AI Security Camera Control System

I want to put intelligence behind my existing IP cameras so they can spot unusual activity on their own and trigger the right security responses without me lifting a finger. The core of the job is to build an AI-driven controller that watches the live feed, detects predefined events (motion in restricted hours, unknown faces, package removal, etc.), and then automatically issues the appropriate security alert—push notification, email, or siren—through a simple dashboard or mobile push gateway. Scope of work • Connect to standard ONVIF or RTSP cameras on my local network. • Run real-time video analytics (OpenCV, TensorFlow, or another proven framework is fine) to classify events I can customise later. • Expose a lightweight web or REST interface so I can arm/disarm zones and review alert logs. • Push alerts instantly to my phone and optionally trigger a relay (e.g., a smart siren). • Package everything so it installs on a small box in my office (Raspberry Pi 4 or Ubuntu server—your call, just outline the resource requirements). Acceptance criteria 1. At least three event types reliably detected (e.g., motion, person, package). 2. <1 second latency from detection to alert on a local network. 3. Clear setup guide that lets me add or remove cameras and tweak sensitivity without touching code. 4. Source code delivered in a Git repo with comments and a brief README. If you have prior work with Home Assistant, MQTT, or similar automation stacks, please mention it—plug-and-play is a big plus for me.