Estimation of Delay using Sensor Data for Reporting through Business Intelligence

2016 ◽  
Author(s):  
Victor Molano ◽  
Alexander Paz
Keyword(s):  
Business Intelligence ◽  
Sensor Data

scholarly journals A Novel Integrated Machine & Business Intelligence Framework for Sensor Data Analysis

2020 ◽  
Author(s):  
Kalyani akiri ◽  
Venkat Rao b
Keyword(s):  
Business Intelligence ◽  
Polynomial Regression ◽  
Binary Classification ◽  
Case Analysis ◽  
Business Case ◽  
Machine Intelligence ◽  
Sensor Data ◽  
Smart Devices ◽  
Business Decision ◽  
Industrial Operations

Increased smart devices in various industries is creating numerous sensors in each of the equipment prompting the need for methods and models for sensor data. Current research proposes a systematic approach to analyze the data generated from sensors attached to industrial equipment. The methodology involves data cleaning, preprocessing, basics statistics, outlier, and anomaly detection. Present study presents the prediction of RUL by using various Machine Learning models like Regression, Polynomial Regression, Random Forest, Decision Tree, XG Boost. Hyper Parameter Optimization is performed to find the optimal parameters for each variable. In each of the model for RUL prediction RMSE, MAE are compared. Outcome of the RUL prediction should be useful for decision maker to drive the business decision; hence Binary classification is performed, and business case analysis is performed. Business case analysis includes the cost of maintenance and cost of non-maintaining a particular asset. Current research is aimed at integrating the machine intelligence and business intelligence so that the industrial operations optimized both in resource and profit.

scholarly journals Frontiers of business intelligence and analytics 3.0: a taxonomy-based literature review and research agenda

2020 ◽  
Vol 13 (2) ◽  
pp. 685-739
Author(s):  
Mathias Eggert ◽  
Jens Alberts
Keyword(s):  
Literature Review ◽  
Business Intelligence ◽  
Research Agenda ◽  
Rapid Development ◽  
Status Quo ◽  
Sensor Data ◽  
Third Wave ◽  
The Third ◽  
Systems Research ◽  
The Status

Abstract Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.

scholarly journals A Novel Integrated Machine & Business Intelligence Framework for Sensor Data Analysis

2021 ◽  
Vol 3 (1) ◽  
pp. 27-38
Author(s):  
S. Kalyani ◽  
A. Mary Sowjanya ◽  
K. Venkat Rao
Keyword(s):  
Data Analysis ◽  
Business Intelligence ◽  
Sensor Data

Operations-Intelligence-Strategy (OIS) Process in Healthcare

2020 ◽  
pp. 88-105
Author(s):  
Xue Ning
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Business Intelligence ◽  
Sensor Data ◽  
Strategy Development ◽  
Healthcare Organizations ◽  
Term Care ◽  
Biomedical Image ◽  
Operational Level ◽  
Starting Point

The healthcare industry has generated a huge amount of data in diverse formats. The big data in healthcare is leading the revolution in healthcare. Collecting data at the operational level is the starting point for the big data-driven healthcare revolution. By analyzing the operational level big data, healthcare organizations can gain the business intelligence for further strategy development, for example how to improve the healthcare quality, how to provide better long-term care, and how to empower the patients. This chapter discusses this process as operations-intelligence-strategy (OIS) process in healthcare. Objectives are understanding how to gain business intelligence from sensor data mining in healthcare, biomedical signal analysis, and biomedical image analysis, and exploring the applications and impacts of the OIS process, with a focus on the sensor data mining in healthcare.

Auditory visualization of landmine detector sensor data

2009 ◽  
Author(s):  
Bradley M. Davis ◽  
Woodrow W. Winchester ◽  
Jason D. Zedlitz
Keyword(s):  
Sensor Data

Business Intelligence (BI)

2004 ◽  
Author(s):  
Jeff Worst ◽  
Keyword(s):  
Business Intelligence

Implementation System of Business Intelligence System In The Company

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Research Library ◽  
Decision Making Process ◽  
Intelligence System ◽  
Business Intelligence Systems

This study aims to determine the stages that must be implemented in building a Business Intelligence System structured and appropriate in building Business Intelligence Systems in an organization, and understand the important aspects that must be considered for investment development Business Intelligence System is increasing. Business must be based on the conditions and needs of the organization in achieving the desired goals. If these conditions occur, then the decision-making process will be better and more accurate. The purpose of this study is to determine the important aspects that must be understood and prepared in using the Business Intelligence System in an organization. The method used is the explanation as well as the research library of several books, articles and other literature.

Od Business Intelligence do Business Performance Management

2012 ◽  
pp. 39-43
Author(s):  
Janusz Nesterak ◽  
Bernard Ziębicki
Keyword(s):  
Performance Management ◽  
Business Intelligence ◽  
Business Performance ◽  
Business Performance Management

Zarządzanie przedsiębiorstwem we współczesnych warunkach wymaga stosowania zaawansowanych systemów umożliwiających gromadzenie i przetwarzanie informacji do postaci użytecznej w podejmowaniu decyzji zarządczych. Możliwości takie stwarzają systemy klasy Business Intelligence. Systemy te obecnie są już szeroko stosowane w krajowych przedsiębiorstwach. Ostatnio coraz popularniejsze stają się systemy określane mianem Business Performance Management, które są traktowane jako kolejna generacja Business Intelligence. Istota systemów Business Performance Management dotychczas nie była szeroko prezentowane w literaturze krajowej. Część badaczy zajmujących się tą tematyką traktuje wymienione kategorie systemów jako tożsame. W artykule przedstawiono istotę systemów Business Performance Management oraz omówiono różnice pomiędzy tą kategorią rozwiązań i systemami Business Intelligence. Omówiono także elementy tworzące systemy Business Performance Management. Przedstawiono również metodykę oraz korzyści stosowania Business Performance Management w przedsiębiorstwach. (abstrakt oryginalny)

Anomaly Detection in Sensor Data

2018 ◽  
Vol 18 (1) ◽  
pp. 20-32 ◽  
Author(s):  
Jong-Min Kim ◽  
Jaiwook Baik
Keyword(s):  
Anomaly Detection ◽  
Sensor Data

Study on Fault Diagnosis of Planetary Gearbox in Unmanned Aerial Vehicle Using Multi sensor Data

2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Unmanned Aerial Vehicle ◽  
Sensor Data ◽  
Planetary Gearbox ◽  
Aerial Vehicle
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