Zero-shot Microclimate Prediction with Deep Learning

• URL: http://arxiv.org/abs/2401.02665v1
• Date: Fri, 5 Jan 2024 06:46:56 GMT
• Title: Zero-shot Microclimate Prediction with Deep Learning
• Authors: Iman Deznabi, Peeyush Kumar, Madalina Fiterau
• Abstract summary: We propose a novel zero-shot learning approach designed to forecast various climate measurements at new and unmonitored locations. Our method surpasses conventional weather forecasting techniques in predicting microclimate variables by leveraging knowledge extracted from other geographic locations.
• Score: 5.335262943835543
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Weather station data is a valuable resource for climate prediction, however, its reliability can be limited in remote locations. To compound the issue, making local predictions often relies on sensor data that may not be accessible for a new, previously unmonitored location. In response to these challenges, we propose a novel zero-shot learning approach designed to forecast various climate measurements at new and unmonitored locations. Our method surpasses conventional weather forecasting techniques in predicting microclimate variables by leveraging knowledge extracted from other geographic locations.

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