ODSearch: Fast and Resource Efficient On-device Natural Language Search for Fitness Trackers' Data
January 31, 2022 Β· Declared Dead Β· π Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
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Authors
Reza Rawassizadeh, Yi Rong
arXiv ID
2201.13202
Category
cs.IR: Information Retrieval
Cross-listed
cs.HC
Citations
8
Venue
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
Last Checked
4 months ago
Abstract
Mobile and wearable technologies have promised significant changes to the healthcare industry. Although cutting-edge communication and cloud-based technologies have allowed for these upgrades, their implementation and popularization in low-income countries have been challenging. We propose "ODSearch", an On-device Search framework equipped with a natural language interface for mobile and wearable devices. To implement search, "ODSearch" employs compression and Bloom filter, it provides near real-time search query responses without network dependency. In particular, the Bloom filter reduces the temporal scope of the search and compression reduces the size of the data to be searched. Our experiments were conducted on a mobile phone and smartwatch. We compared "ODSearch" with current state-of-the-art search mechanisms, and it outperformed them on average by 53 times in execution time, 26 times in energy usage, and 2.3% in memory utilization.
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