AI-Integrated Smart Environment Monitoring System with Real-Time Dart Dashboard: A Unified IOT Framework Using ESP32, Multisensory Array, and Intelligent Alert Mechanism
Bhagyashri Wakde1, Amith C Patil2, B Nithya Shree3, Nihar T N4, Varun P S5
1 Professor, Dept. of Computer Science Engineering, Rajiv Gandhi Institute of Technology, Bengaluru, India
2 Dept. of Computer Science Engineering, Rajiv Gandhi Institute of Technology, Bengaluru, India
3 Dept. Of Computer Science Engineering, Rajiv Gandhi Institute of Technology, Bengaluru, India
4 Dept. Of Computer Science Engineering, Rajiv Gandhi Institute of Technology, Bengaluru, India
5 Dept. Of Computer Science Engineering, Rajiv Gandhi Institute of Technology, Bengaluru, India
Abstract—The rapid convergence of the Internet of Things (IoT), low-cost embedded microcontrollers, and cloud analytics has fundamentally transformed real-time environmental monitoring and smart security systems. This paper presents a comprehensive survey and integrated framework synthesizing six peer-reviewed research works spanning IoT-based indoor environment quality (IEQ) monitoring, ESP32-based weather stations, air quality monitoring using Raspberry Pi, and multi-factor authentication mechanisms for banking security. The surveyed systems collectively demonstrate the effectiveness of low-cost sensor nodes—specifically ESP32-WROOM, Raspberry Pi, and DHT22/MQ-series/BH1750 sensor suites—in achieving high-accuracy, real-time measurements with R2 >0.98 and RMSE <0.5 across environmental parameters including temperature, humidity, particulate matter (PM2.5), illuminance, and air quality index (AQI). Communication protocols, including MQTT, Wi-Fi (IEEE 802.11 b/g/n), and cloud platforms such as ThingSpeak, Blynk, Firebase, and Google Sheets, are critically evaluated. Additionally, the security domain is addressed through a novel Morse code eye-blink biometric authentication mechanism integrated with an enhanced Vigenère cipher and the bank management system, achieving a 98% biometric success rate and 0.01% false acceptance rate. The proposed unified framework bridges the gap between environmental sensing accuracy, communication efficiency, energy optimization, and secure data access, positioning the integrating architecture as a scalable, cost-effective solution for smart buildings, precision agriculture, and industrial IoT deployments.
Index Terms—Internet of Things (IoT), ESP32-WROOM, Environmental Monitoring, Indoor Air Quality (IAQ), MQTT Protocol, ThingSpeak, Biometric Authentication, Morse Code, Vigenère Cipher, DHT22, PM2.5, Smart Security, Cloud Analytics, Edge Computing
