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ChirpStack + Grafana Data Visualization

ChirpStack + Grafana Data Visualization​

Background​

ItemDetail
Products UsedLHT65N × 10, DLOS8 × 1
Network ServerChirpStack v4 (self-hosted)
ApplicationGrafana + PostgreSQL
Customer ScenarioCustomer wants to monitor temperature & humidity in 10 office rooms with a Grafana dashboard, all on a private local network (no cloud dependency)

Solution Architecture​

LHT65N (×10)  →  DLOS8 Gateway  →  ChirpStack v4  →  PostgreSQL  →  Grafana
                     (local LAN)      (Docker)          (TimescaleDB)

All components run on a single Ubuntu server within the customer's LAN.

Step-by-Step​

1. DLOS8 Gateway Configuration​

  1. Access DLOS8 web UI at 10.130.1.1
  2. Set LoRaWAN → Service Provider to Custom / Private LoRaWAN
  3. Configure ChirpStack Gateway Bridge address: 10.130.1.100:1700

2. ChirpStack v4 Setup (Docker)​

git clone https://github.com/chirpstack/chirpstack-docker.git
cd chirpstack-docker
docker compose up -d
  • Add Gateway in ChirpStack UI
  • Create Device Profile with Dragino LHT65N codec
  • Register 10 devices

3. Data Pipeline to PostgreSQL​

Use ChirpStack Integration → PostgreSQL to automatically store decoded data.

Alternatively, use MQTT subscriber to write to TimescaleDB:

import paho.mqtt.client as mqtt
import psycopg2, json

def on_message(client, userdata, msg):
    data = json.loads(msg.payload)
    obj = data.get("object", {})
    # Insert into TimescaleDB
    cur.execute(
        "INSERT INTO sensor_data (device, temperature, humidity, ts) VALUES (%s,%s,%s,NOW())",
        (data["deviceInfo"]["deviceName"], obj.get("TempC_SHT"), obj.get("Hum_SHT"))
    )
    conn.commit()

4. Grafana Dashboard​

  • Add PostgreSQL/TimescaleDB as data source
  • Create panels: temperature heatmap, humidity trend, per-room cards
  • Set alert rules for temperature > 28°C or humidity > 70%

Result​

  • Fully private deployment, zero cloud dependency
  • 10 rooms monitored with 10-minute intervals
  • Grafana dashboard accessible to facility management team via LAN

Notes​

  • TimescaleDB is recommended over plain PostgreSQL for time-series queries
  • ChirpStack v4 Docker deployment requires at least 2GB RAM