Smart farming improves yields, saves energy.

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The first crop of agricultural IoT improved livestock training, environmental monitoring and the supply chain. Below are five picks from IoT’s latest harvest.

Precision agriculture, which tackles the wastage in farming due to its many variables and their unpredictability, will be worth $4 billion to the global economy by 2018, says analyst Informa. Here’s how the IoT manages the risk and the environmental impact from crop inputs. 

1. Yield estimation

Currently, many farmers estimate the value of this season’s crop by getting a laborer to walk along the rows of fruit and vegetables counting each by hand. In today’s large farms they often count a small sample then multiply that to get a rough estimate. However, this is on average only 60 percent accurate, according to Agridata.

Agridata uses ‘computer visioning’ to count the grapes, apples and nuts grown by its clients, with over 90 percent accuracy, it claims. The artificial intelligence software examines images collated automatically by cameras embedded in drones. These create more accurate estimates and come earlier in the growing season too, so the business can adjust its costs.

Farmers have a better idea how much they will be able to sell each season. The crop quality improves too because the earlier arrival of intelligence means they can prune the trees at the best times in the growing season. Agridata claims its clients’ profits increase by a quarter as a result.

2. Energy and water

In the wine industry, different grape vines have different requirements for water, depending on the kind and quality of wine that will be produced from them. For example, pinot noir grapes like different soil and moisture than chardonnay but both can be grown, in adjacent plots, if the farmer is able to manage the growing conditions.

Water and energy are the biggest costs for crop growers. Wexus reads energy meters and water flow sensors to help growers to manage these expensive variables. The feedback from the electricity meters is used to calculate automated decisions on actions that will cut energy costs. These vary from moving to an optimal rate plan to reporting on the least efficient water pumps that could be profitably replaced. In California, Jackson Family Wines was alerted (by an algorithmic analysis) that a pump was likely to fail in two days. Averting this crisis saved the crops served by that pump from dehydration. Automatically triggered irrigation saves on labor costs too. 

3. Guided tractors

As tractors plough or cut rows of corn, wheat and soy they can be harnessed as data collectors. Combining the data from a seeder (like the volume of seed planted in each square centimeter of the field) with a sprayer (the volumes of fertilizer, pesticide and herbicide) and a harvester (the crop volumes) allows the FarmMobile management system to calculate yield management much more accurately. Now growers can see the cause and effect of, say, fungicides on total yield. 

Farm machines can be GPS guided and nearly autonomous too. The farmer now monitors the tractor’s driving, which tends to be more precise. Machines don’t overlap their last pass, like human drivers do, which saves up to 30 percent of fuel costs and chemical inputs.

4. Internet of cows

Cattle tracking system Stepla fits herds with sensors that report on their location and movements. Aside from alerting farmers when their livestock have strayed, analysis of their movements can identify behaviors related to certain conditions. Cows move differently when they are in heat or when calving, for example, and protracted periods of inactivity indicate sickness – or worse. These are all critical conditions that need instant resolution and the IoT both improves breeding schedules and saves lives through its early warning of dangers. When combined with external harmonized data, such as weather and air quality, it provides the farmer with information on how local conditions may impact livestock.

5. Drones and robots

Agritech company Monsanto plans to help eliminate 100 million tons of greenhouse gas emissions from US agriculture by 2030 by using “carbon-smart farming practices”.  Among the agritech disciplines applied are advanced robotics, sensors and artificial intelligence which guide and apply pesticides. Microwaves and lasers can be used to destroy pests without the use of pesticides.

Remote sensors monitor conditions in the field through color and infrared aerial photography, satellite imaging and radar sensing to create images and maps. When combined with robotics, drones can be used for applying pesticides. Arysta LifeScience, Vegetech and MC-Clic have developed an application to control red palm weevil pests in palm trees whereby a micro-granular formulation of the bio-insecticide Beauveria bassiana (a fungus) is applied by drones. Drones solve the problem created by the height of palm trees, which make them difficult to access.

Read about how Orange helped Dacom improve agricultural yields with IoT. And find out more about the range of IoT services offered.