Human Activity Recognition in Smart Cities from Smart Watch Data using LSTM Recurrent Neural Networks

Author:

Kandpal Meenakshi1,Sharma Bhisham2,Barik Rabindra K.3,Chowdhury Subrata4,Patra Sudhansu Shekhar3,Dhaou Imed Ben5

Affiliation:

1. KIIT Deemed to be University,School of Computer Engineering,Bhubaneswar,India

2. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

3. KIIT Deemed to be University,School of Computer Applications,Bhubaneswar,India

4. Sri Venkateshwara College of Engineering and Technology (A),MCA Department,Chittoor,AP,India

5. Dar Al-Hekma University,Hekma School of Engineering, Computing, and Informatics,Department of Computer Science,Jeddah,Saudi Arabia

Publisher

IEEE

Reference28 articles.

1. Activity recognition using cell phone accelerometers

2. DeepEar

3. The Benefits of Personalized Smartphone-Based Activity Recognition Models

4. Applications of mobile activity recognition;lockhart;Proceedings of the ACM Conference on Ubiquitous Computing,2102

5. ZOE. A Cloud-less Dialog-enabled Continuous Sensing Wearable Exploiting Heterogeneous Computation;lane;Proceedings of the 13th Annual International Conference on Mobile Systems Applications and Services,0

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