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Understanding the Innovation Landscape needed for Enabling Technologies in the World’s Energy Transition

Paul Hobcraft

IRENA’s Innovation Landscape report highlights innovations in enabling technologies and explored explicitly in the following briefs, where you go automatically to the download: Utility-scale batteries. Artificial Intelligence and Big Data. Also, IRENA produced a substantial main Innovation Landscape report. Blockchain.

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Continuing the Energy Transition Journey

Paul Hobcraft

Everywhere you turn, you stumble across reports on one aspect or another of the energy transformation we are undertaking. I am looking at this energy transition through the eyes of the innovator, as it offers so much in new solutions and designs that any innovator would love to be part of. degree mark.

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New Technology Improving Worldwide Health & Wellness

eZassi

released a joint report that claimed 40% of the world population suffers from water scarcity and that by 2030, 700 million people may be displaced because of it. Designing Technology for Improved Mobility. Collaboration for Clean Water is the Current Mother of Invention. Water makes up 70% of the Earth’s surface, but only 2.5%

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6 Ways to Drive Sustainability in Transportation

Acuvate

A significant step in this journey has been taken at a recently concluded COP26 summit, where various governments have pledged to reduce emissions by 2030. Acuvate helped the government department of a large city metropolis install cameras (with mics) that leverage AI in specific locations. With our planet on a path to a 2.7

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10 Most Popular Tech Scouting Questions Answered

PlanBox Innovation

A tried-and-true approach is to design discovery sessions that leverage the 4 lenses of innovation. For example, try to conceptualize how you can expand into new markets using machine learning, artificial intelligence, etc. This allows you to explore new possibilities that you otherwise would not have considered.

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IoT-based Predictive Maintenance in Industry 4.0: The Way Forward

Acuvate

An IoT-based solution allows organizations to store and analyze terabytes of equipment data run and machine learning algorithms to forecast failures and hazards and predict when industrial equipment is likely to fail.​ Why IoT-based predictive maintenance in industry 4.0 billion by 2030? An analytics layer extracts insights.