Integrating Big Data Analytics Into Farm Management
The modern world revolves around data, may it be traditional sales and stocks value projection or more modern uses like targeted advertising and engagement analytics, but the applications go far beyond the expected; Big Data Analytics can be used to streamline and manage a number of larger processes, including the management of framland, equipment and yield projections.
By creating opportunities for intimate management of large operations without needing the traditional manpower and time investment, almost all processes from yield projection to harvest can be improved with the application of Big Data Analysis to farm management.
Here, we’ll discuss applications of Big Data Analytics in farm management, the potential boon of introducing data analytics into each key stage of farm management, and discuss how integrating these processes into everyday practices can improve yield, increase profits and save money.
Analytics can use decades of data gathered on weather patterns, yield and records of successful and failed crops to make deciding what to plant, when to plant and profit the margins to work within, for best results. “Informed farmers can avoid debt, decrease overheads and bolster their business with new ventures, all through accessing Big Data Analytics” comments Linda Williams, a business blogger at UK Writings and Best british essays.
Remote Machine Management
Machinery can be an unpredictable overhead; poor time management can leave machinery sat in a barn unutilised, while unnoticed faults can quickly become serious damage that can leave a tractor out of use for long periods of time. Using Big Data Analytics, large machinery can be controlled and monitored remotely, allowing an entire fleet to be maintained by a single operator. Installing sensors both within and outside of the machinery allows automated and instant recognition of faults, of machines left not in use or alerts for scheduled maintenance and required downtime, preventing development of faults.
Digital Farm Management
With crop management machinery automated, fields can be cared for remotely. Plowing earth and seed distribution, watering and pesticide dispersal are achieved without having to attend to crops directly, while sensors and automatic data collection enabled through Big Data Analytics gather information on crop health. Farm owners can direct machinery to attend to entire fields and focus on other matters while the crops are maintained, improving employee satisfaction through reduced workload, stress and permitting other objectives to be achieved.
Digging further into the applications of automated crop care, sensory equipment and machinery tracking allows plants to be assessed and managed on an individual basis. Known as Precision Farming, this adds a layer of tailored care traditional farming could not manage, resulting in less pesticide usage, lower overhead costs and a higher yield of healthy crops by limiting the spread of disease and infestations at a plant to plant level.
Increased Employee Safeguards
With less farmhands managing large, dangerous machinery, the potential for injury also falls, in turn lowering insurance premiums and improving employee morale. When time feels used efficiently and stress levels are low, farm hands are more productive and don’t have to have the lengthy training required to handle heavy machinery unless required, again lowering overheads.
“Automating machinery creates an organised business and content workforce, where individuals feel valued for their contribution and feel safe in the fields. Better organisation guarantees a higher profit margin; it’s simple fact,” offers David Allen, tech writer at Eliteassignmenthelp and Academized.
Food Safety Security
The correct care, timely harvest and storage of crops is vital to maintain freshness, reduce waste and increase profits. Automated machinery can use data gathered by Big Data Analytics to set harvester blades at heights less likely to damage crops and alert if a crop has been gathered but not stored correctly. Appropriate storage conditions, shelf life and common faults and blemishes of crops can all maintain quality until it’s shipped.
Big Data Analytics in Farm Management: Conclusions
As daunting as it seems to integrate into farm management, Big Data Analytics has a multitude of applications that create efficient daily practices, increase profits and improve quality and yield without sacrificing employee satisfaction. In a world where data is a gift to businesses, it makes sense to integrate Big Data Analytics into aspects of farm management.
This post does not have any comments. Be the first to leave a comment below.
Post A Comment
You must be logged in before you can post a comment. Login now.