Serverless Sensor Data Pipeline Using AWS (IoT → Lambda → DynamoDB → Dashboard)

Problem statement

Traditional IoT systems often require dedicated backend servers, leading to higher costs, poor scalability, and maintenance overhead. There is a need for a highly scalable, cost-efficient, and maintenance-free solution that can ingest, process, store, and visualize IoT data without managing servers.

Abstract

This project builds a serverless architecture using AWS cloud services. IoT devices send sensor data to AWS IoT Core, which triggers AWS Lambda functions for real-time processing. Cleaned data is stored in DynamoDB, while historical analytics can be performed using AWS Athena. A lightweight dashboard (React or AWS Amplify Hosting) visualizes live and past sensor data. This architecture auto-scales with load, has zero server management, and is ideal for large sensor deployments.

Components required

• ESP32 / ESP8266 IoT node
• AWS IoT Core (MQTT Broker)
• AWS Lambda
• AWS DynamoDB
• AWS IAM & API Gateway
• Frontend dashboard (React / Next.js / Amplify)

Block diagram

Working

IoT sensors periodically publish readings to AWS IoT Core using MQTT. An IoT Rule triggers a Lambda function that validates, filters, and transforms the incoming data. The processed data is then inserted into DynamoDB. The dashboard calls an API Gateway endpoint that queries the database and displays time-series graphs and real-time updates. The entire system scales automatically and requires no physical servers.

Applications

• Smart campus monitoring
• Large-scale IoT deployments
• Industry sensor analytics
• Environmental monitoring stations
• Cloud DevOps training projects