{"id":761356,"date":"2021-07-15T12:13:54","date_gmt":"2021-07-15T19:13:54","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=761356"},"modified":"2021-10-01T13:37:04","modified_gmt":"2021-10-01T20:37:04","slug":"micro-climate-prediction-multi-scale-encoder-decoder-based-deep-learning-framework","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/micro-climate-prediction-multi-scale-encoder-decoder-based-deep-learning-framework\/","title":{"rendered":"Micro-climate Prediction &#8211; Multi Scale Encoder-decoder based Deep Learning Framework"},"content":{"rendered":"<p>This paper presents a deep learning approach for a versatile Micro-climate prediction framework (DeepMC). Micro climate predictions are of critical importance across various applications, such as Agriculture, Forestry, Energy, Search & Rescue, etc. To the best of our knowledge, there is no other single framework which can accurately predict various micro-climate entities using Internet of Things (IoT) data. We present a generic framework (DeepMC) which predicts various climatic parameters such as soil moisture, humidity, wind speed, radiation, temperature based on the requirement over a period of 12 hours &#8211; 120 hours with a varying resolution of 1 hour &#8211; 6 hours, respectively. This framework proposes the following new ideas: 1) Localization of weather forecast to IoT sensors by fusing weather station forecasts with the decomposition of IoT data at multiple scales and 2) A multi-scale encoder and two levels of attention mechanisms which learns a latent representation of the interaction between various resolutions of the IoT sensor data and weather station forecasts. We present multiple real-world agricultural and energy scenarios, and report results with uncertainty estimates from the live deployment of DeepMC, which demonstrate that DeepMC outperforms various baseline methods and reports 90%+ accuracy with tight error bounds.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper presents a deep learning approach for a versatile Micro-climate prediction framework (DeepMC). Micro climate predictions are of critical importance across various applications, such as Agriculture, Forestry, Energy, Search & Rescue, etc. To the best of our knowledge, there is no other single framework which can accurately predict various micro-climate entities using Internet of [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"2021 Knowledge Discovery and Data 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Access to high-quality micro-climate predictions is difficult due to high degree of variability across regions and stochastic local effects. This project addresses these issues by developing technology that enable systems workflows relying on micro-climate predictions.","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/924843"}]}},{"ID":881235,"post_title":"Project FarmVibes","post_name":"project-farmvibes","post_type":"msr-project","post_date":"2022-10-06 08:00:00","post_modified":"2024-07-29 09:55:45","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/project-farmvibes\/","post_excerpt":"Democratizing digital tools for sustainable agriculture As one of the biggest contributors to climate change, agriculture, along with land use degradation and deforestation, account for about a quarter of the global GHG emissions and consumes about 70% of the world\u2019s freshwater resources. Agriculture is also amongst the most impacted by climate change. Farmers depend on predictable weather for their farm management practices, and unexpected weather events, e.g., high heat, floods, etc. leaves them unprepared to&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/881235"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/761356","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/761356\/revisions"}],"predecessor-version":[{"id":761362,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/761356\/revisions\/761362"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=761356"}],"wp:term":[{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=761356"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=761356"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=761356"},{"taxonomy":"msr-publisher","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publisher?post=761356"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=761356"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=761356"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=761356"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=761356"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=761356"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=761356"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=761356"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=761356"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}