A Machine Learning Decision-Support System Improves the Internet of Things’ Smart Meter Operations

2017 ◽  
Vol 4 (4) ◽  
pp. 1056-1066 ◽  
Author(s):  
Joseph Siryani ◽  
Bereket Tanju ◽  
Timothy J. Eveleigh
2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Ju Li ◽  
Muhammad Nazir Jan ◽  
Mohammad Faisal

Big data is a challenging issue as its volume, shape, and size need to be modified in order to extract important information for a specific purpose. The amount of data is rising with the passage of time. This increase in volume can be a challenging issue to analyze the data for smooth industry and the Internet of things. Several tools, techniques, and mechanisms are available to support the handling and management process of such data. Decision support systems can be one of the important techniques which can support big data in order to make decisions on time. The proposed study presents a decision support system to deal with big data and scientific programming for the Industrial Internet of Things. The study has used the tool of SuperDecisions to plot the hierarchy of situations of big data and scientific programming and to select the best alternative among the available.


Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 611 ◽  
Author(s):  
Mohamed Abdel-Basset ◽  
Mai Mohamed ◽  
Victor Chang ◽  
Florentin Smarandache

Many companies have observed the significant benefits they can get via using internet. Since then, large companies have been able to develop business transactions with customers at anytime, anywhere, and in relation to anything, so that we now need a more comprehensive concept than the internet. This concept is the Internet of Things (IoT). IoT will influence decision making style in various phases of selling, buying and marketing process. Therefore, every individual and company should know precisely what IoT is, and how and why they should incorporate it in their operations. This motivated us to propose a smart system based on IoT to help companies and marketers make a powerful marketing strategy via utilizing obtained data from IoT devices. Not only this, but the proposed system can also solve the problems which face companies and customers in online shopping. Since there are different types of the same product, and also different criteria for purchasing which can be different between individuals, customers will need a decision support system to recommend them with the best selection. This motivates us to also propose a neutrsophic technique to deal with unclear and conflicting information which exists usually in the purchasing process. Therefore, the smart system and neutrosophic technique is considered as a comprehensive system which links between customers, companies, marketers to achieve satisfaction for each of them.


Author(s):  
Nadide Caglayan ◽  
Sule Itir Satoglu

Waste management is the method developed to eliminate the negative effects of waste to the environment and human health. The study focuses on the subject vehicle routing. The purpose of this study is to minimize the distance of route for the vehicles which pick up recyclable items collected in containers. For this purpose, a decision support system is proposed based on the internet of things. This is to ensure that the vehicles are routed to filled containers only thanks to the data obtained from sensors. In the chapter, a municipality's recyclable waste container location information was collected and resolved. As a result of the study, the route costs developed by IoT application and the costs incurred in conventional locating results were compared. Finally, the issues that can be improved in relation to the problem have been evaluated.


2016 ◽  
Vol 64 (4) ◽  
pp. 877-886 ◽  
Author(s):  
M. Jasiński ◽  
P. Majtczak ◽  
A. Malinowski

Abstract This paper introduces a fuzzy logic (FL) based decision support system (DSS) for a three-phase bidirectional AC-DC grid converter, working in a modern grid-like smart grid or smart industry. It is assumed that the appliances connected to that grid interact as in the Internet of Things (IoT) or like in the Internet of Everything (IoE) i.e. with a human being located in the chain of data flow. A power electronics AC-DC converter, operating as a shunt active power filter (SAPF) is selected for the case study. A harmonics reduction algorithm is presented as an implementation sample of the DSS. The operation of the SAPF is described and analysed. Experimental results showing the tuning process and operation of the laboratory model are also presented and discussed. Finally, it is shown that the DSS is an elegant and intuitive interface, which can simplify a human’s or machine’s decision-making process. Thanks to the DSS, the meaning of transferred data is translated into linguistic variables that can be understood by non-experts. Hence, it is expected that the amount of transferred data in the smart grid and in the IoE would be reduced. But in the same time, the high quality of the controlled process is retained, as shown by the example of a conventional SAPF.


Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.


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