University of Twente Student Theses
Human activity recognition based on energy efficient schemes
Rawat, K. (2020) Human activity recognition based on energy efficient schemes.
|
PDF
1MB |
| Abstract: | Human activity recognition (HAR) has been an active area of research for decades. While traditional sensor-based activity recognition methods have demonstrated high recognition accuracy, they suffer from a significant overhead in terms of energy and computation, especially for resource-constrained devices. To address that, this thesis employs a multi-faceted approach to arrive at an optimized system where the design involves optimization of energy consumption through number of sensors, computation through minimal set of features and reduced classifier size and cost through a nominal hardware platform. |
| Item Type: | Essay (Master) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Embedded Systems MSc (60331) |
| Link to this item: | https://purl.utwente.nl/essays/82563 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page
