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Published on: November 25, 2016
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Positioning Methods and the Use of Location and Activity Data in Forests.
Robert F Keefe1, Ann M Wempe1, Ryer M Becker1
1Department of Forest, Rangeland and Fire Sciences, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844, USA.
Forests
|May 14, 2023
Summary
This study reviews positioning systems for natural resource management, focusing on accuracy in remote areas. It proposes a hierarchical data model using wearable tech and IoT for better resource tracking and big data analytics.
Area of Science:
- Forestry and Natural Resource Management
- Geospatial Science and Technology
- Data Science and Analytics
Background:
- Effective management of natural resources, particularly in forestry and fire management, requires reliable positioning systems for moving assets.
- Traditional communication infrastructure is often unavailable in remote, forested environments, posing challenges for real-time data collection and sharing.
- Emerging data science themes like IoT, wearable technology, and big data offer potential solutions for enhancing natural resource management.
Purpose of the Study:
- To review and synthesize literature on positioning systems for forest and fire management, emphasizing accuracy and range in challenging environments.
- To explore the relevance of emerging data science concepts (LBS, geofences, IoT, big data) for advancing natural resource management.
- To propose a hierarchical data collection and sharing model tailored for natural resource applications.
Main Methods:
- Conducted systematic literature reviews on positioning systems and data science themes relevant to natural resource management.
- Integrated findings from forestry, fire management, wildlife, and fisheries literature, alongside concepts from video object detection and inventory tracking.
- Developed a hierarchical data model based on reviewed technologies and concepts, considering range, bandwidth, and data processing tradeoffs.
Main Results:
- Identified key positioning technologies and data science concepts applicable to natural resource management in remote areas.
- Presented a hierarchical model where short-range wireless technologies (Bluetooth, BLE, ANT) collect data, with smartphones/tablets acting as hubs.
- Demonstrated how data is processed incrementally and fused at higher levels, balancing range and bandwidth for effective resource management and public safety.
Conclusions:
- A hierarchical data collection and sharing model, integrating wearable technology and IoT, can significantly improve data management in natural resource applications.
- The proposed model addresses challenges of data volume, spatial-temporal complexity, and connectivity limitations in remote environments.
- Future research should focus on advancing big data analytics for natural resources to fully leverage these technological advancements.
Keywords:
Global Navigation Satellite SystemGlobal Positioning SystemInternet of Thingsactivity recognitionbig datafisheriesforestrygeofencelocation-based servicesmesh networkpassive integrated transponderradio frequency identificationradio telemetryultra-widebandwearable technologywildland firewildlife
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