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How artificial intelligence is helping Ghana plan for a renewable energy future

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Inhalt bereitgestellt von Nature Publishing Group and Nature Careers. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Nature Publishing Group and Nature Careers oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Julien Harou’s career started in geology in his current role as a water management and infrastructure researcher now straddles economics and engineering, with a particular focus on using artificial intelligence (AI) to measure Ghana’s future energy needs.


Harou is relatively upbeat about progress so far towards achieving sustainable and reliable energy for all by 2030, the seventh of 17 Sustainable Development Goals (SDGs) agreed by the United Nations in 2015. He points out that from 2015 to 2021, the portion of the global population with access to electricity increased from 87% to 91%, and last year about 30% came from renewable sources.


Harou’s research at the University of Manchester, UK, incorporates computer modeling and artificial intelligence design algorithms to balance Ghana’s long term renewable energy and infrastructure needs. But AI also helps to address the environmental and human health impacts. For example, Ghana’s Volta River was dammed in the 1960s to create the Akosombo dam. But its arrival depleted fish stocks and increased weed and algae growth, providing habitat for vectors of waterborne diseases. It’s all about compromise, he tells the seventh episode of How to Save Humanity in 17 Goals, a podcast series that profiles scientists whose work addresses one or more of the SDGs.


Episodes 7-12 are produced in partnership with Nature Water, and introduced by Fabio Pullizi, its chief editor.



Hosted on Acast. See acast.com/privacy for more information.

  continue reading

170 Episoden

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iconTeilen
 
Manage episode 416932671 series 2435388
Inhalt bereitgestellt von Nature Publishing Group and Nature Careers. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Nature Publishing Group and Nature Careers oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Julien Harou’s career started in geology in his current role as a water management and infrastructure researcher now straddles economics and engineering, with a particular focus on using artificial intelligence (AI) to measure Ghana’s future energy needs.


Harou is relatively upbeat about progress so far towards achieving sustainable and reliable energy for all by 2030, the seventh of 17 Sustainable Development Goals (SDGs) agreed by the United Nations in 2015. He points out that from 2015 to 2021, the portion of the global population with access to electricity increased from 87% to 91%, and last year about 30% came from renewable sources.


Harou’s research at the University of Manchester, UK, incorporates computer modeling and artificial intelligence design algorithms to balance Ghana’s long term renewable energy and infrastructure needs. But AI also helps to address the environmental and human health impacts. For example, Ghana’s Volta River was dammed in the 1960s to create the Akosombo dam. But its arrival depleted fish stocks and increased weed and algae growth, providing habitat for vectors of waterborne diseases. It’s all about compromise, he tells the seventh episode of How to Save Humanity in 17 Goals, a podcast series that profiles scientists whose work addresses one or more of the SDGs.


Episodes 7-12 are produced in partnership with Nature Water, and introduced by Fabio Pullizi, its chief editor.



Hosted on Acast. See acast.com/privacy for more information.

  continue reading

170 Episoden

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