Data analytics solutions transformed the farming industry

data analytics solutions

Agriculture is the world’s largest industry! As smart machines and sensors crop up on farms and data grows in quantity, farming processes become increasingly data-driven. Rapid developments in data analytics solutions, Internet of Things (IoT) and cloud computing is propelling the industry forward.

With the development of data analytics solutions today, we can monitor farms, soil, plant activity and water levels to understand agricultural systems in a way that we were never able to before. With the use of wireless sensors, we can gather and analyse this data to discover patterns that will allow farmers to make more educated decisions that will increase the output, and ultimately, grow a better product.

Read on to see how data analytics solutions are shaping the farming industry’s trajectory.

Smart farming using data analytics solutions

Smart farming, also called the Third Green Revolution, is the innovation of the agriculture sector through the adoption of smart technologies. In the years to come, it promises to bridge the gap between the latest tech solutions and the agricultural sector – a realm that is used to relying on more traditional farming methods.

Farmers are using data to calculate harvest yields, fertiliser demand, cost savings, and even identifying optimisation strategies for future crops. Smart farming uses data analytics solutions to gather information from multiple farming practices to create algorithms that can be utilised by different farms to create a crop yield that is both fruitful and sustainable. With this knowledge, farmers will be able to better predict activity in the farm and utilise methods that are not only better for their crops but more environmentally sound.

Research predicts the global smart farming market to reach around $23 billion by 2022 and grow at a compound annual growth rate (CAGR) of almost 20% from 2017 to 2022, such as accelerated development triggered by the increasing demand for crop yield and food production with the same resources.

Monitoring and warning systems with predictive analytics

A significant risk factor in farming and agriculture is the external variables we have no control over. Pest and crop diseases, for example, can decimate entire harvests, as can natural disasters, like storms or extreme weather. Before data analytics solutions existed, it was almost impossible to predict such events.

Machine learning and algorithmic tools can be designed to factor in any number of external insights or information. Farmers can then use predictive modeling techniques to plan or act accordingly – Think weather patterns, consumer demand and even industry trends. This data will help workers in the agriculture industry understand how the surrounding world affects their business.

What should they plant? When is the best time? What earnings can they expect? Are the cost of supplies rising? How does this affect profits? All these questions can be answered using data analytics solutions.

Crop management

By using sophisticated computer algorithms to analyse decades, and sometimes, centuries of weather and crop data, today’s farmers can predict crop yields with shocking accuracy, before planting a single seed. The insight provided by data analytics allows farmers to start and harvest their crops at an optimum time, which maximises crop yields and minimises stress.

Rather than filling up an entire plot, farmers can account for the fluctuations in demand. Farmers can see how much they produced in previous years, what that meant for customers, how this affected market forces and how to improve operations going forward. They could cut excess waste by producing fewer crops for a lower demand season to complete certain objectives, like saving money or clearing space to grow alternative crops.

Thanks to recent advances in drone technology, the internet and data analytics, automation has reached staggering new heights. Farmers are using drones with advanced sensors to survey their crops, update their data and notify them of areas that need improvement. As technology continues to progress, you can expect drones to move from surveying to planting and harvesting.

Moving forward

Chemists and agricultural scientists have been analysing plant data for years, in the hopes of developing crops that can grow in any environment. Chemically engineered seeds designed with data analytics solutions may sound like a bad thing on the surface, and the news usually portrays it that way. However, seeds engineered with the aid of data analytics could put an end to world hunger.

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