Cloud-Assisted Mood Fatigue Detection System

This paper introduces basic concept of mood fatigue detection and existing solutions as well as some typical solutions, such as mobile sensing and cloud computing technology. In the first place, we sum up main challenges of mood fatigue detection and the direction of future study. Then one type of system implementation is put forward, such system consists of: 1) Wearable devices used to detect the users’ mood fatigue; 2) Clouds data center; 3) Application and service manager. We take overall consideration of many factors like the user’s physiological information, external environment conditions and user behavior, evaluate accurately through big data analytic technology the users’ state of mood fatigue and to what extent shall one keeps vigilant as well as what measures shall be adopted to improve the users’ working performance and alert the users to keep themselves away from the danger. Finally a real system is established in this paper, it is composed of the smart clothing, cloud platform and mobile terminal application.

[1]  Min Chen,et al.  Software-Defined Network Function Virtualization: A Survey , 2015, IEEE Access.

[2]  Min Chen,et al.  iDoctor: Personalized and professionalized medical recommendations based on hybrid matrix factorization , 2017, Future Gener. Comput. Syst..

[3]  Min Chen,et al.  AIWAC: affective interaction through wearable computing and cloud technology , 2015, IEEE Wireless Communications.

[4]  Victor C. M. Leung,et al.  Poster -- SAfeDJ community: situation-aware in-car music delivery for safe driving , 2014, MobiCom.

[5]  Min Chen,et al.  Toward Cost-Effective Mobile Video Streaming via Smart Cache With Adaptive Thresholding , 2015, IEEE Transactions on Broadcasting.

[6]  Depeng Jin,et al.  Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment , 2015, Internet Measurement Conference.

[7]  Min Chen,et al.  Enhanced Fingerprinting and Trajectory Prediction for IoT Localization in Smart Buildings , 2016, IEEE Transactions on Automation Science and Engineering.

[8]  Min Chen,et al.  A unified control and optimization framework for dynamical service chaining in software-defined NFV system , 2015, IEEE Wireless Communications.

[9]  Victor C. M. Leung,et al.  CAP: community activity prediction based on big data analysis , 2014, IEEE Network.

[10]  Min Chen,et al.  Demo: LIVES: Learning through Interactive Video and Emotion-aware System , 2015, MobiHoc.

[11]  R.A. Zoroofi,et al.  Open/Closed Eye Analysis for Drowsiness Detection , 2008, 2008 First Workshops on Image Processing Theory, Tools and Applications.

[12]  Di Wu,et al.  Eco-Aware Online Power Management and Load Scheduling for Green Cloud Datacenters , 2016, IEEE Systems Journal.

[13]  Xiaofei Wang,et al.  Cloud-enabled wireless body area networks for pervasive healthcare , 2013, IEEE Network.

[14]  Wenjian Wang,et al.  QoE-driven spectrum assignment for 5G wireless networks using SDR , 2015, IEEE Wireless Communications.

[15]  V. K. Banga,et al.  Development of a drowsiness warning system based on the fuzzy logic , 2010 .

[16]  Xiaoli Li,et al.  Deep Convolutional Neural Networks on Multichannel Time Series for Human Activity Recognition , 2015, IJCAI.

[17]  Jürgen Schmidhuber,et al.  Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction , 2011, ICANN.

[18]  M. Bennamoun,et al.  3-D Face Recognition Using Curvelet Local Features , 2014, IEEE Signal Processing Letters.

[19]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[20]  Min Chen,et al.  CP-Robot: Cloud-Assisted Pillow Robot for Emotion Sensing and Interaction , 2016 .

[21]  Sheng Chen,et al.  Social-aware D2D communications: qualitative insights and quantitative analysis , 2014, IEEE Communications Magazine.

[22]  Victor C. M. Leung,et al.  EMC: Emotion-aware mobile cloud computing in 5G , 2015, IEEE Network.

[23]  M. Shamim Hossain,et al.  Green Video Transmission in the Mobile Cloud Networks , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[24]  Zhu Han,et al.  Optimal Base Station Scheduling for Device-to-Device Communication Underlaying Cellular Networks , 2016, IEEE Journal on Selected Areas in Communications.

[25]  Ling Guan,et al.  A Deformable 3-D Facial Expression Model for Dynamic Human Emotional State Recognition , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[26]  Jian He,et al.  iCloudAccess: Cost-Effective Streaming of Video Games From the Cloud With Low Latency , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[27]  Limei Peng,et al.  Green data center with IoT sensing and cloud-assisted smart temperature control system , 2016, Comput. Networks.

[28]  Victor C. M. Leung,et al.  EMC: Emotion-aware Mobile Cloud Computing , 2015 .

[29]  Min Chen,et al.  Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring , 2016, Mobile Networks and Applications.

[30]  Sei-Wang Chen,et al.  Real-Time Vision-Based Driver Drowsiness/Fatigue Detection System , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[31]  Meikang Qiu,et al.  Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data , 2017, IEEE Systems Journal.

[32]  Daqiang Zhang,et al.  Context-aware vehicular cyber-physical systems with cloud support: architecture, challenges, and solutions , 2014, IEEE Communications Magazine.

[33]  Min Chen,et al.  Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies , 2015, Mob. Networks Appl..

[34]  Daqiang Zhang,et al.  VCMIA: A Novel Architecture for Integrating Vehicular Cyber-Physical Systems and Mobile Cloud Computing , 2014, Mobile Networks and Applications.

[35]  Pascal Vincent,et al.  Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion , 2010, J. Mach. Learn. Res..

[36]  Guigang Zhang,et al.  Deep Learning , 2016, Int. J. Semantic Comput..

[37]  Peng Sun,et al.  Drowsiness Detection Based on Eyelid Movement , 2010, 2010 Second International Workshop on Education Technology and Computer Science.

[38]  Min Chen,et al.  Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks , 2016, Sensors.

[39]  Sheng Chen,et al.  Multiple Mobile Data Offloading Through Disruption Tolerant Networks , 2014, IEEE Transactions on Mobile Computing.

[40]  S B Puri,et al.  3D FACE RECOGNITION UNDER EXPRESSIONS, OCCLUSIONS AND POSE VARIATION , 2018 .

[41]  Depeng Jin,et al.  Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures , 2016, IEEE Transactions on Vehicular Technology.

[42]  D. de Waard,et al.  The influence of music on mood and performance while driving , 2012, Ergonomics.