TEAMER: Field Demonstration of MarineSitu Marine Energy Monitoring Tools (Public)
This submission contains data collected during a four-month field demonstration (July-October 2024) of MarineSitu's Adaptable Monitoring Package (AMP) at the Pacific Northwest National Laboratory (PNNL) Marine and Coastal Research Laboratory (MCRL) in Sequim, WA. The project evaluated the platform's survivability in a tidal channel and the iterative development methodology for real-time AI-driven environmental monitoring.
The dataset includes:
Sample Optical Imagery: High-resolution greyscale images from a modular camera systems capturing confirmed or suspected marine life interactions using automated object detection-activated acquisition.
Machine Learning Artifacts: Object detection model weights (.pt) for three iterations each of optical and acoustic models, validation datasets with manually labeled annotations (.txt), and model-generated detection predictions (.json).
Analysis Software: Python-based tools for model performance validation (Precision, Recall, mAP50, false positive rate analysis) and synchronized multi-instrument data review.
Prerequisites/Assumptions: Use of the included Python scripts requires a Python 3.10+ environment. Users should refer to the provided README.md files within the "Data Viewer" and "Model Validation" directories for installation and usage instructions.
Note: This submission includes a representative sample of optical imagery. A larger dataset of optical and sonar data will be made availalbe on July 1, 2029, in the following repository: https://mhkdr.openei.org/submissions/689
Citation Formats
TY - DATA
AB - This submission contains data collected during a four-month field demonstration (July-October 2024) of MarineSitu's Adaptable Monitoring Package (AMP) at the Pacific Northwest National Laboratory (PNNL) Marine and Coastal Research Laboratory (MCRL) in Sequim, WA. The project evaluated the platform's survivability in a tidal channel and the iterative development methodology for real-time AI-driven environmental monitoring.
The dataset includes:
Sample Optical Imagery: High-resolution greyscale images from a modular camera systems capturing confirmed or suspected marine life interactions using automated object detection-activated acquisition.
Machine Learning Artifacts: Object detection model weights (.pt) for three iterations each of optical and acoustic models, validation datasets with manually labeled annotations (.txt), and model-generated detection predictions (.json).
Analysis Software: Python-based tools for model performance validation (Precision, Recall, mAP50, false positive rate analysis) and synchronized multi-instrument data review.
Prerequisites/Assumptions: Use of the included Python scripts requires a Python 3.10+ environment. Users should refer to the provided README.md files within the "Data Viewer" and "Model Validation" directories for installation and usage instructions.
Note: This submission includes a representative sample of optical imagery. A larger dataset of optical and sonar data will be made availalbe on July 1, 2029, in the following repository: https://mhkdr.openei.org/submissions/689
AU - Joslin, James
A2 - Scott, Mitchell
A3 - Runyan, Alexa
A4 - Nowak, Theodore
A5 - Sather, Nichole
DB - Marine and Hydrokinetic Data Repository
DP - Open EI | National Laboratory of the Rockies
DO -
KW - MHK
KW - Marine
KW - Hydrokinetic
KW - energy
KW - power
KW - AMP
KW - Environmental Monitoring
KW - Machine Learning
KW - Object Detection
KW - Sequim Bay
KW - TEAMER
KW - miniAMP
KW - Adaptable Monitoring Package
KW - optical imagery
KW - acoustic imagery
KW - sonar
KW - code
KW - Python
KW - data
KW - raw data
KW - ML
KW - optical
KW - acoustic
KW - imagery
LA - English
DA - 2026/06/15
PY - 2026
PB - MarineSitu
T1 - TEAMER: Field Demonstration of MarineSitu Marine Energy Monitoring Tools (Public)
UR - https://mhkdr.openei.org/submissions/709
ER -
Joslin, James, et al. TEAMER: Field Demonstration of MarineSitu Marine Energy Monitoring Tools (Public). MarineSitu, 15 June, 2026, Marine and Hydrokinetic Data Repository. https://mhkdr.openei.org/submissions/709.
Joslin, J., Scott, M., Runyan, A., Nowak, T., & Sather, N. (2026). TEAMER: Field Demonstration of MarineSitu Marine Energy Monitoring Tools (Public). [Data set]. Marine and Hydrokinetic Data Repository. MarineSitu. https://mhkdr.openei.org/submissions/709
Joslin, James, Mitchell Scott, Alexa Runyan, Theodore Nowak, and Nichole Sather. TEAMER: Field Demonstration of MarineSitu Marine Energy Monitoring Tools (Public). MarineSitu, June, 15, 2026. Distributed by Marine and Hydrokinetic Data Repository. https://mhkdr.openei.org/submissions/709
@misc{MHKDR_Dataset_709,
title = {TEAMER: Field Demonstration of MarineSitu Marine Energy Monitoring Tools (Public)},
author = {Joslin, James and Scott, Mitchell and Runyan, Alexa and Nowak, Theodore and Sather, Nichole},
abstractNote = {This submission contains data collected during a four-month field demonstration (July-October 2024) of MarineSitu's Adaptable Monitoring Package (AMP) at the Pacific Northwest National Laboratory (PNNL) Marine and Coastal Research Laboratory (MCRL) in Sequim, WA. The project evaluated the platform's survivability in a tidal channel and the iterative development methodology for real-time AI-driven environmental monitoring.
The dataset includes:
Sample Optical Imagery: High-resolution greyscale images from a modular camera systems capturing confirmed or suspected marine life interactions using automated object detection-activated acquisition.
Machine Learning Artifacts: Object detection model weights (.pt) for three iterations each of optical and acoustic models, validation datasets with manually labeled annotations (.txt), and model-generated detection predictions (.json).
Analysis Software: Python-based tools for model performance validation (Precision, Recall, mAP50, false positive rate analysis) and synchronized multi-instrument data review.
Prerequisites/Assumptions: Use of the included Python scripts requires a Python 3.10+ environment. Users should refer to the provided README.md files within the "Data Viewer" and "Model Validation" directories for installation and usage instructions.
Note: This submission includes a representative sample of optical imagery. A larger dataset of optical and sonar data will be made availalbe on July 1, 2029, in the following repository: https://mhkdr.openei.org/submissions/689
},
url = {https://mhkdr.openei.org/submissions/709},
year = {2026},
howpublished = {Marine and Hydrokinetic Data Repository, MarineSitu, https://mhkdr.openei.org/submissions/709},
note = {Accessed: 2026-07-13}
}
Details
Data from Jun 15, 2026
Last updated Jun 15, 2026
Submission in progress
Organization
MarineSitu
Contact
Paul Murphy
330.606.2630
Authors
Keywords
MHK, Marine, Hydrokinetic, energy, power, AMP, Environmental Monitoring, Machine Learning, Object Detection, Sequim Bay, TEAMER, miniAMP, Adaptable Monitoring Package, optical imagery, acoustic imagery, sonar, code, Python, data, raw data, ML, optical, acoustic, imageryDOE Project Details
Project Name Testing Expertise and Access for Marine Energy Research
Project Lead Lauren Ruedy
Project Number EE0008895

