Title:

Lightning Weather Station

The Lightning Weather Station is an automated photography system designed to capture, store, and wirelessly transmit lightning strike images for atmospheric research at UNH. Traditional lightning photography requires manual camera operation and physical data retrieval, limiting researchers' ability to collect comprehensive datasets from remote locations. Our system addresses these challenges by automating the complete workflow from lightning detection through photo transfer to researcher access.​ The system integrates a Canon Rebel T7 camera with a Raspberry Pi running custom Python automation scripts. When lightning is detected, photos are automatically captured and transferred to the Pi within 60 seconds. A duplicate detection algorithm using MD5 hashing and time-based blocking prevents redundant storage during multi-strike events, while SHA256 checksums verify transfer integrity. Photos are renamed to a consistent Camera_Date_Time.jpg convention and made accessible through a Flask web application running on the Pi.​ To support deployment in remote locations without internet connectivity, the Raspberry Pi hosts its own wireless network, enabling researchers to connect directly and access photos via the web interface. This offline-first architecture ensures data persistence regardless of network conditions, while automatic service startup on boot enables long-term field deployment without manual intervention.​ Testing demonstrated successful end-to-end automation with reliable photo transfer, effective duplicate prevention, and remote accessibility. The system eliminates the need for physical camera access, enabling researchers to collect lightning photography data continuously from remote weather station locations while accessing results wirelessly from their lab or office.

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