scholarly journals Monitoring and control of distributed web services on cloud computing infrastructure

2014 ◽  
Author(s):  
Dimitrios Dechouniotis
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Monitoring And Control ◽  
And Control ◽  
Computing Infrastructure

scholarly journals Energy Efficiency Metrics of University Data Centers

2018 ◽  
Vol 1 (2) ◽  
pp. 64
Author(s):  
Lenonel Hernandez ◽  
Genett Jimenez ◽  
Piedad Marchena
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Large Volume ◽  
Data Center ◽  
Data Centers ◽  
Monitoring And Control ◽  
And Control ◽  
The Impact ◽  
Computing Infrastructure

The data centers are fundamental pieces in the network and computing infrastructure, and evidently today more than ever they are relevant. Since they support the processing, analysis, assurance of the data generated in the network and by the applications in the cloud, which every day increases its volume thanks to technologies such as Internet of Things, Virtualization, and cloud computing, among others. Precisely the management of this large volume of information makes the data centers consume a lot of energy, generating great concern to owners and administrators. Green Data Centers offer a solution to this problem, reducing the impact produced by the data centers in the environment, through the monitoring and control of these. The metrics are the tools that allow us to measure in our case the energy efficiency of the data center and evaluate if it is friendly to the environment. These metrics will be applied to the data centers of the ITSA University Institution, Barranquilla and Soledad campus, and the analysis of these will be carried out. In previous research, the most common metric (PUE) was analyzed to measure the efficiency of the data centers, to verify if the University's data center is friendly to the environment. It is planned to extend this study by carrying out an analysis of several metrics to conclude which is the most efficient and which allows defining the guidelines to update or convert the data center in a friendly environment. 

Internet of Things

2021 ◽  
pp. 19-43
Author(s):  
Imran Khan ◽  
Lídia Oliveira ◽  
Ana Carla Amaro ◽  
Ana Melro
Keyword(s):  
Cloud Computing ◽  
Cultural Heritage ◽  
First Generation ◽  
Safety Monitoring ◽  
Third Generation ◽  
Technological Solution ◽  
Monitoring And Control ◽  
Iot Applications ◽  
Societal Challenges ◽  
And Control

The potential of IoT applications is now recognized, namely the use the IoT as a technological solution for societal challenges such as in health, education, industries, tourism, agricultural, and for this chapter concern, in cultural heritage dissemination. This chapter presents the different evolutionary phases of IoT and its different generations, first-generation experienced embedded things, second-generation a complex social web of things, and third-generation experience the autonomous social objects and cloud computing. This chapter analyzes the characteristics of IoT, for example interconnectivity, intelligence, heterogeneity, safety, monitoring and control, big data and analytics, information sharing and collaboration. Furthermore, this chapter describes the different usage of IoT scenarios applications in some specific areas, such as agriculture, cultural heritage, and tourism.

scholarly journals Aflatoxin detection on direction of the 4.0 age at 3.0 costs

2019 ◽  
Vol 7 (7) ◽  
pp. 338-346 ◽  
Author(s):  
Mariana Matulovic ◽  
Flávio José de Oliveira Morais ◽  
Angela Vacaro de Souza ◽  
Cleber Aalexandre de Amorim ◽  
Luiz Fernando Sommaggio Coletta
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Cloud Computing ◽  
Environmental Variables ◽  
Low Cost ◽  
Machine Learning Algorithms ◽  
Toxic Metabolite ◽  
Monitoring And Control ◽  
Carcinogenic Effects ◽  
And Control

Articulate the most diverse and sophisticated technologies, such as Remote Sensing, Big Data, Cloud Computing, Internet of Things, 3D Printing, among others, is part of universe 4.0, whether industrial or agricultural. Focusing on agricultural context, this paper proposes a low-cost 4.0 device to perform the monitoring and control of certain environmental variables for the detection of aflatoxins in peanut crops. Aflatoxins are toxic metabolite of fungi genus Aspergillus that can cause toxic and carcinogenic effects in humans and animals. The device developed was able to monitor temperature and humidity variations helping the aflatoxins identification. The equipment portability allows its use in silos with encapsulation via Additive Manufacturing, besides the aflatoxin prediction from Machine Learning algorithms.

scholarly journals IP Telephony Applicability in Cloud Computing

2018 ◽  
Vol 3 (CITT2017) ◽  
pp. 128-133
Author(s):  
Francisco Palacios ◽  
Mitchell Vásquez Bermúdez ◽  
Fausto Orozco ◽  
Diana Espinoza Villón
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Open Source ◽  
Open Source Software ◽  
Ip Telephony ◽  
Amazon Web Services ◽  
Private Branch Exchange ◽  
And Control

This paper carries out a research related to the applicability of VoIP over Cloud Computing to guarantee service stability and elasticity of the organizations. In this paper, Elastix is used as an open source software that allows the management and control of a Private Branch Exchange (PBX); and for developing, it is used the services given Amazon Web Services due to their leadership and experience in cloud computing providing security, scalability, backup service and feasibility for the users.

scholarly journals Smart Industrial IoT Monitoring and Control System Based on UAV and Cloud Computing Applied to a Concrete Plant

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3316 ◽  
Author(s):  
Marouane Salhaoui ◽  
Antonio Guerrero-González ◽  
Mounir Arioua ◽  
Francisco J. Ortiz ◽  
Ahmed El Oualkadi ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Control System ◽  
Fog Computing ◽  
Cloud Services ◽  
Industrial Control System ◽  
Monitoring And Control ◽  
Industrial Control ◽  
Monitoring And Control System ◽  
Industrial Iot ◽  
And Control

Unmanned aerial vehicles (UAVs) are now considered one of the best remote sensing techniques for gathering data over large areas. They are now being used in the industry sector as sensing tools for proactively solving or preventing many issues, besides quantifying production and helping to make decisions. UAVs are a highly consistent technological platform for efficient and cost-effective data collection and event monitoring. The industrial Internet of things (IIoT) sends data from systems that monitor and control the physical world to data processing systems that cloud computing has shown to be important tools for meeting processing requirements. In fog computing, the IoT gateway links different objects to the internet. It can operate as a joint interface for different networks and support different communication protocols. A great deal of effort has been put into developing UAVs and multi-UAV systems. This paper introduces a smart IIoT monitoring and control system based on an unmanned aerial vehicle that uses cloud computing services and exploits fog computing as the bridge between IIoT layers. Its novelty lies in the fact that the UAV is automatically integrated into an industrial control system through an IoT gateway platform, while UAV photos are systematically and instantly computed and analyzed in the cloud. Visual supervision of the plant by drones and cloud services is integrated in real-time into the control loop of the industrial control system. As a proof of concept, the platform was used in a case study in an industrial concrete plant. The results obtained clearly illustrate the feasibility of the proposed platform in providing a reliable and efficient system for UAV remote control to improve product quality and reduce waste. For this, we studied the communication latency between the different IIoT layers in different IoT gateways.

New Remote Monitoring and Control System Architectures Based on Cloud Computing

2012 ◽  
Vol 579 ◽  
pp. 312-329 ◽  
Author(s):  
Jui Yu Cheng ◽  
Min Hsiung Hung ◽  
Shih Sung Lin ◽  
Fan Tien Cheng
Keyword(s):  
Cloud Computing ◽  
Control System ◽  
Remote Monitoring ◽  
Remaining Useful Life ◽  
Monitoring And Control ◽  
Monitoring And Control System ◽  
Power Monitoring ◽  
Equipment Monitoring ◽  
Remote Monitoring And Control ◽  
And Control

In recent years, cloud computing has become a new trend of Internet applications and can potentially bring benefits and new business models for various industries and applications. In this paper, we first review two traditional Internet-based remote monitoring and control (RMC) architectures, i.e. AVMS (Automatic Virtual Metrology System) for equipment monitoring and ZDPMCS (ZigBee-based Distributed Power Monitoring and Control System) for power monitoring. Then, their corresponding new architectures based on cloud computing are developed. Specifically, a cloud-computing-based intelligent equipment monitoring architecture (CCIEMA) is proposed. The CCIEMA mainly consists of three parts: cloud side-providing various equipment monitoring related cloud services, equipment side-containing several equipment managers for monitoring and controlling equipment, and client side-including various Web-based GUIs for users to interact with the system. Based on the proposed CCIEMA, various prediction models can be created on the cloud and then downloaded to the equipment manager for performing yield rate prediction, machining precision conjecture, and remaining useful life prediction. By the same approach, we also propose a new power monitoring and control architecture based on cloud computing and ZigBee, called CZPMCA, and show its major operational scenarios. The potential benifits of the proposed CCIEMA and CZPMCA are described as well, compared to the tradiotional RMC architectures. The research results can be useful references for constructing various RMC systems using cloud computing.

AI-Based Cloud Computing Application for Smart Earthmoving Operations

2020 ◽  
Author(s):  
Ashraf Salem ◽  
Osama Moselhi
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Low Cost ◽  
Remote Sensing Data ◽  
Project Managers ◽  
Monitoring And Control ◽  
The Status ◽  
Artificial Neural Network Ann ◽  
Data Acquisition Module ◽  
And Control

This paper introduces a newly developed model for automated monitoring and control of productivity in earthmoving operations. The model makes use of advancements in wireless sensing networks, Internet of Things (IoT), and artificial intelligence. It utilizes data analytics and a dashboard to provide project managers with actionable data on the status of these operations in near-real time. The model consists of two modules; the first is a low-cost open-source remote sensing data acquisition module for collecting data throughout the execution of earthmoving operations. The collected data is sent to a cloud-based MySQL database, in which the second module is designed to (1) measure actual productivity in near-real-time, (2) detecting the location and condition of hauling roads and (3) monitoring and reporting driving conditions over these roads. Artificial Neural Network (ANN) is used in cloud computing for analyzing the productivity to determine and prioritize causes behind experienced loss of productivity from that planned

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