Farming has advanced significantly from the days of horse-drawn plows and low-cost manual labor. Farming technology brings an efficiency and scale that earlier generations never thought possible.
For example, today’s farmers’ grandparents would be quite shocked to see autonomous tractors that can leave the farm, work the field and return without human intervention.
Technology is advancing beyond the whizzy hardware. It is now more about the data that arises from these connected assets. From a farmers’ perspective there is a lot of knowledge handed down from previous generations. This knowledge can be thought of as the data that is unique to that particular farm; the geology, micro-climate and other knowledge specific to their type of farming.
This data can be enhanced using simple IoT technology to collect specific local information such as soil temperature, depth of moisture, PH levels, the amount of sunlight in various parts of a field. Adding to this using other layers of publicly available or open/shared data - such as weather and climate –this combined factual information and farmers’ knowledge gives the data context that is specific to their farm.
For example, a wet winter might mean that certain parts of the farm will naturally have more ground moisture. Or, prevailing winds during the growing period might mean that certain crops behind various hedgerows grow quicker.
Over time, contextual data will help build a model of how a farm performs. This contextual data can then be used for predicting the future. Just like with weather forecasting, the farmer can start to look at risk mitigation – when to harvest for the best crop yield, or when to move the livestock to maximize grazing time.
Cost of Smart Agriculture
Farmers’ margins are low because we consumers all want lower-priced food – plus the supply chain is getting larger as the distribution network reaches further around the globe - putting demand on farmers to produce more for less.
Advances will continue with farming equipment and it will be more efficient, enabling farmers to maximize yields and reduce their operating costs. We will see advances in hardware technology, such as GPS-guided tractors that efficiently sow seeds to predefined depths depending on predicted sunlight and drainage. We will see drone-assisted livestock monitoring - such as checking for problem lambs that need medical assistance during lambing season.
But this doesn’t come cheap. Farmers will have to find the means to fund such high-end technology, to recover ROI and to keep capital expenditures down and minimize operating costs while maintaining effective margins to be competitive.
How? Maybe farming communities will combine (pun) forces and share equipment with the concept of equipment-as-a-service, or pay-per-use models to reduce the cost. Equipment manufacturers will have to help – finding new business models to help drive adoption in the advances of smart agriculture.
They will also need IoT platforms to assist with driving these new business models - for connecting high-value assets, data for usage monitoring and predictive maintenance, automated billing models and friction-less operating models, all aimed at equipment availability and utilization. These will become the major requirements to meet the new equipment subscription models.
The smartest smart farmers will be looking to data technology and analytics to use contextual data in a way that maximizes their margins, based on smart decisions based on facts. They will be – and are – farming smartly.