Smart Forest Navigation System Using LoRa and Dynamic Pathfinding
Navigating dense forest environments presents significant challenges due to obstructed GPS signals, dynamic terrain, and limited communication infrastructure. This research proposes a Smart Forest Navigation System that enables real-time, infrastructure-free navigation by integrating LoRa communicat...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11037668/ |
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| Summary: | Navigating dense forest environments presents significant challenges due to obstructed GPS signals, dynamic terrain, and limited communication infrastructure. This research proposes a Smart Forest Navigation System that enables real-time, infrastructure-free navigation by integrating LoRa communication, radar-based obstacle detection, and Dynamic A<inline-formula> <tex-math notation="LaTeX">${}^{\ast }$ </tex-math></inline-formula> (D<inline-formula> <tex-math notation="LaTeX">${}^{\ast } $ </tex-math></inline-formula>) pathfinding. The system leverages Time of Arrival (ToA) measurements from LoRa nodes for long-range localization, enhanced through sensor fusion with Inertial Measurement Unit (IMU) data using an Extended Kalman Filter (EKF) on the user’s smartphone. A radar sensor provides real-time environmental perception, detecting obstacles and updating a dynamically evolving map enriched with satellite, drone, and crowdsourced data via probabilistic modeling. Path optimization is handled by the D<inline-formula> <tex-math notation="LaTeX">${}^{\ast }$ </tex-math></inline-formula> Lite algorithm, which adapts to terrain changes and obstacle updates, using a cost function that accounts for terrain difficulty and energy efficiency. All computations are performed on-device, ensuring low-latency operation without reliance on GPS or external servers. The proposed system offers a cost-effective, energy-efficient solution suitable for forest exploration, wildlife tracking, and search and rescue missions in GPS-denied environments. |
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| ISSN: | 2169-3536 |