WEATHERAI

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WaterView uses advanced computer vision and AI technologies to transform common cameras into multivariable sensors for real-time granular weather and environmental monitoring, reducing costs. First-generation models require expensive hardware and software and device calibration, while WeatherAI’s second-generation AI analysis is more portable and scalable and trained on optimized datasets. This could be a significant breakthrough in improving the ability to monitor the environment and climate on a global scale.

Start date: 01/06/2021

Duration in months: 12

Problem Description

WeatherAI wants to develop a second generation of AI algorithms that is more portable and scalable and trained on optimized datasets.

Goals

New services

Challenges

Parallelize training algorithm on HPC to achieve the required accuracy in inference.

Innovation results

GPUs were used for the model training. Parallel CPUs were used for image augmentation. Hyperparameters and datasets were optimized for 5 models.

Business impact

Test-before-invest. It is possible to test the feasibility of using AI to develop weather monitoring analytics, before buying the hardware

Project page

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