Arduino Sensor Project Explorations

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Spent the day working with Arduino and various environmental sensors, building a home air quality monitoring system that’s turned into a fascinating learning experience.

Started with basic temperature and humidity sensing using a DHT22. The simplicity of reading sensor data and displaying it on an LCD screen feels like magic when you’re used to high-level software development.

Added a particulate matter sensor to measure PM2.5 and PM10 levels. The readings correlate surprisingly well with official air quality reports, giving confidence in the DIY approach to environmental monitoring.

The real challenge came when trying to log data over time. Arduino’s limited memory means you need external storage or network connectivity. I opted for WiFi connectivity to push data to a cloud service.

Power management becomes critical for battery-operated sensors. Sleep modes, efficient code, and careful component selection can extend battery life from days to months. It’s a different mindset from desktop programming.

The sensor ecosystem is incredible. Temperature, humidity, air pressure, light levels, motion detection, sound levels – you can measure almost anything with readily available modules. The hard part is often choosing which sensors you actually need.

Calibration is more complex than expected. Cheap sensors often require offset corrections and environmental compensation. Professional-grade accuracy requires careful calibration procedures and sometimes multiple sensor readings.

Been experimenting with different communication protocols too. I2C for short distances, LoRa for long-range low-power communication, and WiFi for high-bandwidth applications. Each has its place depending on project requirements.

The visualization aspect is crucial for making sensor data useful. Raw numbers mean little without context, trends, and alerts. Building web dashboards that make environmental data actionable is as important as the sensing itself.

Error handling becomes critical when devices run unattended for long periods. Network failures, sensor errors, and power interruptions need graceful handling to maintain data integrity.

Planning to expand this into a distributed sensing network around the neighborhood. The potential for citizen science applications is exciting.