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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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11037668/ |
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| author | Isha Nevatia Vraj Chaudhary M. Thurai Pandian |
| author_facet | Isha Nevatia Vraj Chaudhary M. Thurai Pandian |
| author_sort | Isha Nevatia |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9712b6d1b4b34f39b1df7451d301cc7f |
| institution | Matheson Library |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-9712b6d1b4b34f39b1df7451d301cc7f2025-07-11T23:01:46ZengIEEEIEEE Access2169-35362025-01-011311442811444310.1109/ACCESS.2025.358046311037668Smart Forest Navigation System Using LoRa and Dynamic PathfindingIsha Nevatia0https://orcid.org/0009-0000-9706-4585Vraj Chaudhary1https://orcid.org/0009-0008-3521-4523M. Thurai Pandian2https://orcid.org/0000-0002-9901-6197School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, IndiaSchool of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, IndiaSchool of Computer Science and Engineering, SRM Institute of Science and Technology, Tiruchirappalli, Tamil Nadu, IndiaNavigating 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.https://ieeexplore.ieee.org/document/11037668/D* Liteextended Kalman filter (EKF)inertial measurement unit (IMU)LoRamultilaterationnavigation |
| spellingShingle | Isha Nevatia Vraj Chaudhary M. Thurai Pandian Smart Forest Navigation System Using LoRa and Dynamic Pathfinding IEEE Access D* Lite extended Kalman filter (EKF) inertial measurement unit (IMU) LoRa multilateration navigation |
| title | Smart Forest Navigation System Using LoRa and Dynamic Pathfinding |
| title_full | Smart Forest Navigation System Using LoRa and Dynamic Pathfinding |
| title_fullStr | Smart Forest Navigation System Using LoRa and Dynamic Pathfinding |
| title_full_unstemmed | Smart Forest Navigation System Using LoRa and Dynamic Pathfinding |
| title_short | Smart Forest Navigation System Using LoRa and Dynamic Pathfinding |
| title_sort | smart forest navigation system using lora and dynamic pathfinding |
| topic | D* Lite extended Kalman filter (EKF) inertial measurement unit (IMU) LoRa multilateration navigation |
| url | https://ieeexplore.ieee.org/document/11037668/ |
| work_keys_str_mv | AT ishanevatia smartforestnavigationsystemusingloraanddynamicpathfinding AT vrajchaudhary smartforestnavigationsystemusingloraanddynamicpathfinding AT mthuraipandian smartforestnavigationsystemusingloraanddynamicpathfinding |