Deakin University

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Edge4Emotion: An Edge Computing based Multi-source Emotion Recognition Platform for Human-Centric Software Engineering

conference contribution
posted on 2021-01-01, 00:00 authored by Ben Cheng, Owen Wang, Di ShaoDi Shao, Chetan AroraChetan Arora, Thuong HoangThuong Hoang, Xiao LiuXiao Liu
Human emotion recognition has been widely used and intensively studied in many areas such as e-Commerce, online education, healthcare, human-computer interaction and recently human-centric software engineering (HCSE). HCSE investigates human factors in the entire software development lifecycle, and human emotion can be used in many scenarios such as requirement gathering and usability testing. However, even though existing studies have already shown the advantages of emotion recognition with multi-source data such as text, audio and video, the current research and practice in HCSE are primarily based on single-source data. In addition, emotion recognition in HCSE faces several challenges such as multiple participants, changing environments and real-time requirement. To tackle these challenges, this paper proposes Edge4Emotion, a novel edge computing-based multisource human emotion recognition platform for HCSE. Edge4Emotion takes the advantage of the edge computing paradigm to efficiently support the collection of multi-source data such as audio, video and physiological data from various IoT devices, and emotion recognition with both single- and multisource models. As an on-going project, this paper focuses on the platform design and the preliminary evaluation of the platform with representative emotion recognition applications. The platform will be further extended to include more multi-source learning models and serve as an open-source platform for the development and evaluation of multi-source emotion recognition models for HCSE.



Cluster, Cloud and Internet Computing. Symposium (2021 : 21st : Melbourne, Victoria)


610 - 613




Melbourne, Victoria

Place of publication

Piscataway, N.J.

Start date


End date






Publication classification

E1 Full written paper - refereed

Title of proceedings

CCGrid 2021 : Proceedings of the 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing