LoRa rescue: Emergency distress signal geolocation system
In a calamity, cellular networks, internet services, and electricity may prove to be unreliable. And yet, emergency responders will need a way to contact and locate people-in-need as soon as possible. As such, this thesis proposes an emergency trilateration system that uses LoRa. A wireless communic...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2021
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etdb_ece/6 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1006&context=etdb_ece |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Language: | English |
| Summary: | In a calamity, cellular networks, internet services, and electricity may prove to be unreliable. And yet, emergency responders will need a way to contact and locate people-in-need as soon as possible. As such, this thesis proposes an emergency trilateration system that uses LoRa. A wireless communications technology characterized by its longer range and lower power consumption compared to other technologies such as Bluetooth and WiFi. This thesis developed a LoRa trilateration algorithm that improves upon the standard trilateration algorithm by using the closest points. This improved trilateration algorithm obtained a 73.0185% improvement in accuracy compared to the standard algorithm, across 25 datasets. Furthermore, the thesis utilized automated elbow methods to acquire the optimal parameters required by the DBSCAN and K-means clustering algorithms. For DBSCAN, the study automated the acquisition of the Epsilon and MinPts parameters, and for K-means, the SoSD parameter. After applying these clustering algorithms to filter the data, the results provided an average error of 39.6506 meters from the actual position. |
|---|