Environmental monitoring has become increasingly critical across industrial, agricultural, and residential domains, demanding systems that are both cost-effective and reliably connected to cloud infrastructure. This paper presents the design and implementation of an IoT-based environmental monitoring system utilizing the ESP8266 NodeMCU microcontroller in conjunction with a DHT11 temperature and humidity sensor and an LM393 ambient light sensor module. The system continuously acquires real-time environmental parameters and serves live data through a locally hosted HTTP web server, enabling visualization via a custom- designed responsive web dashboard accessible on any networked device. Cloud integration is achieved through AWS API Gateway and AWS Lambda, where sensor readings are transmitted every ten seconds and persistently stored in Amazon S3 as both daily CSV files and individual JSON records with accurate UTC timestamps. Automated threshold-based email alerts are delivered through Amazon SNS when ambient temperature exceeds user-defined limits, with a firmware-enforced cooldown mechanism preventing notification redundancy. A dedicated cloud viewer application enables historical data retrieval, statistical analysis, and Excel-based reporting directly from the browser. The proposed system demonstrates that sophisticated environmental monitoring with permanent cloud archiving and intelligent alerting can be realized at minimal cost using commercially available embedded hardware and serverless cloud services, making it particularly suitable for smart home, greenhouse, and laboratory monitoring applications. environmental parameters and serves live data through a locally hosted HTTP web server, enabling visualization via a custom- designed responsive web dashboard accessible on any networked device. Cloud integration is achieved through AWS API Gateway and AWS Lambda, where sensor readings are transmitted every ten seconds and persistently stored in Amazon S3 as both daily CSV files and individual JSON records with accurate UTC timestamps. Automated threshold-based email alerts are delivered through Amazon SNS when ambient temperature exceeds user-defined limits, with a firmware-enforced cooldown mechanism preventing notification redundancy. A dedicated cloud viewer application enables historical data retrieval, statistical analysis, and Excel-based reporting directly from the browser. The proposed system demonstrates that sophisticated environmental monitoring with permanent cloud archiving and intelligent alerting can be realized at minimal cost using commercially available embedded hardware and serverless cloud services, making it particularly suitable for smart home, greenhouse, and laboratory monitoring applications.

This paper has presented a complete WSN-based environmental monitoring system integrating the ESP8266 NodeMCU with DHT11 and LM393 sensors and a serverless AWS cloud backend composed of API Gateway, Lambda, S3, and SNS. The system achieves real-time local visualization, permanent multi-format cloud data archival, and automated email alerting within a clean three-layer architecture at near- zero operating cost within AWS free tier limits. Experimental evaluation over a 12-hour continuous test period confirmed system stability, with end-to-end latency averaging 1.34 seconds and the dashboard performing consistently across all tested browser and device combinations. The results demonstrate that production-quality WSN monitoring with comprehensive data management and intelligent alerting is achievable using commercially available embedded hardware and managed cloud services without custom server infrastructure or significant capital investment. Future work will extend the system with additional sensor modalities including CO2 concentration and barometric pressure, integrate AWS IoT Core for proper multi-device fleet management, and explore Amazon SageMaker-based anomaly detection trained on historical S3 data to replace fixed-threshold alerting with adaptive, context-aware monitoring.

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