Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing

Area of Science:

• Environmental Science
• Sensor Technology
• Data Analytics

Background:

• Traditional weather monitoring systems are often inaccessible to local communities due to high costs and complexity.
• There is a need for cost-effective and user-friendly environmental monitoring solutions for small-scale users.
• Limited resources often hinder community-based environmental data collection and analysis.

Purpose of the Study:

• To introduce a low-cost, easy-to-use local weather station for accessible environmental monitoring.
• To enable efficient in-site measurements of key environmental parameters.
• To provide accurate remote monitoring and short-term weather forecasting capabilities.

Main Methods:

• Development of a weather station utilizing low-cost sensors for measuring temperature, humidity, atmospheric pressure, CO2, and particulate matter (PM1, PM2.5, PM10).
• Implementation of the Autoregressive Integrated Moving Average (ARIMA) model for short-term weather forecasting.
• Design of a user-friendly interface for seamless data communication via web-based platforms.

Main Results:

• The weather station accurately monitors environmental variables with a low error margin of 0.67%.
• The system provides reliable short-term forecasts using the ARIMA model.
• The open-source nature of the station enhances data accessibility and sharing.

Conclusions:

• The developed low-cost weather station significantly improves accessibility to environmental monitoring for small-scale users and local communities.
• The system empowers informed decision-making for agriculture, transportation, and air quality management through real-time data and forecasts.
• This work offers a sustainable blueprint for future advancements in accessible environmental technology and community-driven climate action.