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020 _a9789811662102
024 7 _a10.1007/978-981-16-6210-2
_2doi
040 _aTR-AnTOB
_beng
_erda
_cTR-AnTOB
041 _aeng
050 4 _aS494.5.D3
072 7 _aUT
_2bicssc
072 7 _aTEC007000
_2bisacsh
072 7 _aUT
_2thema
090 _aS494.5.D3EBK
245 1 0 _aInternet of Things and Analytics for Agriculture, Volume 3
_h[electronic resource] /
_cedited by Prasant Kumar Pattnaik, Raghvendra Kumar, Souvik Pal.
250 _a1st ed. 2022.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2022.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Big Data,
_x2197-6511 ;
_v99
505 0 _aIoT: Foundations and Applications -- Functional Framework for IoT-based agricultural system -- Field monitoring and automation system -- Agriculture Sensor Network: Infrastructure, protocols and standards -- Implementation of sensors and RFID for disease and pest control -- Sensor-based Precision agriculture, Sensor data acquisition. .
520 _aThe book discusses one of the major challenges in agriculture which is delivery of cultivate produce to the end consumers with best possible price and quality. Currently all over the world, it is found that around 50% of the farm produce never reaches the end consumer due to wastage and suboptimal prices. The authors present solutions to reduce the transport cost, predictability of prices on the past data analytics and the current market conditions, and number of middle hops and agents between the farmer and the end consumer using IoT-based solutions. Again, the demand by consumption of agricultural products could be predicted quantitatively; however, the variation of harvest and production by the change of farm's cultivated area, weather change, disease and insect damage, etc., could be difficult to be predicted, so that the supply and demand of agricultural products has not been controlled properly. To overcome, this edited book designed the IoT-based monitoring system to analyze crop environment and the method to improve the efficiency of decision making by analyzing harvest statistics. The book is also useful for academicians working in the areas of climate changes.
650 0 _aInternet of things.
650 0 _aArtificial intelligence.
650 0 _aAgriculture—Economic aspects.
650 0 _aSustainability.
650 1 4 _aInternet of Things.
650 2 4 _aArtificial Intelligence.
650 2 4 _aAgricultural Economics.
650 2 4 _aSustainability.
653 0 _aArtificial intelligence -- Agricultural applications
653 0 _aInternet of things
700 1 _aPattnaik, Prasant Kumar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKumar, Raghvendra.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aPal, Souvik.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
830 0 _aStudies in Big Data,
_x2197-6511 ;
_v99
856 4 0 _uhttps://doi.org/10.1007/978-981-16-6210-2
_3Springer eBooks
_zOnline access link to the resource
942 _2lcc
_cEBK