By Ard0230 November 15, 2019

Big data is gathered from a huge collection of data created by the measurements of agriculture practice. More so its development is devised as precision agriculture. Precision agriculture digitizes traditional method of agriculture by responding to soil, crop and climate changes (Bronson and Keevil, 2019). Miles suggest precision agriculture implements computerized information “into farm management, from satellites and tractors to drones and machine learning algorithms” (Miles, 2019, p.2). Farm equipment uses ‘Big Data’ in harvesting from the field, giving an increase understanding towards conventional farming. It uses algorithmic technologies in farming operations for weather forecast and planting preparations.

The collection of big data analytics can be used on agricultural disaster management.  By digging through unstructured data and knowledge from past, it finds out patterns that could give farmers an idea in managing upcoming disaster that may potentially harm farming ahead of time. GPS satellites are mounted on the field and used to handle soil and crop measurements which then uses GPS signals for accuracy. Its process minimalizes pest and diseases through a precise targeted application of pesticide. Rather than ploughing or fertilizing by eye, farmers can calculate number of necessary alternatives for a certain field to a precise amount. It considers various ecological factor into account to maximise the crop by dispensing “accurate agricultural inputs in real time and in specific field areas” (Salima et al., 2019, p. 603). Making it possible to avoid excess of raw materials, when beforehand this was used as spares. In doing so results in increases productivity on areas of the field that needs more watering or ploughing. Beyond its reduction of negative environmental process, it has enhanced the social aspect of farming and the value of the work.

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