HUMAN-CENTRIC AUTOMATED LIGHTING CONTROL ALGORITHM IN SMART BUILDINGS USING THE KINCONY ESP32 ARCHITECTURE

Abstract

This thesis section investigates the conceptualization, design, and structural integration of a human-centric automatic lighting control algorithm optimized for modern Smart Building Management Systems (SBMS). Traditional automated lighting topologies routinely rely on basic motion-detection parameters, which frequently generate false-negative states during periods of low physical mobility, culminating in ambient blackouts that compromise occupant comfort and cognitive focus. To mitigate these systemic inefficiencies, this work introduces an intelligent temporal-polling algorithm executed via an industrial-grade, ESP32-powered Kincony relay hardware ecosystem. By moving beyond reactive macro-movement triggers, the proposed algorithm establishes a non-disruptive presence verification framework operating on a flexible 5-to-10-minute dynamic evaluation window. This framework accounts comprehensively for the "human factor," balancing strict electrical energy conservation mandates with the physiological and psychological comfort demands of workspace occupants. The architectural framework, behavioral logic, hardware deployment, and comparative operational profiles are detailed herein to establish a standard for seamless, invisible automation within smart architectural environments.