Presenter: Diane M. Jubeili

Faculty Sponsor: Manish Wadhwa

School: Salem State University

Research Area: Computer Science

Session: Poster Session 2, 11:30 AM - 12:15 PM, 165, D12

ABSTRACT

This project presents an automated birdhouse monitoring system designed to provide real-time wildlife identification through the integration of embedded hardware and cloud-based artificial intelligence. Built on a Raspberry Pi platform, the system utilizes a PIR (Passive Infrared) motion sensor to detect the arrival of a bird. Upon triggering, a Pi Camera module captures high-resolution imagery, which is then transmitted to the Google Cloud Vision API.

By leveraging machine learning through this API, the system identifies the specific species or characteristics of the bird. The processed information, along with the captured image, is then delivered to the user via SMS notification. This end-to-end IoT pipeline demonstrates the practical application of sensor fusion, cloud computing, and automated remote communication, offering a sophisticated yet accessible solution for ornithological study and hobbyist wildlife observation.