Environmental Sensor Network Project Overview This cutting-edge Arduino project leverages a network of state-of-the-art sensors to accurately and continuously monitor a wide range of environmental data, including ultraviolet (UV) radiation, temperature, humidity, and air quality. Designed for exceptional versatility, the system is capable of transmitting collected data via radio frequency (RF) over distances up to 10 km or alternatively displaying a QR code on an integrated screen. Observers can scan this QR code to instantly access environmental data and contribute with their personal perceptions of the climate, thus enriching the dataset with valuable subjective information. All this data is meticulously stored in a database, ready for practical applications or as study material in machine learning (ML) projects.
Features UV Sensor Capable of detecting the intensity of ultraviolet radiation in the environment with unprecedented accuracy. Essential for assessing sun exposure and preventing skin and eye damage due to overexposure to UV rays. Temperature Sensor Provides accurate and real-time temperature measurements. Crucial for understanding thermal trends and adequately preparing for environmental conditions. Humidity Sensor Offers critical data on the water vapor content in the air. Fundamental for assessing environmental comfort and efficiently managing HVAC systems. Air Quality Sensor Measures various pollutants and particles in the air, providing a comprehensive view of ambient air quality. Indispensable for identifying areas with polluted air and taking steps to improve public health. Data Transmission and QR Code RF capability extends the system's reach and applicability significantly, while the innovative QR code feature allows for direct and personalized interaction with end users. Users can easily access environmental data and share their personal perceptions, adding a unique human dimension to the dataset. Data Storage and Applications All collected data, both objective and subjective, is stored in a secure and structured database, ready for analysis or use in a variety of practical applications. From smart building automation to machine learning research, our system opens new doors to innovation and the study of our surrounding environment. Getting Started (Here you would include instructions on how to set up and use the system, including any necessary software or hardware configurations.)
Contributing We welcome contributions from the community. If you have suggestions for improvements or new features, please feel free to open an issue or submit a pull request.
License (Include license information here, typically something like: "This project is licensed under the MIT License - see the LICENSE.md file for details")