Predictive analytics with surveillance big data

Ayhan, Samet; Pesce, Johnathan; Comitz, Paul; Gerberick, Gary; Bliesner, Steve

doi:10.1145/2447481.2447491

Cited by 14 publications

(4 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An efficient data storage is essential to analyze big data on shop floor. Therefore, the following approach considers storage of the acquired data and describe a scalable service architecture for an analytics system that enables query processing and data analytics of data streams [26]. The service provides uncompressed and correlated data in a warehouse for further analysis.…”

Section: Data Storagementioning

confidence: 99%

“…The service provides uncompressed and correlated data in a warehouse for further analysis. On this occasion, descriptive, predictive and prescriptive analytics tools can be used [26]. From a business point of view the article recognizes that two central prerequisites are necessary for efficient and effective manufacturing processes: process transparency and process responsiveness [27].…”

Section: Data Storagementioning

confidence: 99%

See 1 more Smart Citation

Smart Manufacturing with Prescriptive Analytics

Vater

Harscheidt

Knoll

2019

2019 8th International Conference on Industrial Technology and Management (ICITM)

View full text Add to dashboard Cite

Automotive industry faces challenges in manufacturing like increasingly individualized products with a short lead-time to market and higher quality. Additionally to that, new technologies, such as Internet of Things (IoT), big data, data analytics and cloud computing, are changing the production into the next generation of industry. To address these challenges intelligent manufacturing in combination with data analytics plays an important role. In this sense, the integration of prescriptive analytics in manufacturing may help industry to increase productiveness. This paper provides first a comprehensive review of key elements for prescriptive analytics in manufacturing. Furthermore, this paper highlights requirements for a prescriptive analytics based production control, so called prescriptive automation, and finally points out field of activities in this topic.

show abstract

Section: Data Storagementioning

confidence: 99%

Section: Data Storagementioning

confidence: 99%

Smart Manufacturing with Prescriptive Analytics

Vater

Harscheidt

Knoll

2019

2019 8th International Conference on Industrial Technology and Management (ICITM)

View full text Add to dashboard Cite

show abstract

“…In a related work, an analytics system that enables query processing and predictive analytics over streams of the aviation data is being presented [31]. The related work attempts to address the big data problem with the traditional technologies.…”

Section: Related Workmentioning

confidence: 99%

Big Data Analytics Framework for System Health Monitoring

Kumar

2015

2015 IEEE International Congress on Big Data

View full text Add to dashboard Cite

In this paper, we present our Machine Learning (ML) based big data analytics framework that we tested to improve the quality and performance of Auxiliary Power Units (APU) health monitoring services. We are motivated to develop and apply practical and useful big data analytics technologies for industrial applications in aerospace and aviation. Key contributions of our work include the development and use of our ML algorithms that have been tested and used to analyze multiple data sources and to provide useful insights and increase the ability to predict (1) APU wear from 39%to 56% and (2) APU shutdown events from 19% to 60%. Such system health monitoring can be integrated with the widely used condition based maintenance (CBM) services. Users can use this cloud based analytic toolset and access the big data through any devices (PCs, Tablets, smart phones) anytime and anywhere.

show abstract

“…Cognos analytics 11.1 TM is a platform that enables business to analyze their data intelligently using visual interaction helps in discovering patterns and meaning of the particular business data (Volitich, 2008). Predicative analysis is a feature in the tool that can assist in decision making, strategic planning and risk management (Ayhan, Pesce, & Comitz, et al, 2012).…”

Section: Cognos Analytics 111 Tmmentioning

confidence: 99%

Big data for small businesses: Abstracting security and decision-making tools

Salih

Njenga

Kalpa Publications in Computing

View full text Add to dashboard Cite

The study delineates the understanding of big data as an emergent phenomenon that has brought a notable shift in the relationship between technology and business decision- making. Using grounded theory techniques, the study espouses opportunities and alternative perceptions from small businesses regarding the value that big data may offer in contrast to usage experience by big businesses. Information security lies at the heart of these consideration. The study draws on concepts and tenets from the discipline of information security to support a theoretical underpinning for big data usage in small businesses. A substantive theory has been developed from this work with three distinct concepts emerging that show that financial consideration, management mindset and size consideration play a big part in influencing small business perceptions.

show abstract

Predictive analytics with surveillance big data

Cited by 14 publications

References 19 publications

Smart Manufacturing with Prescriptive Analytics

Smart Manufacturing with Prescriptive Analytics

Big Data Analytics Framework for System Health Monitoring

Big data for small businesses: Abstracting security and decision-making tools

Contact Info

Product

Resources

About