Abstract
M-MOVE-IT is an open-source framework that simplifies data acquisition, annotation, and AI training for wearable technology. It addresses the challenges of synchronizing video and IMU data, making it easier to develop AI models for healthcare, sports, wildlife monitoring, anti-poaching, and livestock management applications. The framework automates and streamlines managing sensors, subjects, and deployments, synchronizing data, and annotating activities. M-MOVE-IT uses the real-time clocks of sensors and an offset annotation step to achieve precise synchronization, automatically parses sensor metadata, and generates annotation tasks. The export module provides data in JSON format for easy use in AI training. M-MOVE-IT's design supports active learning and human-in-the-loop development, enhancing the efficiency and scalability of wearable technology research.
| Original language | English |
|---|---|
| Title of host publication | UbiComp Companion 2024 - Companion of the 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing |
| Editors | Vassilis Kostakos, Judy Kay, Thuong Hoang |
| Place of Publication | New York, NY |
| Publisher | Association for Computing Machinery |
| Pages | 911-915 |
| Number of pages | 5 |
| ISBN (Electronic) | 979-8-4007-1058-2 |
| DOIs | |
| Publication status | Published - 5 Oct 2024 |
| Event | ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2024 - Melbourne, Australia Duration: 5 Oct 2024 → 9 Oct 2024 |
Conference
| Conference | ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2024 |
|---|---|
| Abbreviated title | UbiComp 2024 |
| Country/Territory | Australia |
| City | Melbourne |
| Period | 5/10/24 → 9/10/24 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 15 Life on Land
Keywords
- Active learning (AL)
- Activity recognition
- Multimodal AI
- Multimodal annotation
- Sensor fusion
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Dive into the research topics of 'M-MOVE-IT: Multimodal Machine Observation and Video-Enhanced Integration Tool for Data Annotation'. Together they form a unique fingerprint.Research output
- 2 Citations
- 1 Software
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M-MOVE-IT: Multimodal Machine Observation and Video-Enhanced Integration Tool for Data Annotation
Kamminga, J. W., 2024Research output: Non-textual form › Software › Academic
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