119 lines
3.7 KiB
Markdown
119 lines
3.7 KiB
Markdown
# Gateway — BLE to MQTT
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This component runs on a Raspberry Pi 4 and acts as the communication bridge
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between the Nordic Thingy:52 sensor nodes and the rest of the system.
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It reads environmental data from the nodes over BLE and publishes it to a
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local MQTT broker (Mosquitto) in a structured JSON format.
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## Role in the architecture
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```
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Thingy:52 nodes --> (BLE) --> Raspberry Pi --> (MQTT) --> Database / ML / Notifications
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```
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## Dependencies
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Install the required Python libraries:
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```bash
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pip3 install bleak paho-mqtt --break-system-packages
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```
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Install and start the Mosquitto MQTT broker:
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```bash
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sudo apt install -y mosquitto mosquitto-clients
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sudo systemctl enable mosquitto
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sudo systemctl start mosquitto
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```
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## Usage
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```bash
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python3 gateway.py
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```
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At startup, the script asks for the room ID (e.g. C1, A2, B5).
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It then automatically discovers all Thingy:52 nodes in range by filtering
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BLE advertising packets on the Nordic Configuration service UUID (ef680100).
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Each detected node is assigned a name based on the room ID and a counter
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(e.g. C1_thingy1, C1_thingy2).
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To run the gateway in the background and keep it running after closing SSH:
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```bash
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nohup python3 gateway.py > log.txt 2>&1 &
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```
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## MQTT topic structure
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```
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classroom/{room_id}/{node_id}
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```
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Example: `classroom/C1/C1_thingy1`
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## Message format
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Each message is published as a JSON object with the following structure:
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```json
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{
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"timestamp": "2026-03-26T13:24:05.176072+00:00",
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"room_id": "C1",
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"node_id": "C1_thingy1",
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"sensors": {
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"co2_ppm": 400,
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"temperature_c": 25.37,
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"humidity_pct": 44
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}
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}
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```
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| Field | Type | Description |
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|---|---|---|
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| timestamp | string (ISO 8601 UTC) | Time of measurement, added by the gateway |
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| room_id | string | Identifier of the monitored room |
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| node_id | string | Identifier of the Thingy:52 node |
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| co2_ppm | integer | eCO2 concentration in parts per million |
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| temperature_c | float | Indoor air temperature in degrees Celsius |
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| humidity_pct | integer | Relative humidity in percent |
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## Output files
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For each session, two local files are created in the gateway directory:
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- `data_{room_id}.csv` — comma-separated file for local analysis
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- `data_{room_id}.json` — JSON file following the database team format
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## Publishing interval
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The default publishing interval is 5 minutes (300 seconds).
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This can be adjusted by modifying the `INTERVAL` variable in `gateway.py`.
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## Utility scripts
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- `scan.py` — scans for nearby BLE devices and prints their name and MAC address
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- `check_uuid.py` — connects to Thingy:52 nodes and prints their advertised service UUIDs
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## Notes on the CO2 sensor
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The Thingy:52 uses a CCS811 sensor which measures eCO2 (equivalent CO2),
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estimated from volatile organic compound (VOC) levels rather than directly
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measuring CO2 concentration. Values should be interpreted as indicative trends
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rather than precise measurements, particularly during the first 24 to 48 hours
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of operation while the sensor calibrates.
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## Overnight test results
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An overnight test was conducted with 2 Thingy:52 nodes placed in two separate
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rooms (windows closed, 7h session, 5 minute interval).
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- Room 1: 4 occupants (2 adults, 2 children)
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- Room 2: unoccupied
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CO2 rose progressively from 400 ppm to a peak of 1071 ppm in the occupied room,
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consistent with human respiration in a confined space. The unoccupied room
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remained stable between 400 and 465 ppm, confirming that variations in Room 1
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are directly linked to human presence.
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Note: the CCS811 sensor measures eCO2 estimated from VOC levels, not direct CO2.
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Occasional spikes (e.g. 877 ppm at 02:45, 1071 ppm at 03:05) may be caused by
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factors such as perspiration or movement near the sensor and should be interpreted
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with caution.
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