Enabling the use of egocentric camera images for process mining

Kanaris, Alkinoos (2025) Enabling the use of egocentric camera images for process mining. Bachelor's Thesis, Computing Science.

Preview	Text bCS2025KanarisA.pdf Download (6MB) | Preview
	Text Toestemming.pdf Restricted to Registered users only Download (234kB)

Abstract

This thesis explores the use of egocentric camera images in process mining, focusing on how multimodal data can enhance the discovery and conformance analysis of manual and physical processes that are difficult to capture through conventional digital logs. The research employs tools such as ProM and pm4py to analyze event logs, assessing their conformance and usability for business and research applications. By integrating egocentric video data, the study aims to bridge the gap between digital and manual processes, offering new insights into operational transparency and process optimization. The findings indicate a significant improvement in process discovery and conformance analysis when multimodal data is utilized, offering potential applications across industries with high manuality. The requirements for this research include evaluating the effectiveness of egocentric data in creating more comprehensive event logs and assessing how well traditional process mining tools can handle this new data format.

Item Type:	Thesis (Bachelor's Thesis)
Supervisor name:	Karastoyanova, D. and Medema, M.
Degree programme:	Computing Science
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	06 May 2025 08:06
Last Modified:	28 May 2025 06:31
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/35120

Actions (login required)

View Item