Web 2.0 Mash-Up System for Real Time Data Visualisation and Analysis Using OSS

2015 ◽  
pp. 208-231 ◽  
Author(s):  
Wajid Khan ◽  
Fiaz Hussain ◽  
Edmond C. Prakash
Keyword(s):  
Decision Making ◽  
Vital Role ◽  
Decision Makers ◽  
Resource Utilisation ◽  
Data Visualisation ◽  
Time Data ◽  
Real Time Data ◽  
Analytical Tools ◽  
Transactional Data ◽  
Day By Day

The arrival of E-commerce systems has contributed a lot to the economy and also played a vital role in collecting a huge amount of transactional data in the form of online orders and web enquiries, with such a huge volume of data it is getting difficult day by day to analyse business and consumer behaviour. There is a greater need for business analytical tools to help decision makers understand data properly - and understanding data will lead to amazing things such as hidden trends, effective resource utilisation, decision making ability and understanding business and its core values.

Web 2.0 Mash-Up System for Real Time Data Visualisation and Analysis Using OSS

2018 ◽  
pp. 1418-1441
Author(s):  
Wajid Khan ◽  
Fiaz Hussain ◽  
Edmond C. Prakash
Keyword(s):  
Decision Making ◽  
Vital Role ◽  
Decision Makers ◽  
Resource Utilisation ◽  
Data Visualisation ◽  
Time Data ◽  
Real Time Data ◽  
Analytical Tools ◽  
Transactional Data ◽  
Day By Day

The arrival of E-commerce systems has contributed a lot to the economy and also played a vital role in collecting a huge amount of transactional data in the form of online orders and web enquiries, with such a huge volume of data it is getting difficult day by day to analyse business and consumer behaviour. There is a greater need for business analytical tools to help decision makers understand data properly - and understanding data will lead to amazing things such as hidden trends, effective resource utilisation, decision making ability and understanding business and its core values.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

Real-time data visualisation on the adaptive city platform

2021 ◽  
Author(s):  
Justas Brazauskas ◽  
Rohit Verma ◽  
Vadim Safronov ◽  
Matthew Danish ◽  
Ian Lewis ◽  
...  
Keyword(s):  
Real Time ◽  
Data Visualisation ◽  
Time Data ◽  
Real Time Data

scholarly journals TRANSFORMATION OF THE DECISION SUPPORT SYSTEM MODEL FOR STANDARD SITUATIONS USING INTELLECTUAL AND ANALYTICAL METHODS

2021 ◽  
Vol 21 (3) ◽  
pp. 14-25
Author(s):  
V.V. Antonov ◽  
◽  
K.A. Konev ◽  
G.G. Kulikov ◽  
◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Decision Makers ◽  
Information Support ◽  
Accurate Identification ◽  
Interaction Structure ◽  
Typical Situation ◽  
Analytical Tools

The article discusses the issues of improving the efficiency of decision support activities on a relatively large amount of information. The research relevance is associated with the increasing complexity of control objects, which leads to a decrease in the efficiency of decision-making based on the personal experience of decision-makers, up to complete impossibility. The purpose of the ar-ticle is to analyze the problems faced by decision-makers and the creation of methods to improve the effectiveness of decision-making in typical situations. The article examines the main compo-nents of the intelligent subsystem of the decision support system, which require the use of analytical tools, and also forms the methods interaction structure necessary for the effective formation of sce-narios of information support for decision making. To achieve the goals, a decision support method based on an intelligent component was used, which is aimed at creating an effective infrastructure to sup-port decision-making; methods of identification and categorization, designed to implement the most accurate and correct comparison of the characteristics (state) of the observed situation and the characteristics of a typical situation stored in the knowledge base; correlation methods aimed at finding dependencies between the characteristics of situations and scenarios to solve problems associated with these situa-tions; a method for constructing subject qualimetry, used to form a predictive model to assess the degree of compliance of the selected scenario for solving the current situation. As a result, it was de-termined that an important aspect of decision-making in typical situations is the most accurate identification of the state of the situation, the choice of the best scenario for implementing the solu-tion for this situation and the analysis of the consequences of the selected set of measures. To solve these problems, a method for identifying a situation, a method for finding solution scenarios and a qualimetric method for predicting the effectiveness of the selected scenario have been formed. The article concludes that decision-making activities based on the accumulated experience can be im-proved by using the proposed methods and implementing a decision support system with an intelli-gent component.

scholarly journals OrclassWeb: A Tool Based on the Classification Methodology ORCLASS from Verbal Decision Analysis Framework

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Thais Cristina Sampaio Machado ◽  
Plácido Rogerio Pinheiro ◽  
Isabelle Tamanini
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Analysis ◽  
Decision Support Systems ◽  
Decision Makers ◽  
Analysis Framework ◽  
Verbal Decision Analysis ◽  
Human World ◽  
Support Methods ◽  
Day By Day

The decision making is present in every activity of the human world, either in simple day-by-day problems or in complex situations inside of an organization. Sometimes emotions and reasons become hard to separate; therefore decision support methods were created to help decision makers to make complex decisions, and Decision Support Systems (DSS) were created to aid the application of such methods. The paper presents the development of a new tool, which reproduces the procedure to apply the Verbal Decision Analysis (VDA) methodology ORCLASS. The tool, called OrclassWeb, is software that supports the process of the mentioned DSS method and the paper provides proof of concepts, that which presents its reliability with ORCLASS.

scholarly journals Sensors and tribological systems: applications for industry 4.0

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saquib Rouf ◽  
Ankush Raina ◽  
Mir Irfan Ul Haq ◽  
Nida Naveed
Keyword(s):  
Real Time ◽  
Industry 4.0 ◽  
Developing Economies ◽  
Industrial Applications ◽  
Vital Role ◽  
Critical Parameters ◽  
Time Data ◽  
Content Type ◽  
Real Time Data

Purpose The involvement of wear, friction and lubrication in engineering systems and industrial applications makes it imperative to study the various aspects of tribology in relation with advanced technologies and concepts. The concept of Industry 4.0 and its implementation further faces a lot of barriers, particularly in developing economies. Real-time and reliable data is an important enabler for the implementation of the concept of Industry 4.0. For availability of reliable and real-time data about various tribological systems is crucial in applying the various concepts of Industry 4.0. This paper aims to attempt to highlight the role of sensors related to friction, wear and lubrication in implementing Industry 4.0 in various tribology-related industries and equipment. Design/methodology/approach A through literature review has been done to study the interrelationships between the availability of tribology-related data and implementation of Industry 4.0 are also discussed. Relevant and recent research papers from prominent databases have been included. A detailed overview about the various types of sensors used in generating tribological data is also presented. Some studies related to the application of machine learning and artificial intelligence (AI) are also included in the paper. A discussion on fault diagnosis and cyber physical systems in connection with tribology has also been included. Findings Industry 4.0 and tribology are interconnected through various means and the various pillars of Industry 4.0 such as big data, AI can effectively be implemented in various tribological systems. Data is an important parameter in the effective application of concepts of Industry 4.0 in the tribological environment. Sensors have a vital role to play in the implementation of Industry 4.0 in tribological systems. Determining the machine health, carrying out maintenance in off-shore and remote mechanical systems is possible by applying online-real-time data acquisition. Originality/value The paper tries to relate the pillars of Industry 4.0 with various aspects of tribology. The paper is a first of its kind wherein the interdisciplinary field of tribology has been linked with Industry 4.0. The paper also highlights the role of sensors in generating tribological data related to the critical parameters, such as wear rate, coefficient of friction, surface roughness which is critical in implementing the various pillars of Industry 4.0.

scholarly journals Still normal? Contextualizing real-time data with long-term statistics to monitor anomalies and systematic changes in storm surge activity – Introduction of a prototype web tool storm surge monitor for the German coasts

2021 ◽  
Author(s):  
Xin Liu ◽  
Insa Meinke ◽  
Ralf Weisse
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Storm Surge ◽  
Storm Surges ◽  
Added Value ◽  
Time Data ◽  
Storm Activity ◽  
The Public ◽  
Real Time Data

Abstract. Storm surges represent a major threat to many low-lying coastal areas in the world. While most places can cope with or are more or less adapted to present-day risks, future risks may increase from factors such as sea level rise, subsidence, or changes in storm activity. This may require further or alternative adaptation and strategies. For most places, both forecasts and real-time observations are available. However, analyses of long-term changes or recent severe extremes that are important for decision-making are usually only available sporadically or with substantial delay. In this paper, we propose to contextualize real-time data with long-term statistics to make such information publicly available in near real-time. We implement and demonstrate the concept of a ”storm surge monitor” for tide gauges along the German North Sea and Baltic Sea coasts. It provides automated near real-time assessments of the course and severity of the ongoing storm surge season and its single events. The assessment is provided in terms of storm surge height, frequency, duration, and intensity. It is proposed that such near real-time assessments provide added value to the public and decision-making. It is further suggested that the concept is transferable to other coastal regions threatened by storm surges.

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