Distributed Smart Street Lighting: A Case Study on Predictive Control under Heterogeneous Road Traffic
The reliability of distributed smart streetlight control networks, like the Traffic-Aware Street Lighting Scheme Management Network (TALiSMaN), tends to drop during peak traffic hours. This is caused by heavy data broadcast within the network. As a result, TALiSMaN experiences unexpected network con...
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| Main Authors: | , , |
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| Format: | Proceeding |
| Language: | en |
| Published: |
2025
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/50719/4/ICEEI%202025%20-%20Copy.pdf http://ir.unimas.my/id/eprint/50719/ https://ftsm.ukm.my/iceei2025/images/programme/PROGRAMBOOK_ICEEI2025.pdf |
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| Summary: | The reliability of distributed smart streetlight control networks, like the Traffic-Aware Street Lighting Scheme Management Network (TALiSMaN), tends to drop during peak traffic hours. This is caused by heavy data broadcast within the network. As a result, TALiSMaN experiences unexpected network congestion and subsequently increases the packet loss rate. To address this limitation, a predictive control scheme is proposed and integrated into TALiSMaN. This scheme enables TALiSMaN to predict road traffic conditions for real-time adjustments to data broadcasting rates and streetlight brightness levels. The performance of the proposed scheme was simulated and evaluated under two streetlight network topologies: linear and cross-junction. While the proposed scheme reduces packet drop by an average of 0.01%–5.63% and 0.04%–6.28% across two network topologies, the simulation results also demonstrate an improvement in the streetlight usefulness. However, these improvements come with an energy use trade-off. Compared to standard TALiSMaN, the proposed scheme consumed 1.7–12.7 times more energy. |
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