IntelliSpace: Cross-Platform Smart Campus Automation

Modern educational facilities frequently experience severe administrative friction and substantial energy waste due to unautomated electrical loads and manual oversight. Traditional institutional surveillance paradigms rely on passive recording or commercial cloud AI subscriptions that consume excessive WAN bandwidth, create recurring financial liabilities, and expose sensitive video feeds to external privacy hazards. To overcome these constraints, IntelliSpace introduces a fully decoupled, zerocloud edge automation framework engineered specifically for the Department of Information Technology at K.L.N. College of Engineering. The system unites on-premise neural perception, distributed microcontroller switching, and multi-tenant mobile management. Visual intelligence is decentralized to an on-premise Edge Computing Workstation with local GPU acceleration executing YOLOv8m-pose for 17-point skeletal landmarking and DeepFace for biometric verification, accomplishing real-time head-counting, lecture engagement assessment, and sub-1.5s emergency fall detection directly from local RTSP streams. Hardware actuation utilizes Wi-Fi-enabled ESP8266 NodeMCU nodes interfaced with optocoupled 2-channel active-LOW relays to regulate laboratory computing benches and classroom lighting. A cross-platform Flutter client coordinates dynamic 5- day cycle academic schedules, optimistic appliance switching, and on-device Google ML Kit OCR scanning of physical student ID credentials, pairing with an automated cloud SMS gateway for instant parent notification. Complemented by an interactive 3D/2D digital twin, long-range LoRa mesh telemetry, and solar UPS failover, IntelliSpace achieves complete data sovereignty, 142ms inference latency, and verified 34.2% energy conservation.