Recognizing user activity based on accelerometer data from a mobile phone
Activity recognition refers to the ability of a machine/device to recognize the activity of users. This area of research has attracted many works especially related to the context aware and ubiquitous computing area. Wearable accelerometers have been explored for this activity recognition purpose; h...
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iium-13222011-08-15T06:47:16Z http://irep.iium.edu.my/1322/ Recognizing user activity based on accelerometer data from a mobile phone Ayu, Media Anugerah Mantoro, Teddy Abdul Matin, Ahmad Faridi Omar Basamh, Saeed Saleem LB1025 Teaching (principles and practices) T Technology (General) Activity recognition refers to the ability of a machine/device to recognize the activity of users. This area of research has attracted many works especially related to the context aware and ubiquitous computing area. Wearable accelerometers have been explored for this activity recognition purpose; however the impracticality of attaching accelerometers to the user presents significant issues. Accelerometers today are embedded in many mobile devices. This paper explores the potential and possibility of using these accelerometer data to determine user activity recognition. The initial experiments show encouraging results with a very good accuracy rate of 92%. A simple prototype developed supports the implementation of the recognition process conducted. 2011 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/1322/1/Recognizing_user_activity_based_on_accelerometer_data_from_a_mobile_phone.pdf Ayu, Media Anugerah and Mantoro, Teddy and Abdul Matin, Ahmad Faridi and Omar Basamh, Saeed Saleem (2011) Recognizing user activity based on accelerometer data from a mobile phone. In: 2011 IEEE Symposium On Computers & Informatics (ISCI), 20-23 March 2011, Kuala Lumpur. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5958987 |
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LB1025 Teaching (principles and practices) T Technology (General) |
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LB1025 Teaching (principles and practices) T Technology (General) Ayu, Media Anugerah Mantoro, Teddy Abdul Matin, Ahmad Faridi Omar Basamh, Saeed Saleem Recognizing user activity based on accelerometer data from a mobile phone |
description |
Activity recognition refers to the ability of a machine/device to recognize the activity of users. This area of research has attracted many works especially related to the context aware and ubiquitous computing area. Wearable accelerometers have been explored for this activity recognition purpose; however the impracticality of attaching accelerometers to the user presents significant issues. Accelerometers today are embedded in many mobile devices. This paper explores the potential and possibility of using these accelerometer data to determine user activity recognition. The initial experiments show encouraging results with a very good accuracy rate of 92%. A simple prototype developed supports the implementation of the recognition process conducted. |
format |
Conference or Workshop Item |
author |
Ayu, Media Anugerah Mantoro, Teddy Abdul Matin, Ahmad Faridi Omar Basamh, Saeed Saleem |
author_facet |
Ayu, Media Anugerah Mantoro, Teddy Abdul Matin, Ahmad Faridi Omar Basamh, Saeed Saleem |
author_sort |
Ayu, Media Anugerah |
title |
Recognizing user activity based on accelerometer data from a mobile phone |
title_short |
Recognizing user activity based on accelerometer data from a mobile phone |
title_full |
Recognizing user activity based on accelerometer data from a mobile phone |
title_fullStr |
Recognizing user activity based on accelerometer data from a mobile phone |
title_full_unstemmed |
Recognizing user activity based on accelerometer data from a mobile phone |
title_sort |
recognizing user activity based on accelerometer data from a mobile phone |
publishDate |
2011 |
url |
http://irep.iium.edu.my/1322/ http://irep.iium.edu.my/1322/ http://irep.iium.edu.my/1322/1/Recognizing_user_activity_based_on_accelerometer_data_from_a_mobile_phone.pdf |
first_indexed |
2023-09-18T20:08:35Z |
last_indexed |
2023-09-18T20:08:35Z |
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1777407324830302208 |