Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart Environment
To provide accurate activity recognition within a smart environment, visible spectrum cameras can be used as data capture devices in solution applications. Privacy, however, is a significant concern with regards to monitoring in a smart environment, particularly with visible spectrum cameras. Their...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-01-01
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| Series: | Journal of Sensor and Actuator Networks |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2224-2708/8/1/10 |
| _version_ | 1831718548349648896 |
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| author | Matthew Burns Philip Morrow Chris Nugent Sally McClean |
| author_facet | Matthew Burns Philip Morrow Chris Nugent Sally McClean |
| author_sort | Matthew Burns |
| collection | DOAJ |
| description | To provide accurate activity recognition within a smart environment, visible spectrum cameras can be used as data capture devices in solution applications. Privacy, however, is a significant concern with regards to monitoring in a smart environment, particularly with visible spectrum cameras. Their use, therefore, may not be ideal. The need for accurate activity recognition is still required and so an unobtrusive approach is addressed in this research highlighting the use of a thermopile infrared sensor as the sole means of data collection. Image frames of the monitored scene are acquired from a thermopile infrared sensor that only highlights sources of heat, for example, a person. The recorded frames feature no discernable characteristics of people; hence privacy concerns can successfully be alleviated. To demonstrate how thermopile infrared sensors can be used for this task, an experiment was conducted to capture almost 600 thermal frames of a person performing four single component activities. The person’s position within a room, along with the action being performed, is used to appropriately predict the activity. The results demonstrated that high accuracy levels, 91.47%, for activity recognition can be obtained using only thermopile infrared sensors. |
| first_indexed | 2024-12-21T01:18:11Z |
| format | Article |
| id | doaj.art-e05375d0a00b427082ff074e522a7b1f |
| institution | Directory Open Access Journal |
| issn | 2224-2708 |
| language | English |
| last_indexed | 2024-12-21T01:18:11Z |
| publishDate | 2019-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Sensor and Actuator Networks |
| spelling | doaj.art-e05375d0a00b427082ff074e522a7b1f2022-12-21T19:20:44ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082019-01-01811010.3390/jsan8010010jsan8010010Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart EnvironmentMatthew Burns0Philip Morrow1Chris Nugent2Sally McClean3School of Computing, Ulster University, Belfast BT37 0QB, Northern Ireland, UKSchool of Computing, Ulster University, Belfast BT37 0QB, Northern Ireland, UKSchool of Computing, Ulster University, Belfast BT37 0QB, Northern Ireland, UKSchool of Computing, Ulster University, Belfast BT37 0QB, Northern Ireland, UKTo provide accurate activity recognition within a smart environment, visible spectrum cameras can be used as data capture devices in solution applications. Privacy, however, is a significant concern with regards to monitoring in a smart environment, particularly with visible spectrum cameras. Their use, therefore, may not be ideal. The need for accurate activity recognition is still required and so an unobtrusive approach is addressed in this research highlighting the use of a thermopile infrared sensor as the sole means of data collection. Image frames of the monitored scene are acquired from a thermopile infrared sensor that only highlights sources of heat, for example, a person. The recorded frames feature no discernable characteristics of people; hence privacy concerns can successfully be alleviated. To demonstrate how thermopile infrared sensors can be used for this task, an experiment was conducted to capture almost 600 thermal frames of a person performing four single component activities. The person’s position within a room, along with the action being performed, is used to appropriately predict the activity. The results demonstrated that high accuracy levels, 91.47%, for activity recognition can be obtained using only thermopile infrared sensors.http://www.mdpi.com/2224-2708/8/1/10thermopileinfraredsensorsactivity recognitionimage processingsensor fusionactivities of daily livingcomputer visionsmart environments |
| spellingShingle | Matthew Burns Philip Morrow Chris Nugent Sally McClean Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart Environment Journal of Sensor and Actuator Networks thermopile infrared sensors activity recognition image processing sensor fusion activities of daily living computer vision smart environments |
| title | Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart Environment |
| title_full | Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart Environment |
| title_fullStr | Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart Environment |
| title_full_unstemmed | Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart Environment |
| title_short | Fusing Thermopile Infrared Sensor Data for Single Component Activity Recognition within a Smart Environment |
| title_sort | fusing thermopile infrared sensor data for single component activity recognition within a smart environment |
| topic | thermopile infrared sensors activity recognition image processing sensor fusion activities of daily living computer vision smart environments |
| url | http://www.mdpi.com/2224-2708/8/1/10 |
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