healthcare, social media, agriculture etc. Just like that one of the areas is medical health care where we always require the help of bi...
Big data is a term which is nowaday's mostly used in almost all sectors like healthcare, social media, agriculture etc. Just like that one of the areas is medical health care where we always require the help of big dataanalytics to Predictive modelling and clinical decision support, disease or safety assessment, public health and research. Medical big data analysis is plagued by missing values, curse of dimensionality, bias control, and observation study's inability to verify causality due to residual confounding and reverse causation. We have different types of big data indexing techniques like apache lucene, apache solr, elastic search, splunk, sphinx etc. to process very huge number of datasets to increase speed, efficiency and performance. The purpose of this work is to investigate and analyze the various indexing systems in order to determine which one is superior for the processing of large amounts of data. Elasticsearch is a RESTful, distributed, and analytical engine that has the potential to tackle a wide variety of issues. It is currently being utilized by a growing number of businesses, and many of them are beginning to incorporate it into their rescue gear in the field of industrial sector.
In IoT-based air quality monitoring system, a set of IoT devices are deployed for sensing of the air quality data at different junction of a smart city. These deployed IoT devices periodically forward the sensed data ...
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ISBN:
(纸本)9789811925412;9789811925405
In IoT-based air quality monitoring system, a set of IoT devices are deployed for sensing of the air quality data at different junction of a smart city. These deployed IoT devices periodically forward the sensed data to the base station for further processing and analytics. Missing of Air Quality Index (AQI) data is very challenging issues in real-time monitoring of AQI in a smart city due to failure of IoT devices, data corruption in the wireless transmission, malfunction of sensors etc. Missing data recovery is a very fundamental issue with real-time IoT-based AQI monitoring system. To solve the missing data recovery problem, this paper has used tensor complete based data recovery models such as Bayesian Gaussian Canonical Polyadic (BGCP) decomposition, Bayesian Augmented Tensor Factorization (BAIT) and High accuracy Low Rank Tensor Completion (HaLRTC) to recovery the AQI missing data. Performance analysis of the tensor complete based data recovery models is evaluated using real time AQI dataset in terms of Root Mean Square Error and Mean Absolute Percentage Error.
In the industry 4.0 era, the 3D visualization and real-time automatic monitoring of intelligent warehousing supported are becoming increasingly important. In intelligent warehousing system, 2D chart mode is key compon...
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With the rapid development of information technology, the logistics industry is undergoing a profound transformation. The traditional logistics management methods can no longer meet the needs of modern business activi...
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ISBN:
(数字)9798331519032
ISBN:
(纸本)9798331519049
With the rapid development of information technology, the logistics industry is undergoing a profound transformation. The traditional logistics management methods can no longer meet the needs of modern business activities, and the emergence of intelligent logistics data analysis platforms provides strong support for improving logistics efficiency and optimizing resource allocation. However, traditional data analysis platforms face many challenges in terms of data security, information traceability, and data sharing. Therefore, researching and implementing an intelligent logistics data analysis platform based on blockchain technology is of great significance for promoting innovative development in the logistics industry. This article aims to explore the research and implementation of an intelligent logistics data analysis platform based on blockchain technology. With the rapid development of the logistics industry, data analysis and processing have become the key to improving logistics efficiency and reducing costs. Traditional data analysis methods have problems such as low data security and difficulty in information traceability. Therefore, this study combines blockchain technology with intelligent logistics data analysis to build an efficient and secure platform.
In the field of artificial intelligence, its applications have penetrated into daily life, such as smart home appliances, navigation, and medical treatment. This article introduces the design and implementation of an ...
In the field of artificial intelligence, its applications have penetrated into daily life, such as smart home appliances, navigation, and medical treatment. This article introduces the design and implementation of an intelligent machine learning system based on artificial intelligence computing. This system utilizes artificial intelligence algorithms to analyze and process a large amount of data, thereby achieving automated learning and prediction of data. At the same time, the system also has good scalability and maintainability, which can adapt to the needs of different fields and application scenarios. The experimental results show that among the four algorithms, their accuracy has reached over 80%, and the time taken is within 3 seconds. The design and implementation of this system provides an effective solution for intelligentdata analysis and decision-making.
With the popularization of cloud computing and the deepening of its application, more and more cloud block storage systems have been put into use. The performance optimization of cloud block storage systems has become...
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In order to improve urban transportation and infrastructure maintenance in smart cities, this research tackles the need for effective vehicle recognition and road condition prediction. The research builds a hybrid mod...
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ISBN:
(数字)9798331529635
ISBN:
(纸本)9798331529642
In order to improve urban transportation and infrastructure maintenance in smart cities, this research tackles the need for effective vehicle recognition and road condition prediction. The research builds a hybrid model that uses both classic image processing methods and convolutional neural networks (CNNs) to reliably identify and quantify automobiles in live video streams. By analyzing visual indications and historical data, the programme reliably monitors traffic flow and assesses road conditions, achieving a 95% recognition rate and counting accuracy. These predictive skills enable timely interventions for road repair, thereby reducing maintenance costs and accident risks. To achieve the safety, efficiency, and sustainability goals of smart cities, the model incorporates real-time traffic monitoring with predictive analytics. This integration provides useful information for infrastructure development and traffic management. Innovative, data-driven solutions to improve urban mobility and infrastructure resilience in modern cities are possible, according to this research.
Postponement tolerant systems administration (DTN) is a technique to PC orchestrates plan that attempts to deal with the specific issues in heterogeneous frameworks that could require steady accessibility. The capacit...
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The development of the transportation industry is of great significance to social progress and the well-being of the people. smart highways are a vital component in the construction of an intelligent transportation sy...
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ISBN:
(数字)9798331530808
ISBN:
(纸本)9798331530815
The development of the transportation industry is of great significance to social progress and the well-being of the people. smart highways are a vital component in the construction of an intelligent transportation system. How to build smarter highways has emerged as a hot topic of discussion within the industry. Cloud computing technology has been widely applied across various industries and has become the core driving force behind the innovation and transformation of traditional sectors. To this end, this paper first systematically reviews the typical application scenarios of cloud computing in the five key aspects of highway construction, management, maintenance, operation, and service. It explores how cloud computing technology enables the intelligent transformation of highways in different links. The aim of this paper is to reveal the operational mechanisms and application values of cloud computing throughout the entire life cycle of smart highways. It provides essential scientific references for the important issue of how to build smart highways, and is also expected to shed light on the relevant practices for the transformation and upgrading of the transportation industry.
This paper presents a community health models and designs a corresponding system using wearable care devices depend on Internet of Things, Cloud computing, dataanalytics and other information technologies. For common...
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