The rapid proliferation of intelligent infrastructure has made the protection of homes ever more crucial. This Work describes a smart home security system based on AIoT, which combines sensing devices, cloud computing, and AI for real-time detection of invaders and subsequent alerts. The system uses a Raspberry Pi 3 connected with an ultrasonic sensor and a Pi Camera for activity tracking at access points. The camera takes a photograph once motion is detected, which is then sent to Amazon S3. An AWS Lambda function is then triggered for using Amazon Rekognition for comparison of identified faces with a collection of registered family members. Based on the success of this comparison, people are labeled as either known occupants or intruders. The results are stored in the cloud and immediately relayed to the homeowner through a Telegram bot sending marked up images and alerts. Experimental results suggest that the system attains on-average detection latency of 150 ms, a recognition accuracy of 93.7 % for faces, and alert dispatching within 1.2 seconds. Tests performed under different conditions of illumination, distance, and scenarios involving intruders demonstrate the robustness of the solution. With a serverless structure and modular components, this system offers a scalable, reliable, and cost-effective solution for smart home security.