The Intelligent Lighting System using Artificial Intelligence (AI) and Big Data is designed to improve energy efficiency, automation, and user comfort in smart buildings and other intelligent environments. The system collects real-time information from occupancy or human-detection sensors, ambient-light sensors and lighting/energy measurements. The collected data is cleaned, transformed, stored and analysed to identify occupancy patterns, lighting requirements and energy-consumption trends. Based on the literature reviewed, the proposed system combines occupancy detection, adaptive lighting control, Big Data analytics and energy-consumption prediction. CNN-YOLO-based human detection can be used for occupancy identification, adaptive control can determine whether lighting should be switched or dimmed, distributed Big Data processing can support large historical datasets and a stacked LSTM model can be used for energy-consumption prediction. The integrated system is intended to reduce unnecessary lighting operation while maintaining suitable illumination.
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Alfiya Javeed (2026) studied this question.
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