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Index    Newsroom    News    News Content
news 2019/05/01

AAEON Intelligent Street Light


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AAEON Intelligent Street Light

Intelligent Street Lights are an integral component to building Smart Cities. Not only can they provide illumination, they can also be used to help detect environmental conditions and provide greater services throughout the city. The biggest benefits are helping cities become safer, more flexible and improve energy efficiency.


Intelligent Street Lights are controlled through both edge sensors and the Central Management System. Illumination varies based on surroundings, ensuring the most efficient use of resources. In case of a malfunction, the system immediately notifies the administrator, enabling prompt response times. The user friendly interface allows for management that is convenient and efficient in real time from a remote site.


Thanks to the Intelligent Street Light system from AAEON, implementing Smart City solutions is easier than ever, allowing more cities to save energy, reduce CO2 emissions, and reduce maintenance costs. The time and money saved by Intelligent Street Lights can allow Smart Cities to invest in upgrading other facilities and provide financial flexibility.


Watch our video to learn more about how AAEON and Intelligent Street Lights are making Smart Cities safer, flexible, and energy efficient.



Edge Computing

AAEON Atlas*, powered by Intel Vision Products, is a powerful edge computing node that consolidates data streams from smart lighting, environmental monitoring, and video sensors. Atlas works at the edge to allow city administrators to create a connected data hub that enables numerous new applications. For example, when the Atlas edge node is deployed in conjunction with a camera, network video recorder (NVR), and management system, it can power a citywide parking application. Car drivers can park on city streets without having to fish for change or pay at a meter—nearby smart cameras on streetlights can capture and classify images such as license plates using computer vision and charge the owner directly for the exact parking time via a gateway and cloud-based management system connected to a department of motor vehicles database.


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