IoT-based intelligent modular LED lighting with redundancy and decentralized control for smart industrial and urban applications

This paper introduces the design and implementation of an intelligent, modular Light Emitting Diode (LED) lighting system for industrial and municipal applications, leveraging modern computer science methods and the Internet of Things (IoT). The system features power redundancy, decentralized control, and native support for Power Line Communication (PLC) and the Digital Addressable Lighting Interface (DALI) to ensure high reliability, low latency, and energy efficiency. We detail a robust communication and data transmission architecture together with sensor-driven control algorithms that enable context-aware dimming, occupancy-based scheduling, and continuous self-tuning to reduce consumption while maintaining lighting quality. Simulation studies and laboratory prototypes demonstrate marked performance gains: Mean Time Between Failures (MTBF) increases by more than 60%, reaching up to 65,000 hours, and energy savings reach approximately 30% relative to conventional deployments. The modular design facilitates phased rollouts and retrofits, while built-in monitoring, diagnostics, and predictive maintenance analytics improve lifecycle management and reduce downtime. The proposed approach aligns with smart-city initiatives and Industry 4.0 automation, providing interoperable management, centralized orchestration, and fine-grained control across heterogeneous facilities.

Authors

Publication Details

Journal
International Journal of Innovative Research and Scientific Studies
Published
2025-09-18
DOI
https://doi.org/10.53894/ijirss.v8i6.9963
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
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article

IoT-based intelligent modular LED lighting with redundancy and decentralized control for smart industrial and urban applications

Mukhtar Junisbekov, Murat Kunelbayev, Yerbol Turgynbekov, Dmitriy Grigoryev et al.
International Journal of Innovative Research and Scientific Studies
Impact of Light on Environment and Health
article

IoT-based intelligent modular LED lighting with redundancy and decentralized control for smart industrial and urban applications

Mukhtar Junisbekov, Murat Kunelbayev, Yerbol Turgynbekov, Dmitriy Grigoryev, Kairat Sakan
article en

Abstract

This paper introduces the design and implementation of an intelligent, modular Light Emitting Diode (LED) lighting system for industrial and municipal applications, leveraging modern computer science methods and the Internet of Things (IoT). The system features power redundancy, decentralized control, and native support for Power Line Communication (PLC) and the Digital Addressable Lighting Interface (DALI) to ensure high reliability, low latency, and energy efficiency. We detail a robust communication and data transmission architecture together with sensor-driven control algorithms that enable context-aware dimming, occupancy-based scheduling, and continuous self-tuning to reduce consumption while maintaining lighting quality. Simulation studies and laboratory prototypes demonstrate marked performance gains: Mean Time Between Failures (MTBF) increases by more than 60%, reaching up to 65,000 hours, and energy savings reach approximately 30% relative to conventional deployments. The modular design facilitates phased rollouts and retrofits, while built-in monitoring, diagnostics, and predictive maintenance analytics improve lifecycle management and reduce downtime. The proposed approach aligns with smart-city initiatives and Industry 4.0 automation, providing interoperable management, centralized orchestration, and fine-grained control across heterogeneous facilities.

International Journal of Innovative Research and Scientific StudiesVol. 8(6)
Openalex Percentile: Top 76%
Impact of Light on Environment and Health
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IoT-based intelligent modular LED lighting with redundancy and decentralized control for smart industrial and urban applications — Mukhtar Junisbekov, Murat Kunelbayev, et al. · International Journal of Innovative Research and Scientific Studies (2025) | TGRS Research Map | TGRS