Islab at 23:45, 9 October 2021

2021-10-09T23:45:15Z

Islab: Created page with "{{StudentProjectTemplate |Summary=Forecasting industrial IoT Time Series |Keywords=Time Series Analysis, Time Series Forecasting, IIoT, Alfa Laval |References= Nielsen, Ailee..."

2021-09-23T11:10:06Z

Created page with "{{StudentProjectTemplate |Summary=Forecasting industrial IoT Time Series |Keywords=Time Series Analysis, Time Series Forecasting, IIoT, Alfa Laval |References= Nielsen, Ailee..."

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{{StudentProjectTemplate
|Summary=Forecasting industrial IoT Time Series
|Keywords=Time Series Analysis, Time Series Forecasting, IIoT, Alfa Laval
|References=
Nielsen, Aileen. Practical time series analysis: Prediction with statistics and machine learning. O'Reilly Media, 2019.

Brownlee, Jason. Deep learning for time series forecasting: predict the future with MLPs, CNNs and LSTMs in Python. Machine Learning Mastery, 2018.

Aggarwal, Charu C. Data mining: the textbook. Springer, 2015. [Chapter 14]

Please contact me if you want a soft copy of above references
|Prerequisites=Data Mining Course (Lecture: Time Series Analysis)
|Supervisor=Hadi Fanaee
|Level=Master
|Status=Open
}}
This is a fantastic opportunity to work with Alfa Laval, a world's leader and pioneer in producing separator machines. During the project, you will have this opportunity to gain access to real-life industrial IoT data and gain first-hand experience with such kind of valuable data.

This project aims to investigate the application of time series models for making forecasting for various onboard sensor time series from separator machines. The separators purify oil and water supplies onboard marine vessels.

The main objective of this project is to evaluate the usefulness of time series models in forecasting sensor time series of separator machines. Generating accurate time series forecast opens new opportunities to develop new-generation real-time anomaly detection systems. The benefits of more in-depth exploration are both in terms of technical and business value, including among the others: property damage control, oil Loss reduction, overall machine health, and fuel quality control.

Hadi Fanaee, Assistant Professor
Website: www.fanaee.com
E-mail: hadi.fanaee@hh.se

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 |Summary=Forecasting industrial IoT Time Series
 |Keywords=Time Series Analysis, Time Series Forecasting, IIoT, Alfa Laval
-|References=
+|References=https://www.youtube.com/watch?v=ZuydOEws92s
 |Prerequisites=Data Mining Course (Lecture: Time Series Analysis)
 |Supervisor=Hadi Fanaee

Forecasting Industrial IoT Time Series @AlfaLaval - Revision history

Islab at 23:45, 9 October 2021

Islab: Created page with "{{StudentProjectTemplate |Summary=Forecasting industrial IoT Time Series |Keywords=Time Series Analysis, Time Series Forecasting, IIoT, Alfa Laval |References= Nielsen, Ailee..."