RECORD
A Novel Smartphone-Based Activity Recognition Modeling Method for Tracked Equipment in Forest Operations
- Title:
- A Novel Smartphone-Based Activity Recognition Modeling Method for Tracked Equipment in Forest Operations
- Creator:
- Becker, Ryer M.; Keefe, Robert F.
- Date Created:
- 2022-04-06
- Description:
- Activity recognition modelling using smartphone Inertial Measurement Units (IMUs) is an underutilized resource defining and assessing work efficiency for a wide range of natural resource management tasks. This study focused on the initial development and validation of a smartphone-based activity recognition system for excavator-based mastication equipment working in Ponderosa pine (Pinus ponderosa) plantations in North Idaho, USA. During mastication treatments, sensor data from smartphone gyroscopes, accelerometers, and sound pressure meters (decibel meters) were collected at three sampling frequencies (10, 20, and 50 hertz (Hz)). These data were then separated into 9 time domain features using 4 sliding window widths (1, 5, 7.5 and 10 seconds) and two levels of window overlap (50% and 90%). Random forest machine learning algorithms were trained and evaluated for 40 combinations of model parameters to determine the best combination of parameters. 5 work elements (masticate, clear, move, travel, and delay) were classified with the performance metrics for individual elements of the best model (50 Hz, 10 second window, 90% window overlap) falling within the following ranges: area under the curve (AUC) (95.0% - 99.9%); sensitivity (74.9% - 95.6%); specificity (90.8% - 99.9%); precision (81.1% - 98.3%); F1-score (81.9% - 96.9%); balanced accuracy (87.4% - 97.7%). Smartphone sensors effectively characterized individual work elements of mechanical fuel treatments. This study is the first example of developing a smartphone-based activity recognition model for ground-based forest equipment. The continued development and dissemination of smartphone-based activity recognition models may assist land managers and operators with ubiquitous, manufacturer-independent systems for continuous and automated time study and production analysis for mechanized forest operations.
- Document Type:
- Research Article
- Subjects:
- UIEF activity recognition modeling inertial measurement units IMUs work efficiency forest operations tracked harvesting equipment tracked equipment smartphone measurement performance metrics time and motion study forest operations
- UIEF Unit:
- Flat Creek West Hatter Creek East Hatter Creek
- Location:
- UIEF; Flat Creek; West Hatter Creek; East Hatter Creek
- Latitude:
- 46.869607
- Longitude:
- -116.733856
- Publisher:
- Public Library of Science
- Department:
- Forest, Rangeland, and Fire Sciences
- Type:
- Text
Source
- Preferred Citation:
- "A Novel Smartphone-Based Activity Recognition Modeling Method for Tracked Equipment in Forest Operations", UIEF Research Exchange, University of Idaho Library Digital Collections, https://www.lib.uidaho.edu/digital/uief/items/uief_0149.html
Rights
- Rights:
- In copyright, educational use permitted.
- Standardized Rights:
- http://rightsstatements.org/vocab/InC-EDU/1.0/