Implementing IoT Device Diagnostics via Mobile App
Device diagnostics answers: "what's happening with hardware right now" without physical access. CPU temperature, CPU/RAM load, network interface state, uptime, firmware version, latest system log errors.
What to Collect and How
On device (Linux, OpenWRT, ESP-IDF), collect metrics and expose via MQTT JSON or REST:
{
"device_id": "gw-warehouse-03",
"timestamp": 1711449600,
"cpu_load": 12.5,
"ram_used_mb": 87,
"ram_total_mb": 512,
"cpu_temp_c": 52.3,
"uptime_sec": 864000,
"firmware": "2.4.1-stable",
"wifi_rssi": -67,
"mqtt_reconnects": 2,
"last_error": "2024-03-25T08:12:01Z: sensor read timeout on /dev/ttyUSB0"
}
On mobile client—diagnostics dashboard with gauge indicators for CPU/RAM, historical CPU temperature graph (overheating in poorly ventilated enclosure—frequent instability cause), and list of recent errors.
Interpreting RSSI
WiFi RSSI in dBm—not an abstract number. Display with clear thresholds:
String rssiDescription(int dbm) {
if (dbm >= -50) return 'Excellent signal';
if (dbm >= -60) return 'Good signal';
if (dbm >= -70) return 'Satisfactory';
if (dbm >= -80) return 'Weak — packet loss possible';
return 'Critical weak';
}
RSSI -80 dBm and below—reliable cause of periodic MQTT message loss and apparent device "hangs".
Developing IoT device diagnostics screen with system metrics, error history, and network state: 1–2 weeks. Cost individually quoted.