Lighting control of LEDs considering ambient sound variations to meet the requirements of smart cities

Kalani, Mohammad Javad; Kalani, Mahdi; Naderi, Mehdi Salay; Gharehpetian, Gevork B.

doi:10.1016/j.compeleceng.2022.108240

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2024

Publication Types

Select...

Preprint1

Article1

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Optimization of the Spatial Location of Sound Sensors for Urban Noise Monitoring

Cheng,

Zhao,

Wang

et al. 2023

Preprint

View full text Add to dashboard Cite

Optimization of the Spatial Location of Sound Sensors for Urban Noise Monitoring

Cheng,

Zhao,

Wang

et al. 2023

Preprint

View full text Add to dashboard Cite

Internet of Things-Based Multi-Agent System for the Control of Smart Street Lighting

Kouah,

Saighi,

Ammi

et al. 2024

Electronics

View full text Add to dashboard Cite

The Internet of Things refers to a network of interconnected devices, objects, and systems, that can interact with one another without human intervention. The adoption of IoT technology has expanded rapidly, significantly impacting various fields, including smart healthcare, intelligent transportation, agriculture, and smart homes. This paper focuses on smart street lighting, which represents the core piece of the smart city and the key public service for citizens’ safety. Nevertheless, it poses substantial challenges related to energy consumption, especially during energy crises. This work aims to provide an advanced solution that enables intelligent control of street lighting, enhances human safety, reduces CO2 emissions and light pollution, and optimizes energy consumption, as well as facilitates maintenance of the lighting network. The solution is twofold: First, it introduces IoT-based smart street lighting referential models; second, it presents a framework for controlling smart street lighting based on the referential models. The proposal uses an IoT-based fuzzy multi-agent systems approach to address the challenges of smart street lighting. The approach leverages the strengths and properties of fuzzy logic and multi-agent systems to address the system requirements. This is illustrated through a testbed case study conducted on a concrete IoT prototype.

show abstract

Lighting control of LEDs considering ambient sound variations to meet the requirements of smart cities

Cited by 2 publications

References 12 publications

Optimization of the Spatial Location of Sound Sensors for Urban Noise Monitoring

Optimization of the Spatial Location of Sound Sensors for Urban Noise Monitoring

Internet of Things-Based Multi-Agent System for the Control of Smart Street Lighting

Contact Info

Product

Resources

About