Having spent over 12 years in the IoT and M2M space I am still amazed at how the many different industry verticals continue to leverage IoT in new and exciting ways, particularly so with agriculture. So much has changed in the world of farming. Prior to being drawn towards engineering, and not to date myself, my pre-college days were spent on a rural farm some 30 years ago. Speaking from experience, farming back then was much more rudimentary. In 1988 only 5% of farm households had computers. The degree of technology put into small farms was minimal with diagnostics and data collection limited to each individual machine, if it had any at all. Many of the decisions made were based on experience and ‘gut’ feeling. Today IoT has opened up so many doors with farming and provided insights into daily operations to allow farmers to realize both increased efficiencies and return. But how do you accurately measure the success of that since there are so many variables in a day to day agricultural operation?
To get a good insight into today’s leading edge agricultural technologies I sat down with Ron Osborne, Chief Strategy Officer at Farmers Edge; a hardware and software technology company specializing in data science, precision agronomy, GIS, soil science and sustainability.
According to Osborne, the challenge is how you define whether a system is working successfully given the definition of success is relative; relative only to the datasets that they have at the time. With today’s datasets, we are seeing that the inefficient farming of the past will need to change. Huge increases in human population and geo-political uncertainty affecting supply and demand in pricing all weigh heavily into successful food production. Coming at it from today’s standpoint, the data we are able to collect draws us to see a convergence of factors, more than ever in history, that are driving the digitization of the farm. Devices such as soil moisture probes and other soil sensors bridge the gap between science, engineering, and ecosystem modeling based on the volumes of data gathered. Machinery sensors have also played an important role in machinery efficiencies, service and supports that go into making that piece of machinery function better.
One example: provide an ability to connect every piece of machinery on the farm. Machines in the past were always piecemeal, and a farmer would pay so much per year for telematics for a specific piece of machinery, or decide that it was not really needed. This created a fragmented industry. As more pieces became connected this fueled the equipment dealer with the information required to know what to sell, what parts and piece to stock creating a more efficient service and support plan. By connecting entire farm ecosystems, machine telematics to both the farmer and the dealer it can benefit as a business management tool, and strengthen the relationship between all the stakeholders.
Osborne went on to say that in addition to using data to help farmers improve efficiency and productivity, Farmers Edge also has the technology to support buying decisions. Using independent, regional data sets from thousands of farms that integrate weather conditions, topography, soil types, yield data, and equipment performance, Farmers Edge provides unbiased insights to help growers pick the best seed and equipment for their farm. Farmers can use this data to understand which equipment and seed will perform best on their farm, how their farm is performing year-to year and comparatively to other farms within the region, and which decisions they can change to have a better outcome next season.
Access to technology such as cellular networks (that have never been available before) work hand-in-hand with both ground level and machinery level data collection. In fact, where parts of rural community do not have cellular coverage, companies such as Farmers Edge have built mesh networks backhauled to a cellular network or other technologies at the population edge.
Alongside Farmers Edge, companies such as KORE play an important role in providing access technologies such as cellular networks for farms to backhaul data. The increase in cellular coverage, reductions of SIM card costs, competitive data plans, additional infrastructure, and newer cellular technologies such as NB-IoT are now allowing many of the smaller farm and agricultural entities to leverage IoT in ways that were never before attainable. This data highway, combined with the use of data science, machine learning, data analysis at the network edge (on the machine), as well as environmental information back to the farm all in real-time will allow for smarter decisions, a clearer picture of the outcome of those decisions and an overall satisfaction that all this is making a difference in the population’s food production.
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