Abstract
A weather monitoring system is a robust and cost-effective solution designed to monitor and record real-time environmental parameters using Arduino as the central controller. This system integrates various sensors, such as a DHT11 for temperature and humidity, an LDR for light intensity, and a soil moisture sensor, to gather precise data about environmental conditions. The data is processed by the Arduino and displayed locally on an LCD screen, ensuring ease of access for users. The system provides a versatile platform for monitoring key weather parameters in applications such as agriculture, greenhouses, and indoor climate control. Threshold-based automation is implemented to activate actuators like water pumps and fans, providing intelligent responses to environmental changes. For example, the water pump is triggered when soil moisture falls below a certain level, and the fan is activated when the temperature exceeds a predefined threshold. Manual override is also supported through push-button controls, allowing users to operate the system as needed. Designed as a standalone device, the system runs entirely on Arduino and does not rely on internet connectivity, making it ideal for remote or resource-constrained locations. Its modular design allows for easy integration of additional sensors, such as rain or wind-speed sensors, for expanded functionality. By providing accurate, real-time weather data and automating responses to environmental changes, this system reduces manual effort, optimizes resource usage, and enhances productivity. Its simplicity, affordability, and reliability make it a valuable tool for individuals and organizations in agriculture, horticulture, and environmental research. This project demonstrates the potential of Arduino-based systems to solve real-world challenges in a sustainable and scalable..[7] Keywords: IoT (Internet of Things), Environmental Monitoring, Smart Cities, Real-time Data, Sensors, Air Quality Monitoring, Water Quality Monitoring, Climate Data, Data Analytics, Cloud Computing, Wireless Sensor Networks (WSNs), Pollution Detection.
Published Version
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