Smart Farming Big Data

Report: Smart Farming Can Make Food Supply Uncertainty and Volatility a Thing of the Past

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“We have observed a new momentum and a more powerful encounter between the Internet of Things (IoT) community and the agricultural sector [in the past year],” reads a new report from Beecham Research entitled: “Smart Farming: A Sustainable Way to Food.” The report makes a strong argument for smart farming to make the uncertainty and volatility of our food supply a thing of the past.

Smart farming is the use of digital technologies on the farm to help farmers manage their operations more reliably and efficiently, largely through precision agriculture. These technologies can be applied to almost all farming activities including vehicle tracking on arable farms, livestock monitoring, indoor farming, greenhouses and stables, fish farming, forestry, water, grain and fuel storage monitoring, among others.

There are a few core digital technologies used in smart farming that include satellite and drone imagery, sensors, algorithms, robotics, wearable technology, GPS mapping, farm management software and cloud computing.

These tools combine data and analytics to give farmers detailed insights about how their businesses are operating, often providing recommendations for how to make improvements, from when to harvest to how much fertilizer to apply at different points in the growing season, to where cost savings could be made.

In the United States, there are already several good examples of smart farming in use on large farms and companies like John Deere, Trimble, and Valley Irrigation have smart farming products on the market where the potential impact is already evident. For example, John Deere’s automated guidance system for farm equipment — which helps farmers to more accurately perform field activities such as harvesting — can decrease farmers’ costs by 10% because they reduce the amount of overlap they drive, reducing input costs such as fuel and increasing efficiency.

There are challenges for smart farming, however, such as internet and wireless connectivity issues, a slow-to-adopt population and hazy rights and rules around data, but the report is optimistic that smart farming is on the way to becoming an essential part of commercial farming operations.

We caught up with Saverio Romeo, a principal analyst at Beecham Research, to find out more about the report’s findings. Romeo runs research in the areas of machine to machine (M2M), IoT, IoT policy, and wearable technologies. He is a visiting fellow at the Centre for Innovation Management Research and guest lecturer on the IoT at the Department of Informatics at Birkbeck University, London.

His interest in applying broadband and mobile solutions to rural communities comes from tinkering on his grandfather’s farm in Italy. We asked him to drill down on the practical applications and timeline for smart farming globally.

The report makes a compelling case for data-enabled or smart farming in outdoor settings. Where is the field right now in being able to analyze and use the data that has been collected? Is the closed nature of this data, now that smart farming is a business and not just an academic pursuit, going to slow or hasten progress in this field?

Firstly, smart farming has never really been an academic pursuit. Instead, the role of universities has been pivotal in moving from proof of concepts to products and services ready to be deployed. There are plenty of examples in the UK and elsewhere.

The report makes a compelling case for data-enabled farming because data is the essence for understanding farming activities, predicting conditions, taking decisions. Without data, we will not talk about the Internet of Things (IoT), and we will not talk about smart farming.

Finally, the progress of smart farming applications can be hampered primarily by the lack of investment in them, and also the lack of a narrative that can demonstrate the positive effect of smart farming with examples. But, I think we are overcoming those barriers. The evolution of smart farming will not be homogenous per geography and per application, but we are on a good route.

Which crops and uses do you see being the quickest adopters of smart farming techniques?

The report provides several examples. It is not about crops being quick or slow adopters, but it is about the investment capacity of the farming community. Precision agriculture meant as connected agriculture vehicles has been around for some time and it is evolving. We see several activities in horticulture spread among different crops, plants, and topographies. Precision livestock is moving. Smart fishing is also there.

Do you think that entrepreneurs in the space are adequately accounting for the advanced age of the average farmer in the developed world when making their products? What other concerns must smart farming startups consider about their end customer?

Not much can be done about farmers’ age – but more and more people working in farm back offices will be IT and data management savvy, and need not be farmers. Smart farming is also becoming an incentive for the creation of a new generation of smart farmers. That requires time, but we can see a return to farming encouraged by the application of IoT technologies in farming.

There is strong attention from the investment community on agri-tech start-ups. That is good, but let’s not create hype or easy enthusiasm. The farming sector is very often low margin, and therefore keen for new ideas to improve that margin. Speak easy, speak farming language, avoid complication, and offer plug and play solutions. In order to do all that, business feasibility assessment of a smart farming idea is compulsory.

You make a strong point in your report that digital infrastructure, even in rural areas of developed countries, is lacking and therefore hampering the growth of smart farming technologies. Are there countries or areas working to build this infrastructure now? Can this nascent industry mature given the state of internet access in rural communities in Europe and the US?

Yes, connectivity is an issue for the adoption of smart farming applications. It strongly depends on the application you want to deploy. If you are looking for a data-rich application, the problem could be that 3G-4G is not reliable. Satellite can be an option. If you are deploying low-data application – and in farming, there are quite a few – LPWAN (Low Power Wide Area Network) can be a good alternative. The LPWAN community is dedicating a lot of attention on agriculture. LPWAN can overcome the issue of coverage and expensive connectivity costs enabling the deployment of several smart farming applications.

Providing high-speed connectivity in rural areas can be more challenging. This can be driven by government initiatives, and there are some of them in place. It also can be driven by proven business models. It can be provided by mesh networks. Fiber Optics is sometimes available in villages and small towns, rural wireless access can be then deployed towards the farms.

There are several options for making rural connectivity reliable and ready for smart farming. Government forces and market forces can together use those options.

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