Cloud-Based AI Surveillance for Motion Detection and Facial Recognition

Abstract

This research paper presents an automated monitoring system developed with diverse technologies combining cloud computing and Internet of Things (IoT). The system includes motion sensing, image capturing, and facial recognition by the cloud (AWS Rekognition) powered artificial intelligent (AI) algorithms for the better security measures of tracking and recognizing people within surveillance areas. When the sensor attached to the Arduino detects motion, then the camera captures an image of the moving element (the person). That image will be sent to Amazon S3, causing a trigger on an AWS Lambda function, and then using Amazon Rekognition to recognize faces.By leveraging Arduino hardware combined with serverless computing and scalable cloud service, it makes the system accessible, cheap, and a solution to real-time surveillance and identification. Traditional cloud-based surveillance systems offer scalability and remote access, yet they consume a lot of bandwidth and incur high latencies owing to continuous streaming, thus creating a limit in efficiency and responsiveness. Safety and affordability of Arduino, flexibility, easy integration with other sensors make it a better choice for putting together scalable intelligent monitoring applications.