Constant innovation in farming techniques has drastically changed the agricultural output. Using technology in farming is not a new concept. In the primitive age, handheld tools were the standards of farming techniques until the first industrial revolution introduced cotton gin. The 18th century was dawned with the advent of chemical fertilizers, grain elevators, and the first gas-powered tractor. The early 20th century marked the usage of satellites for farmers to plan their work. The 21st century is all about next-gen technologies, where the internet of things is all set to push the future of farming at an unprecedented scale. A new era of smart farming is encompassing the agricultural space for enhanced output, making better-informed decisions and preparing for uncertain exigencies.
Recent estimates show that the world population will rise to 9.7 billion people by 2050. Keeping this number in mind, the UN estimates that global food production needs to increase by at least 60% to feed this rising population. To meet the demands, adopting traditional agricultural and livestock farming methods will be insufficient. Big data concepts like smart farming and precision agriculture are the solution to meet the demands. Smart farming is a farming management concept that uses information and communication technology (ICT) to increase the quantity and quality of agricultural products. Precision agriculture is about implementing automatically controlled machines, monitoring of the yields and different ways of fertilizer spreading and seed drilling.
With smart machines and sensors cropping up on farms, there is an abundance of data, both in quantity and scope. The entire farming is now being data-driven and data-enabled. Technologies in smart farming include tracking systems like Global Positioning System (GPS). GPS enables data to be allocated to a particular area of the land or help to determine the present location of machines or animals in the barn. Sensors in the farm help to measure mineral content, such as the nitrogen content or abundance of weed etc. The data collected from these sensors help to calculate the best fertilizer composition for that particular area and subsequently administer fertilizer as per the set rules and regulations. Farmers are also using drones to control the fields and plant growth. Images captured by these drones are used to collect information about the entire farm area, hence create a detailed digital map for better administration. For livestock farming, microchips and sensors measure the movement patterns of animals, body temperature and other vital data. For cows, analyzing data not only monitors the health of cows but also help to determine the time for insemination.
Uses of Big data in smart farming can be analyzed from the below-mentioned use cases.
Yield Production
Yield production uses mathematical models to gain insight around the weather, yield, chemicals, leaf, and biomass index along with machine learning which crunch statistics and enhance power making decisions. Predicting yields this way allows the farmer to have an insight into the kind of plant and its location to be planted.
Risk Management
Better risk management is becoming more influenced and enhanced by connected devices and the algorithms it uses. Farmers can leverage big data to evaluate the chances of uncertain events like crop failure, drought, the shift in weather patterns and other calamities. Feed efficiency within the production of livestock is enabled by leveraging big data.
Food Safe And Prevention
The modern-day farming is well equipped to handle and instantly detect microbes and incidents of contamination. Collection of data which centers on temperature, humidity, chemical proportion paints a complete picture of the health of smart agricultural business. Earlier detection helps to lower cost and also reduce wastage.
Operational Management
The role of big data cannot be underestimated in aiding different aspects of everyday maintenance of agricultural land. Sensors in the vehicles provide a lot of data which can assist in fleet and equipment management, leading to reduced downtime and increased productivity.
Big data will alter the future of agriculture. It will weed out problems that are bedeviling the sector. Big data will be to quickly discern patterns that humans cannot, make predictions more efficiently and recommend better policies. The power of technology will decrease the spirals of obstacles and usher in an era of e-agriculture.
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