An Automatic and Intelligent Internet of Things for Future Agriculture
Great advances in artificial intelligence and the Internet of Things have been made in recent years. This work develops an intelligent agricultural cultivation system to realize automated and intelligent farm cultivation management and operation. Experimental results demonstrate that the proposed sy...
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| Veröffentlicht in: | IT professional 2022-11, Vol.24 (6), p.74-80 |
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| creator | Ma, Yi-Wei Chen, Jiann-Liang Shih, Ching-Chiu Dabirian, Amir |
| description | Great advances in artificial intelligence and the Internet of Things have been made in recent years. This work develops an intelligent agricultural cultivation system to realize automated and intelligent farm cultivation management and operation. Experimental results demonstrate that the proposed system reduces water consumption by 50% and 30%, respectively, below those of fixed and threshold irrigation methods and predicts more accurately the amount of irrigation water required. The proposed dynamic detection transmission mechanism performs 97.8% fewer communications than are performed in timing transmission mode, effectively reducing overall energy consumption for transmission. Experimental results show that the proposed system reduces cultivation time by 40.94% below that required by the traditional cultivation method, and supports more effective management. Based on all of the experimental results, the proposed method supports convenient cultivation for growers. |
| doi_str_mv | 10.1109/MITP.2022.3205707 |
| format | Article |
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This work develops an intelligent agricultural cultivation system to realize automated and intelligent farm cultivation management and operation. Experimental results demonstrate that the proposed system reduces water consumption by 50% and 30%, respectively, below those of fixed and threshold irrigation methods and predicts more accurately the amount of irrigation water required. The proposed dynamic detection transmission mechanism performs 97.8% fewer communications than are performed in timing transmission mode, effectively reducing overall energy consumption for transmission. Experimental results show that the proposed system reduces cultivation time by 40.94% below that required by the traditional cultivation method, and supports more effective management. 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Based on all of the experimental results, the proposed method supports convenient cultivation for growers.</description><subject>Artificial intelligence</subject><subject>Crops</subject><subject>Cultivation</subject><subject>Data collection</subject><subject>Energy consumption</subject><subject>Farms</subject><subject>Internet of Things</subject><subject>Irrigation</subject><subject>Irrigation water</subject><subject>Machine learning</subject><subject>Smart agriculture</subject><subject>Water consumption</subject><issn>1520-9202</issn><issn>1941-045X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkD1PwzAQhi0EEqXwA5AYLDGn3PkjjseoolAJBEOR2KzUtUuq1CmOM_DvSWgHpnuH5707PYTcIswQQT-8LlfvMwaMzTgDqUCdkQlqgRkI-Xk-ZMkg0wNwSa66bgeAuRDFhCzKQMs-tfsq1ZZWYUOXIbmmqbcupL8cg0u09XT1VYdtR30b6aJPfXS03Mba9s2Yr8mFr5rO3ZzmlHwsHlfz5-zl7Wk5L18yy5hImdAWJXgplfdaKqa0Zw4Vd0xYnXOdaw1--H-z9pWS62oNwnNpmSoKWXAs-JTcH_ceYvvduy6ZXdvHMJw0TOV5zhlyHCg8Uja2XRedN4dY76v4YxDMqMuMusyoy5x0DZ27Y6d2zv3jAZVAxn8B9vFkug</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Ma, Yi-Wei</creator><creator>Chen, Jiann-Liang</creator><creator>Shih, Ching-Chiu</creator><creator>Dabirian, Amir</creator><general>IEEE</general><general>IEEE Computer Society</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope><orcidid>https://orcid.org/0000-0002-3279-6918</orcidid><orcidid>https://orcid.org/0000-0003-0400-5514</orcidid></search><sort><creationdate>20221101</creationdate><title>An Automatic and Intelligent Internet of Things for Future Agriculture</title><author>Ma, Yi-Wei ; Chen, Jiann-Liang ; Shih, Ching-Chiu ; Dabirian, Amir</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c224t-49c150f557ff957279f2e173e24c96396990f205dbfa75bab04f35c2788583183</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial intelligence</topic><topic>Crops</topic><topic>Cultivation</topic><topic>Data collection</topic><topic>Energy consumption</topic><topic>Farms</topic><topic>Internet of Things</topic><topic>Irrigation</topic><topic>Irrigation water</topic><topic>Machine learning</topic><topic>Smart agriculture</topic><topic>Water consumption</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ma, Yi-Wei</creatorcontrib><creatorcontrib>Chen, Jiann-Liang</creatorcontrib><creatorcontrib>Shih, Ching-Chiu</creatorcontrib><creatorcontrib>Dabirian, Amir</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><jtitle>IT professional</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ma, Yi-Wei</au><au>Chen, Jiann-Liang</au><au>Shih, Ching-Chiu</au><au>Dabirian, Amir</au><au>Amir Dabirian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Automatic and Intelligent Internet of Things for Future Agriculture</atitle><jtitle>IT professional</jtitle><stitle>ITP-M</stitle><date>2022-11-01</date><risdate>2022</risdate><volume>24</volume><issue>6</issue><spage>74</spage><epage>80</epage><pages>74-80</pages><issn>1520-9202</issn><eissn>1941-045X</eissn><coden>IPMAFM</coden><abstract>Great advances in artificial intelligence and the Internet of Things have been made in recent years. This work develops an intelligent agricultural cultivation system to realize automated and intelligent farm cultivation management and operation. Experimental results demonstrate that the proposed system reduces water consumption by 50% and 30%, respectively, below those of fixed and threshold irrigation methods and predicts more accurately the amount of irrigation water required. The proposed dynamic detection transmission mechanism performs 97.8% fewer communications than are performed in timing transmission mode, effectively reducing overall energy consumption for transmission. Experimental results show that the proposed system reduces cultivation time by 40.94% below that required by the traditional cultivation method, and supports more effective management. Based on all of the experimental results, the proposed method supports convenient cultivation for growers.</abstract><cop>Washington</cop><pub>IEEE</pub><doi>10.1109/MITP.2022.3205707</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-3279-6918</orcidid><orcidid>https://orcid.org/0000-0003-0400-5514</orcidid></addata></record> |
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| ispartof | IT professional, 2022-11, Vol.24 (6), p.74-80 |
| issn | 1520-9202 1941-045X |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Artificial intelligence Crops Cultivation Data collection Energy consumption Farms Internet of Things Irrigation Irrigation water Machine learning Smart agriculture Water consumption |
| title | An Automatic and Intelligent Internet of Things for Future Agriculture |
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