Live sensor readings from temperature, pressure, vibration, flow rate, current, and humidity sensors delivered to dashboard displays as they arrive from your IoT data pipeline -- built for the data volumes and device counts that industrial and facility monitoring deployments generate, where thousands of sensors report at sub-minute intervals and the combined event stream requires server-side aggregation before it reaches any dashboard client. MQTT-to-WebSocket bridge for devices that publish on MQTT (the standard protocol for IoT sensors): a bridge service subscribes to your MQTT broker (AWS IoT Core, Mosquitto, HiveMQ), processes incoming sensor payloads, applies per-sensor calibration corrections and engineering unit conversions (raw ADC value to Celsius, raw counts to RPM), and broadcasts normalised readings to WebSocket subscribers. Gauge and meter displays for scalar readings: configurable min/max range, colour zone bands (green/amber/red) aligned to your defined operating limits, and a numeric readout with units -- the display format that gives operators the fastest possible out-of-range identification. Rolling trend charts for sensor history: the last 30 minutes to 24 hours of readings shown as a continuous line chart with the current value annotated, zoom and pan for investigating anomalies in historical context without leaving the live view. Vibration spectrum analysis display for machinery monitoring: FFT frequency domain charts generated server-side from raw accelerometer data, updated at a configurable cycle (typically 10-60 seconds) and displayed alongside time-domain amplitude for identifying bearing defects and imbalance signatures. Alert thresholds configured per sensor with hysteresis to prevent alert flapping: a temperature sensor set to alert above 85°C will not re-alert immediately if the value drops to 84°C and rises again -- the hysteresis band (configurable, typically 2-5% of the threshold value) prevents nuisance alerts from noisy sensors near threshold values.