Soil Moisture and Soil Electrical Conductivity (EC) are important parameters for data-driven farming. This knowledge can help a farmer improve crop yield, reduce input costs, and adopt sustainable agriculture practices. However, the high cost of commercial soil moisture and EC sensors has limited their adoption. In this paper, we present the design and implementation of a system, called SMURF, that senses soil moisture and soil EC using RF propagation in existing Wi-Fi bands. It overcomes the key challenge of limited bandwidth availability in the 2.4 GHz unlicensed spectrum using a novel multi-antenna technique that maps the propagation time and amplitude of Wi-Fi at the different antennas as a function of the refractivity and permittivity of soil, and uses them to infer soil moisture and EC.\u00a0 Our experiments with software defined radios (USRP and WARP), and two commodity Wi-Fi cards show that SMURF can accurately estimate soil moisture and EC using Wi-Fi, thereby enabling a future in which a farmer with a smartphone that has a Wi-Fi radio can sense soil in her farm without investing 100s of dollars in soil sensing equipment.<\/p>\n","protected":false},"excerpt":{"rendered":"
Soil Moisture and Soil Electrical Conductivity (EC) are important parameters for data-driven farming. This knowledge can help a farmer improve crop yield, reduce input costs, and adopt sustainable agriculture practices. However, the high cost of commercial soil moisture and EC sensors has limited their adoption. In this paper, we present the design and implementation of […]<\/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":[13547],"msr-publication-type":[193718],"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-509966","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2018-10-07","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-TR-2018-29","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":"510653","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"SMURF_TR (1)","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2018\/10\/SMURF_TR-1.pdf","id":510653,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":510653,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2018\/10\/SMURF_TR-1.pdf"}],"msr-author-ordering":[{"type":"text","value":"Jian Ding","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"}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[],"msr_project":[881235,239387],"publication":[],"video":[],"download":[],"msr_publication_type":"techreport","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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