Abstract
The enormous challenges that agriculture is facing today as consequence of negative impact of climate change must be dealt with by adopting advanced digital technologies. These technologies generate massive volumes of data, known as Big Data, e.g., sensors on fields and crops provide granular data points on soil conditions, as well as detailed information on wind, fertilizer requirements, water availability and pest infestations. The continuous measurement and monitoring of physical environment has enabled to proceed for adopting smart agriculture. Smart agriculture helps in automated farming, collection of data from the field and then analyses it so that the farmer can make informed decision with respect to optimal time of sowing/planting of the crops, optimal time for application of pesticides, insecticides, and fertilizers starting with sowing, and time for harvesting crops in order to grow high quality and larger quantity of crops. The scope of Big Data in not only confined to farm production but it influences the entire food supply chain. To extract information from large volumes of data so generated require a new generation of practices known as “Big Data Analytics”. Big Data, if unlocked intelligently, and analytics has the potential to add value across each step and can streamline food processing value chains starting from selection of right agri-inputs, monitoring the soil moisture, tracking prices of market, controlling irrigations, finding the right selling point and getting the right price.
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Nidhi (2020). Big Data for Smart Agriculture. In: Patnaik, S., Sen, S., Mahmoud, M. (eds) Smart Village Technology. Modeling and Optimization in Science and Technologies, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-030-37794-6_9
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DOI: https://doi.org/10.1007/978-3-030-37794-6_9
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