ESP32 IOT DEVELOPMENT: A COMPREHENSIVE GUIDE TO AWS CLOUD AND MOBILE INTEGRATION - Mitul DilipBhai Modi, (INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY (IJRCAIT), 2024)
This article presents an innovative framework for developing enterprise-grade Internet of Things (IoT) solutions that leverage the ESP32 microcontroller's advanced capabilities integrated with Amazon Web Services (AWS) cloud infrastructure and cross-platform mobile applications. The architecture addresses critical challenges in modern IoT deployments through a multi-layered approach to system design. At the hardware level, we exploit the ESP32's dual-core processor architecture, implementing a task distribution system that dedicates one core to wireless communication and sensor management while utilizing the second core for data processing and power management optimization. This approach achieves consistent sub-80 mA power consumption in active mode while maintaining robust wireless connectivity. The cloud infrastructure leverages AWS IoT Core's MQTT broker for device communication, complemented by a serverless backend comprising Lambda functions, DynamoDB for time-series data storage, and API Gateway for mobile client interactions. The implementation incorporates a comprehensive security framework built on certificate-based authentication, secure boot mechanisms, and encrypted communication channels, ensuring end-to-end data protection. On the mobile front, the solution employs React Native for cross-platform development, featuring real-time data visualization, push notifications for critical alerts, and offline capability through local data persistence. Field testing across various deployment scenarios demonstrates the system's resilience, maintaining 99.9% uptime in production environments and supporting scaled deployments of over 1,000 concurrent devices. The framework includes automated over-the-air (OTA) update mechanisms for both firmware and application layers, enabling seamless maintenance and feature deployment. Performance optimization techniques implemented at each layer result in average end-to-end latency under 100 ms for critical operations and data processing throughput exceeding 1,000 messages per second per device cluster. This comprehensive approach reduces traditional IoT solution development time by 60% while ensuring enterprise-grade reliability and scalability, making it particularly suitable for industrial monitoring, smart building management, and environmental sensing applications.