Air Quality Monitoring with Speech Announcements

Abstract

Abstract: In this project, we design and develop an advanced weather station system using an ESP32 microcontroller, temperature sensor, humidity sensor, and air quality sensor. The primary objectives of this project are data collection, visualization, and auditory feedback. The ESP32 microcontroller acts as the central processing unit and connects to the internet via Wi-Fi to transmit real-time sensor data to an IoT platform. This platform stores and manages the data, making it accessible from anywhere with an internet connection. Users can monitor temperature, humidity, and air quality remotely through a userfriendly web interface Additionally, the project incorporates a display screen that provides local, real-time weather information for on-site users. This display enhances the accessibility of weather data, even in the absence of internet connectivity. To ensure inclusivity and accessibility, the system employs a speech-to-text algorithm implemented in Python. At predefined intervals, the system announces the sensor data via a speaker using text-to-speech (TTS) technology. This feature aids visually impaired individuals in accessing weather information in an auditory format. The combination of sensor integration, IoT connectivity, data visualization, and text-to-speech capabilities creates a comprehensive and user-friendly weather monitoring system suitable for both personal and public use. This project demonstrates the potential of IoT technologies to improve data accessibility and inclusivity in weather monitoring applications. IQ test continue to be one of most reliable tools to measure intelligence skills of the human. The Intelligence Quotient (IQ) tests and the corresponding psychometric explanations dominate both the scientific and popular views about human intelligence. Though the IQ tests have been in currency for long, there exists a gap in what they are believed to measure and what they do. While the IQ tests index the quality of cognitive functioning in selected domains of mental repertoire, the applied settings often inflate their predictive value leading to an interpretive gap.