scholarly journals Micro-Workflows Data Stream Processing Model for Industrial Internet of Things

2021 ◽  
Vol 8 (1) ◽  
Keyword(s):  
Internet Of Things ◽  
Data Stream ◽  
Stream Processing ◽  
Industrial Internet Of Things ◽  
Data Stream Processing ◽  
Industrial Internet

scholarly journals Analysis of Data Stream Processing At Edge Layer for Internet of Things

2020 ◽  
Vol 2 (1) ◽  
pp. 26-37
Author(s):  
Dr. Pasumponpandian
Keyword(s):  
Internet Of Things ◽  
Data Streams ◽  
Data Stream ◽  
Smart Cities ◽  
Stream Processing ◽  
Middle Layer ◽  
Cloud Services ◽  
Decentralized Systems ◽  
Data Stream Processing ◽  
Edge Layer

The progress of internet of things at a rapid pace and simultaneous development of the technologies and the processing capabilities has paved way for the development of decentralized systems that are relying on cloud services. Though the decentralized systems are founded on cloud complexities still prevail in transferring all the information’s that are been sensed through the IOT devices to the cloud. This because of the huge streams of information’s gathered by certain applications and the expectation to have a timely response, incurring minimized delay, computing energy and enhanced reliability. So this kind of decentralization has led to the development of middle layer between the cloud and the IOT, and was termed as the Edge layer, meaning bringing down the service of the cloud to the user edge. The paper puts forth the analysis of the data stream processing in the edge layer taking in the complexities involved in the computing the data streams of IOT in an edge layer and puts forth the real time analytics in the edge layer to examine the data streams of the internet of things offering a data- driven insight for parking system in the smart cities.

A context-driven platform using Internet of things and data stream processing for heating, ventilation and air conditioning systems control

2019 ◽  
Vol 233 (7) ◽  
pp. 877-888
Author(s):  
Fadwa Lachhab ◽  
Mohamed Bakhouya ◽  
Radouane Ouladsine ◽  
Mohammed Essaaidi
Keyword(s):  
Feedback Control ◽  
Internet Of Things ◽  
Air Conditioning ◽  
Data Stream ◽  
State Feedback ◽  
Stream Processing ◽  
State Feedback Control ◽  
Data Stream Processing ◽  
Air Conditioning System ◽  
Air Conditioning Systems

Control approaches of heating, ventilation and air conditioning systems in buildings have been proposed in the past years for minimizing energy consumption and maintaining occupants’ comfort. However, recent studies have shown that context-driven control approaches using Internet of things and data stream processing technologies could further improve energy saving in heating, ventilation and air conditioning systems. In this article, an intelligent control approach using a state feedback technique is introduced to regulate the heating, ventilation and air conditioning system according to the actual context. The proposed thermal state feedback control was then implemented and deployed in our EEBLab to study its effectiveness in a real-setting scenario. The performance of the proposed control was evaluated in a real test-site by deploying a control card that links the controller with the heating, ventilation and air conditioning system. A smart mobile application for real feedback control was also developed and deployed to dynamically adapt the controller to context’s changes. The mobile application and the heating, ventilation and air conditioning system communicate and exchange data under a data acquisition and visualization platform. In this article, a holistic platform that combines Internet of things and data stream processing technologies was developed and deployed in a real-setting scenario. Experiments have been performed, and results are reported to demonstrate the effectiveness and usefulness of the proposed approach in terms of energy saving while maintaining a comfortable room temperature. The proposed state feedback control outperforms the proportional–integral–derivative and ON/OFF approaches in terms of energy consumption while providing acceptable thermal comfort by allowing a neutral thermal sensation with ± 0.30 of predictive mean vote and less than 7% of predicted percentage of dissatisfaction.

An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

2020 ◽  
Author(s):  
Karthik Muthineni
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Internet Of Things ◽  
Intelligent Decision Making ◽  
Internet Of Everything ◽  
Industrial Internet ◽  
Intelligent Decision ◽  
Network Platform ◽  
Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

MONITORING AND PREDICTIVE ANALYTICS OF TECHNOLOGICAL EQUIPMENT ON THE BASED OF INDUSTRIAL INTERNET OF THINGS

2020 ◽  
pp. 7-12
Author(s):  
С.Л. Добрынин ◽  
В.Л. Бурковский
Keyword(s):  
Internet Of Things ◽  
Data Acquisition ◽  
Predictive Analytics ◽  
Actual State ◽  
Monitoring And Control ◽  
Industrial Internet Of Things ◽  
Machining Time ◽  
Industrial Internet ◽  
Acquisition Device ◽  
Data Acquisition Device

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage

RFID data stream processing technology based on CEP

2009 ◽  
Vol 29 (10) ◽  
pp. 2786-2790 ◽  
Author(s):  
Xiao-jia YIN ◽  
Shi-guang JU ◽  
Ying-jie WANG
Keyword(s):  
Data Stream ◽  
Stream Processing ◽  
Processing Technology ◽  
Data Stream Processing ◽  
Rfid Data

Multi-source fusion for weak target images in the Industrial Internet of Things

2021 ◽  
Vol 173 ◽  
pp. 150-159
Author(s):  
Keming Mao ◽  
Gautam Srivastava ◽  
Reza M. Parizi ◽  
Mohammad S. Khan
Keyword(s):  
Internet Of Things ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Weak Target
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