AI/ML for 5G-Energy Consumption Modelling
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As we advance toward the
As we advance toward the global adoption of 5G networks, it becomes essential not only to boost their speed but also enhance their sustainability. The surge in the number of connected devices and the data explosion they induce has imposed a significant challenge on network operators: how to meet the escalating demand without skyrocketing the energy consumption.
Within this context, the energy optimization of base stations emerges as a pivotal aspect of constructing a sustainable and cost-efficient 5G network. Given the myriad factors that impact this energy consumption, having precise models that elucidate how different configurations and parameters affect energy usage is of utmost importance.
This is the juncture at which machine learning enters the picture. It potentially offers a robust tool for developing meticulous energy models and optimizing the energy consumption of the network. This challenge is designed to tackle this crucial concern, enabling participants to contribute towards crafting more energy-efficient 5G networks
Speakers
Nicola Piovesan
Senior Researcher
Huawei
Moderators:
Thomas Basikolo
Programme Officer
International Telecommunication Union (ITU)
Vishnu Ram OV
Independent Research Consultant
Consultant
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More than a Summit, more than a movement, AI for Good is presented as a year round digital platform where AI innovators and problem owners learn, build and connect to help identify practical AI solutions to advance the United Nations Sustainable Development Goals.
AI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.
Disclaimer:
The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.
Within this context, the energy optimization of base stations emerges as a pivotal aspect of constructing a sustainable and cost-efficient 5G network. Given the myriad factors that impact this energy consumption, having precise models that elucidate how different configurations and parameters affect energy usage is of utmost importance.
This is the juncture at which machine learning enters the picture. It potentially offers a robust tool for developing meticulous energy models and optimizing the energy consumption of the network. This challenge is designed to tackle this crucial concern, enabling participants to contribute towards crafting more energy-efficient 5G networks
Speakers
Nicola Piovesan
Senior Researcher
Huawei
Moderators:
Thomas Basikolo
Programme Officer
International Telecommunication Union (ITU)
Vishnu Ram OV
Independent Research Consultant
Consultant
Join the Neural Network!
👉https://aiforgood.itu.int/neural-netw...
The AI for Good networking community platform powered by AI.
Designed to help users build connections with innovators and experts, link innovative ideas with social impact opportunities, and bring the community together to advance the SDGs using AI.
🔴 Watch the latest #AIforGood videos!
aiforgood
📩 Stay updated and join our weekly AI for Good newsletter:
http://eepurl.com/gI2kJ5
🗞Check out the latest AI for Good news:
https://aiforgood.itu.int/newsroom/
📱Explore the AI for Good blog:
https://aiforgood.itu.int/ai-for-good...
🌎 Connect on our social media:
Website: https://aiforgood.itu.int/
Twitter: Twitter: AIforGood
LinkedIn Page: LinkedIn: 26511907
LinkedIn Group: LinkedIn: 8567748
Instagram: Instagram: aiforgood
Facebook: Facebook: AIforGood
What is AI for Good?
We have less than 10 years to solve the UN SDGs and AI holds great promise to advance many of the sustainable development goals and targets.
More than a Summit, more than a movement, AI for Good is presented as a year round digital platform where AI innovators and problem owners learn, build and connect to help identify practical AI solutions to advance the United Nations Sustainable Development Goals.
AI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.
Disclaimer:
The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.
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در تاریخ 1402/04/22 منتشر شده
است.
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