Internet of Things-enabled Smart Devices in Medical Practice: Healthcare Big Data, Wearable Biometric Sensors, and Real-Time Patient Monitoring

This article proposes an intelligent monitoring system for semiconductor manufacturing equipment, which determines spec-in or spec-out for a wafer in process, using Internet of Things–based big data analysis. The proposed system consists of three phases: initialization, learning, and prediction in real time. The initialization sets the weights and the effective steps for all parameters of equipment to be monitored. The learning performs a clustering to assign similar patterns to the same class. The patterns consist of a multiple time-series produced by semiconductor manufacturing equipment and an after clean inspection measured by the corresponding tester. We modify the Line, Buzo, and Gray algorithm for classifying the time-series patterns. The modified Line, Buzo, and Gray algorithm outputs a reference model for every cluster. The prediction compares a time-series entered in real time with the reference model using statistical dynamic time warping to find the best matched pattern and then calculates a predicted after clean inspection by combining the measured after clean inspection, the dissimilarity, and the weights. Finally, it determines spec-in or spec-out for the wafer. We will present experimental results that show how the proposed system is applied on the data acquired from semiconductor etching equipment.

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Proposal of a Big data System for an Intelligent Management of Water Resources

E3S Web of Conferences ◽

10.1051/e3sconf/202131402002 ◽

2021 ◽

Vol 314 ◽

pp. 02002

Author(s):

Sara Bouziane ◽

Badraddine Aghoutane ◽

Aniss Moumen ◽

Ali Sahlaoui ◽

Anas EL Ouali

Keyword(s):

Big Data ◽

Water Resources ◽

Internet Of Things ◽

Water Resources Management ◽

Smart Devices ◽

Water Losses ◽

Resources Management ◽

Water Leak ◽

Intelligent Management ◽

Agriculture Water

Today, advanced technologies like Big Data, IoT, and Cloud Computing can provide new opportunities and applications in all sectors. In the water sector, water scarcity has become a common concern of different institutions and actors worldwide. In this context, several approaches and systems have been proposed and developed, using these technologies, allowing intelligent water resources management. Internet of Things can be used for assisting the Water Industry to collect data, manage and monitor the water infrastructures using smart devices. Big Data is a strategic technology for analyzing and interpreting collected data into valuable and helpful information for better decision making. This paper presents Big Data and Internet of Things technologies. It addresses theirs uses in some use cases such as municipal water losses, water pollution in agriculture, water Leak detection, etc., to provide new systems and innovative solutions for intelligent water resources management. Based on this study, we propose a Big Data and IoT architecture for intelligent water resources management.

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Trends and Technologies in Big Data Processing

Advances in Computational Intelligence and Robotics - Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence ◽

10.4018/978-1-7998-3038-2.ch002 ◽

2020 ◽

pp. 17-42

Author(s):

Amitava Choudhury ◽

Kalpana Rangra

Keyword(s):

Cloud Computing ◽

Big Data ◽

Internet Of Things ◽

Data Processing ◽

Real Time ◽

Computing Technology ◽

Time Data ◽

Big Data Processing ◽

Real Time Data ◽

Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

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