Industrial IoT Gateway

Edge computing gateway for real-time industrial sensor data processing and analytics.

6 months

Manufacturing Company

ESP32FreeRTOSMQTTNode.jsInfluxDB

Key Metrics

500+

Sensors

<100ms

Latency

99.9%

Uptime

10,000

Data Points/sec

Overview

A comprehensive IoT solution designed to bring predictive maintenance capabilities to a legacy manufacturing facility, handling hundreds of sensors with real-time processing and cloud analytics.

The Challenge

A manufacturing plant required real-time monitoring of 500+ sensors with sub-second latency, local data processing for anomaly detection, and reliable cloud synchronization.

Our Solution

Built a custom gateway using ESP32 clusters running FreeRTOS, implementing edge ML for predictive maintenance. Designed a robust MQTT-based architecture with local InfluxDB for data buffering.

The Result

Reduced downtime by 35% through predictive maintenance alerts. Processed 10,000 data points per second with 99.9% uptime over 18 months of operation.

Deep Dive

Edge Architecture

The gateway utilizes a cluster of ESP32 microcontrollers running FreeRTOS, with each node handling specific sensor groups. Inter-node communication uses ESP-NOW for low-latency data aggregation, while MQTT handles cloud connectivity.

Data Pipeline

Sensor data flows through a multi-stage pipeline: acquisition, local filtering, anomaly detection, and cloud sync. Local InfluxDB provides data buffering during network outages, ensuring no data loss.

ML at the Edge

We deployed TensorFlow Lite models on the gateway for real-time anomaly detection. Models were trained on historical data and optimized for the ESP32's limited resources using quantization.