Combining IoT and Predictive Analytics in Agriculture

The Agricultural sector is moving towards data-driven transformations. Farmers and traders are moving towards technological advancements, adopting data analytics and smart farming technologies.

Issues in Agricultural Business

One of the most important and great pain points in agricultural business is to predict events that will show the results.

There is a great pressure on the farms that are within the markets due to rising production costs.

According to UN DESA report, the global population will be approximately 9.7 billion by 2050, up from 7 billion at present adding great pressure to the market.

Simply increasing the land cannot be a feasible solution for many farmers to grow more crops. Hence, technology plays a vital role in making the better use of available space.

How IoT and Predictive Analytics can solve the problems

Data can be collected from these agricultural businesses thereby leveraging technological innovations for better surveying.

With the help of IoT devices we can analyse the status of the crops by the capturing real time data from the sensors.

By collecting data from the sensors and applying predictive analytics we can get insights that help to make better decisions related to harvesting.

Conclusion

With the growth of population at a rapid pace could mean that every agribusiness needs to increase their productivity over the next 35 years and hence with the help of predictive analytics even the most specific problems can be matched.

In the era of smart agriculture, IoT and Big Data Analytics can help power efficient operations around the world. Combining IoT with analytics in agribusiness can help get accurate predictions for market and crop conditions thereby increasing their yields and profits.

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