Low-Cost Automatic Ambient Assisted Living System

Malekmohamad, Hossein; Moemeni, Armaghan; Orun, Ahmet; Purohit, Jayendra Kumar

Abstract

The recent increase in ageing population in countries around the world has brought a lot of attention toward research and development of ambient assisted living (AAL) systems. These systems should be inexpensive to be installed in elderly homes, protecting their privacy and more importantly being non-invasive and smart. In this paper, we introduce an inexpensive system that utilises off-the-shelf sensor to grab RGB-D data. This data is then fed into different learning algorithms for classification different activity types. We achieve a very good success rate (99.9%) for human activity recognition (HAR) with the help of light-weighted and fast random forests (RF).

Citation

Malekmohamad, H., Moemeni, A., Orun, A., & Purohit, J. K. (2018, March). Low-Cost Automatic Ambient Assisted Living System. Presented at 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Athens, Greece

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)
• Start Date: Mar 19, 2018
• End Date: Mar 23, 2018
• Acceptance Date: Feb 1, 2018
• Online Publication Date: Oct 8, 2018
• Publication Date: 2018-03
• Deposit Date: Jul 21, 2020
• Publicly Available Date: Oct 8, 2020
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 693-697
• Book Title: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)
• ISBN: 9781538632284
• DOI: https://doi.org/10.1109/PERCOMW.2018.8480390
• Keywords: Assisted Living, Kinect, Na¨ıve Bayes, Multi Layer Perceptron, Random Forest, Human activity recognition
• Public URL: https://nottingham-repository.worktribe.com/output/4780195
• Publisher URL: https://ieeexplore.ieee.org/document/8480390
• Additional Information: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.