Performance Evaluation of Area-Based Segmentation Technique on Ambient Sensor Data for Smart Home Assisted Living
- Title
- Performance Evaluation of Area-Based Segmentation Technique on Ambient Sensor Data for Smart Home Assisted Living
- Creator
- Kavitha R.; Binu S.
- Description
- Activity recognition(AR) is a popular subject of research in the recent past. Recognition of activities performed by human beings, enables the addressing of challenges posed by many real-world applications such as health monitoring, providing security etc. Segmentation plays a vital role in AR. This paper evaluates the efficiency of Area-Based Segmentation using different performance measures. Area-Based segmentation was proposed in our earlier research work. The evaluation of the Area-Based segmentation technique is conducted on four real world datasets viz. Aruba17, Shib010, HH102, and HH113 comprising of data pertaining to an individual, living in the test bed home. Machine learning classifiers, SVM-R, SVM-P, NB and KNN are adopted to validate the performance of Area-Based segmentation. Amongst the four chosen classification algorithms SVM-R exhibits better in all the four datasets. Area-Based segmentation recognise the four test bed activities with accuracies of 0.74, 0.98, 0.66, and 0.99 respectively. The results reveal that Area based segmentation can efficiently segment sensor data stream which aids in accurate recognition of smart home activities. 2019 Procedia Computer Science. All rights reserved.
- Source
- Procedia Computer Science, Vol-165, pp. 314-321.
- Date
- 2019-01-01
- Publisher
- Elsevier B.V.
- Subject
- Activity Recognition; Elder Care; Machine Learning; Segmentation; Smart Home
- Coverage
- Kavitha R., CHRIST (Deemed to Be University), Bangalore, Karnataka, India; Binu S., Bangalore, Karnataka, India
- Rights
- All Open Access; Gold Open Access
- Relation
- ISSN: 18770509
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Kavitha R.; Binu S., “Performance Evaluation of Area-Based Segmentation Technique on Ambient Sensor Data for Smart Home Assisted Living,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20819.