Big data in farming

Agriculture is a science — If we want to tackle climate change, produce healthy food at home and abroad, and feed an ever-increasing world population, then we need to approach agriculture as an issue of ecology and technology. The agriculture industry is at risk of a decade-long drought. Sure, that may sound pretty serious — but if you think about it, there’s no way to predict what that means for the future. Agriculture has long served as a fundamental component of our economy. If a severe drought leads to food insecurity and price increases, we could face a nationwide recession.

What do the following have in common: Climate change, crop shortfall, forest fires, and rising food prices? Well, according to a recent report by the World Bank, all of these problems are connected. The report identifies a “growing gap” between what it calls the “Green Revolution” (the hybrid seeds and fertilizers that boosted agricultural production from 1960s to 1980s) and what is needed to respond to today’s global food needs.

The agriculture industry is at risk of a decade-long drought. Sure, that may sound pretty serious — but if you think about it, there’s no way to predict what that means for the future.

We have about 3.5 billion hectares of agricultural land in the world, but population growth is expected to exceed 9 billion by 2050! At the same time, increasing desertification and rainfall variability threaten to decrease the amount of arable land on Earth. Certainly, we need to produce more food on less land. When the world runs out of land for food production, something has to be done. Farmers will have to produce more food in less time and space. Big Data Farming has proven to be an appealing technology which provides insights from user behaviour that can be used in agriculture (online data collection). This trend is one of the well-known Big Data Farming trends that represent a new movement that collects and analyses agricultural data using sources like social media, sensors, GPS and other online sources. These days, there’s a big shift in farming from traditional to industrial. Technology has now made it possible for farmers to feed more people with less land (and fewer resources). One way to do this is by analysing data like weather and soil conditions. This has enabled farmers to optimize their yield and make better decisions on where to plant crops and set up satellite farms which has only been possible through Big Data Farming.

Industrialized agriculture uses IoT devices to collect a massive amount of data related to food production. This data is sent to remote servers via the Internet or mobile networks where it gets analysed by advanced analytics tools. Big Data Farming is a highly mechanized process that requires precise yield projections and optimum resource management. The adoption of technologies such as internet of things (IoT), Big Data Farming, cloud computing and analytics have helped farmers to drastically improve the entire process in real time.

Need of Big Data in Farming

Big Data Farming sensing technologies are widely used for collecting data and gaining insights for developing more efficient farm operations. Although these technologies have become prevalent in the last decade, the use of sensors in agriculture is still in a very early stage of development compared to fields such as medicine and transportation.

These sensors are able to send a variety of data such as soil moisture, temperature, sunlight exposure and much more. Data collected by IoT devices can be used to make critical decisions regarding the health and yield of farm crops, in turn greatly influencing farm income and food prices. In an effort to tackle the pressing problem of feeding a growing global population, agricultural technology companies are using internet of things (IoT) devices to collect data in real time from crops and fields.

Big Data Farming is vital to agribusinesses, which rely on analytics and technology to track various inputs and outputs in their operations. Farming Equipment should be considered when making strategic business decision. Big Data Farming can provide insights about the profitability of your business and help spot patterns that could be affecting the bottom line. Nowadays, it is no longer sufficient to analyse your data on its own; you also have to compare it with other sources of relevant information. For example, you might look at climate data or other publicly available information when analysing soil variables.

Farmers are embracing Big Data Farming to automate, gather insights, and ultimately help them make better decisions. For example, smart sensors gather real-time information and share it with cloud servers where advanced analytical tools combine weather, pricing models, and operational data from farm equipment. The informed insights then guide farmers’ decisions.

Precision agriculture uses big data to increase precision—it’s all about adding value at the farm level. The features that Big Data Farming brings are computing analytics, web and mobile technologies, visualization, modelling, and simulation. Farmers could only rely on years of experience and intuition to help them decide when to plant and harvest crops. Predictive insights, in the form of soil risk analytics supported by Big Data Farming, are transforming agriculture by enabling farmers to continuously test their soil and make adjustments based on insights from their farms.

Farmers today are using Big Data Farming to help understand and predict crop maturity, by using satellite imagery, weather data and other factors. They also use this information to determine the best time to harvest their crops, deliver fertilizer or irrigation, and advise you on how to improve soil health. This allows them to lower the costs so that they can deliver a more consistent, high-quality product to their customers. Before one makes a new batch of fertilizer, run a few trials against your last harvest to see how changing the chemical mix affects yield. Our farmers do this all the time and now you can too. With information from past and present stories, soil test analyses and our global weather model, The Climate Corporation is making predictive data a reality.

How Big Data Farming Helps in Agriculture?

Feeding All

Big Data Farming is changing the world. Over 6.4 billion connected devices are already out there, and the number will reach around 20 billion by 2020. However, not all these connected devices are in the hands of consumers. One such growing segment is the industrial IoT (IIoT). With the help of many new technologies for IIoT, industries can save time and money, keep track of their processes and even optimize their supply chains and improve products.

Helping the world’s farmers improve yields is one of the key challenges that even governments are putting their heads together to solve. One way to achieve this is to increase the yield from existing farmlands while making sure that they are ecologically sound.

Improvement in the use of pesticides/pesticide administration through Big Data Farming and analytics are powerful, yet delicate. By leveraging Hadoop Big Data Farming and cutting-edge visualization tools, the efficiency of crop protection products could be greatly improved. Visualization tools include the distribution of crops by region, and regions which have the most at-risk crops to pests or weed infestation. The variations in risks for each crop over time are also calculated through Big Data Farming.

Nation-wide databases are beneficial to agricultural production. With the use of Big Data Farming, farmers can accurately schedule when and where they apply pesticides and fertilizers. This leads to increased profits because crops don’t get destroyed by weeds and insects, which saves farmers time, money and their crops.

Helps in Regulating the Resources

The challenge of governing the use of pesticides has been an arduous one. Big Data Farming, however, allows farmers to regulate the most resource-intensive phase of agricultural cultivation. With data being collected on weather patterns, interactions with wildlife and local communities, changing legislation and regulations, and even data from our own monitors on a daily basis.

Traditionally, managing crops requires heavy use of pesticides that can cause environmental damage. Farmers don’t want to lose money due to pests and weeds. Crops are more profitable when they are harvested in a timely manner, Big Data Farming helps smaller farms by improving the efficiency of their operations.

Decision Making

Cloud computing has created a surge in Big Data Farming as cloud storage enables more and more users to store data online. With the increase in available data, organizations are able to collect and make sense of a broader set of data points than before.

Now, almost every square inch of a farm is monitored from soil moisture levels to well pumps; from body temperature of cattle to solar radiation; from precipitation levels to irrigation scheduling. All this information is fed into a computer program that will help farmers direct their activities with better judgment and decision making.

With the aid of Big Data Farming and cloud computing, farmers can get a ‘real-time’ overview of their farm and thus, plan their strategy better. Big Data Farming has revolutionized farming by bringing to farmers across the globe instantaneous knowledge that could previously only be available to experts or advanced farmers. The future for farmers is looking bright as the climate of smart farming is here. Cloud-based big data along with advanced irrigation techniques will turn farming from moderately successful, to a hugely profitable enterprise. Success in farming is an outcome of information and knowledge. This has been made possible by the availability of data through Big Data Farming.

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