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

Paul Hobcraft

Artificial Intelligence and Big Data. The period 2020 to 2030 is absolutely critical for investments not just to be pledged but effectively deployed on the ground in the physical solutions and effective operation needed to make this energy transition required on track to reach the climate goals. Behind-the-meter batteries.

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Data-Driven Approaches Helping Public Sector with Sustainable Water Management

Acuvate

Some 700 million people could be displaced by intense water scarcity by 2030. Industrial IIoT, in particular, in the form of sensors, flow meters, and edge devices, are being used to collect on-field data to create situational awareness and identify leaks, sewer overflows, and faulty equipment before these require costly repairs.

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Iron Man: the hero of wearables and IoT

mjvinnovation

The forecast is that by the middle of 2030, we’ll have a trillion devices connected. Like Tony Stark, data scientists and organizations need to adapt to the opportunities and data volume of IoT. Understand the relationship between Big Data and Iron Man armor. Is too much data a problem?

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A Guide to Smart Cities

Innovation Walk

With the world’s population increasing at rapid rates, urbanisation has accelerated to the point where 68% of the world’s population will live in urban areas by 2050 and there will be 39 megacities by 2030, according to the United Nations and Euromonitor International , respectively.

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IoT for Logistics: Leveraging Data-driven decisions for Predictive and preventive Fleet Maintenance, Optimizing life cycle, and Ensuring Workforce Safety

Acuvate

In the age of data and AI, industry players are looking to maximize operational efficiency and enhance customer experience with game-changing IoT logistics and fleet management solutions. million by 2030. . It is not surprising that the global IoT market in logistics is expected to reach $100,984.5

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Analysis Of The Next-Generation Mobility Value Chain

Corporate Innovation

In my book The Big Data Opportunity In Our Driverless Future I identify two distinct value chains that have been established because of the car ownership-centric model that has been dominant for the past 70+ years: the vehicle manufacturing and sale value chain , and the vehicle use value chain.

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A New Way of Thinking About the Automotive Industry

Qmarkets

A recently published report by independent think tank RethinkX suggests that by 2030, 95% of U.S. Furthermore, as one billion people get in and out of cars every single day, McKinsey forecasts that aggregating and selling data from these vehicles could grow into a $450 to 750 billion market by 2030.