The objective of this project is to explore and implement an automatic and corrective positioning system for LoRa stations using geolocation through multiple technologies: WiFi, cellular, BLE (Bluetooth Low Energy), and LoRa itself. This approach will address the network’s adaptability and accuracy needs while considering environmental conditions and topological constraints.
This project takes place in a context where optimizing LPWAN (Low Power Wide Area Network) networks is a key challenge for IoT (Internet of Things) applications. By dynamically improving the positioning of LoRa stations, it is possible to enhance network efficiency, optimize energy consumption, and ensure more reliable coverage for various use cases, particularly in urban and rural environments.
## Project's Needs
## Project's Needs
The goal of our project is to enable a device equipped with a LoRa communication module to determine its exact position at any time. To achieve this, we need to enhance ChirpStack by adding a microservice that will handle device localization requests. Specifically, when a device requests its position, ChirpStack will:
1. Query its own database to retrieve available information on this device
2. Consult the BeaconDB database (which we identified for inform us about network positions) for additional reference points.
3. Perform data consistency checks between these sources to refine and what the device informs to refine the position.
Additionally, we need to develop a software solution for the LoRa-equipped device. This software will allow the device to regularly send packets like: "Here is the network around me", containing information on the signals it detects. These data points will then be processed to improve location accuracy.
## Results
## Results
## Constraints
## Constraints
## Necessary ressources
## Necessary ressources
## Delay
To successfully carry out this project, several resources are required:
- 1 Multitech Linux MTCDT LoRa station
- 1 Kerlink iFemto Linux MTCDT LoRa station
- 1 ecoSignal LoRa station (ESP32)
- 2 RPI LoRa stations + Corecell (under Linux)
- 1 LoRa RPI + Picocell station (under Linux)
## Steps to follow
The following steps outline the process for completing the project:
1. Understand ChirpStack: Familiarize with the ChirpStack ecosystem and its functionalities.
2. Microservice/Device Communication: Establish communication between microservices and devices.
3. Develop the Probe: Implement functionality to scan surrounding WiFi networks.
3. Query ChirpStack’s LoRa Position Database: Retrieve positioning data from ChirpStack’s database.
4. Process Positioning Data: Analyze and process the collected positioning data.
5. Store Metadata: Save metadata for future analysis and optimization.
