Data-driven techniques help boost agricultural productivity by increasing yields, reducing losses and cutting down input costs. However, these techniques have seen sparse adoption owing to high costs of manual data collection and limited connectivity solutions. In this paper, we present FarmBeats, an end-to-end IoT platform for agriculture that enables seamless data collection from various sensors, cameras and drones. FarmBeats\u2019s system design that explicitly accounts for weather-related power and Internet outages has enabled six month long deployments in two US farms.<\/p>\n","protected":false},"excerpt":{"rendered":"
Data-driven techniques help boost agricultural productivity by increasing yields, reducing losses and cutting down input costs. However, these techniques have seen sparse adoption owing to high costs of manual data collection and limited connectivity solutions. In this paper, we present FarmBeats, an end-to-end IoT platform for agriculture that enables seamless data collection from various sensors, […]<\/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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556,13562,13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-374810","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-computer-vision","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"USENIX","msr_edition":"","msr_affiliation":"","msr_published_date":"2017-3-27","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"375425","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2017\/03\/FarmBeats-webpage-1.pdf","id":"375425","title":"FarmBeats-webpage","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"user_nicename","value":"Deepak Vasisht","user_id":40231,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Deepak Vasisht"},{"type":"user_nicename","value":"Zerina Kapetanovic","user_id":42303,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Zerina Kapetanovic"},{"type":"text","value":"JongHo Won","user_id":0,"rest_url":false},{"type":"text","value":"Xinxin Jin","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Ranveer Chandra","user_id":33344,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ranveer Chandra"},{"type":"user_nicename","value":"Sudipta Sinha","user_id":33748,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Sudipta Sinha"},{"type":"user_nicename","value":"Ashish Kapoor","user_id":30903,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ashish Kapoor"}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[355739],"msr_group":[714067,768895],"msr_project":[881235,239387,171068,170158],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"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…","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/881235"}]}},{"ID":239387,"post_title":"FarmBeats: AI, Edge & IoT for Agriculture","post_name":"farmbeats-iot-agriculture","post_type":"msr-project","post_date":"2016-06-16 20:10:17","post_modified":"2024-08-29 22:15:59","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/farmbeats-iot-agriculture\/","post_excerpt":"Our goal is to enable data-driven farming. We believe that data, coupled with the farmer's knowledge and intuition about his or her farm, can help increase farm productivity, and also help reduce costs. 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