Bunch of cows standing in the sunset

Smart agriculture uses Internet of Things (IoT) solutions for more efficient and productive farming. Smart agriculture, also called agtech, is an integrated approach that aims to increase agricultural productivity by making farms more connected and intelligent.

Smart agriculture and more efficient farming are critical as globally we’re facing resource depletion, a shrinking amount of arable land, and an enormous, long-term labor shortage. It’s a massive task ahead of us—Food and Agriculture Organization forecasts that the world’s population in 2050 will be 9.1 billion, which will require a 50 percent increase in food production.

To that end, the agriculture industry has come up with IoT-based solutions that make for higher crop productivity, lower use of water, pesticides and fertilizer, lower food costs, reduced runoff and impact on natural ecosystems, and increased worker safety. 

There are agtech startups incorporating IoT for just about every aspect of farming—from Granular, which offers farm management software that monitors an entire farm operation with high-frequency satellite imagery, to La Ruche Qui Dit Oui, which provides e-commerce marketplaces that connect farmers directly to suppliers or consumers, without a middleman.

Person holding a drone in a wheat field
Man holding drone

Robots and Drones

Farmers deploying robotics can spend more time analyzing data and planning their operations than doing heavy labor. As more farmers use agricultural robots and drones, farms become more efficient, they produce crops of higher quality and yield, and they require less manpower.

Currently, agricultural robots are often used to harvest. They can also locate and pull weeds, monitor environmental conditions, and conduct soil analysis. Drones can be programmed to monitor plants for stress, recommend nitrogen, assess for drought, and even plant trees by firing seed missiles. They can view geotagged images from the air to gather information on plant height, count, health, disease, nutrient presence, and weeds.

Robots fitted with high-res cameras work by moving through a field, inspecting and monitoring plants or animals, and sending real-time images to the farmer’s smartphone. For example, Biocarbon's drones aim to fight deforestation by decreasing the time it takes to replant deforested land. Its drones fly over

a candidate site, collect data about the best places to plant seeds, and then launch seed pods that will grow into trees.

Arial photo of agriculture fields
Abstract image of agricultural fields shoot from drone with markers on crops

Precision Agriculture and Predictive Analytics 

Precision agriculture uses predictive analytics to automatically gather and analyze data that help increase a farm’s efficiency, production, and yield. Precision agriculture helps eliminate nutrient overuse and can reduce the overall environmental impact of agriculture while still increasing crop production yields. That’s important, especially in a world where more than 113 million people experienced acute food insecurity in 2018, and 143 million more were on the verge of it.

Predictive analytics looks at historical farm data, as well as current and predicted information, to make decisions. It requires a broad array of data about soil, climate, and crops, provided by sensors and weather stations, and uses machine learning to develop models for farmers to consider.

One example of precision agtech is Gamaya’s hyperspectral imaging technology, which uses a camera to collect information about crop-affecting factors from across the electromagnetic spectrum. It combines that with other data sources, such as satellite observations and terrestrial sensors, and then uses machine learning and AI to turn that into information a farmer can act upon.

Bunch of cows in a field
At Hologram we're Moooo-ving the needle.

Animal Data   

IoT-connected devices give farmers a leg up when it comes to monitoring their animals, even from a distance. Having access to data about animals and their well-being means farm managers can make better decisions more quickly, and that can lead to better profit.

Smart devices can help farmers monitor animals’ feed and water (and provide more when needed), location, and overall health, including fertility. Devices can alert the farmer to a potential health problem before the animal shows visual symptoms, and even advise of the animal’s GPS coordinates. Sensors send information by cellular connectivity, and then algorithms process that information and provide insights to the farmer.

Cowlar, for instance, makes smart collars for cows. A cow’s neck collar monitors the animal’s temperature, activity, and behavior, such as whether it is eating, sleeping, ruminating, or showing lameness. That data transmits to a solar-powered cow router that picks up data from all cowlars within a two-mile range. It then goes to the farmer’s smartphone.


Wireless sensors monitor crop conditions and send data to a smartphone. That helps farmers track their crops closely, even from a distance, and make quick adjustments as needed for better production and yield.

Smart ag uses various types of sensors, including location ones. Optical sensors measure soil properties using light. Electrochemical sensors determine pH and soil nutrient levels by checking the soil. Other sensors measure how compact, moist, or permeable soil is, and monitor air temperature and humidity, which can, for instance, alert a farmer to frost.

Some sensors, such as Phytech for corn, attach directly to a plant. Phytec sensors continuously measure changes in the stem’s diameter. That information is analyzed by the company’s algorithms, and the grower learns about any plant stress right away. They know whether a plant is stressed and needs water by the hour; it also allows them to save water when extra watering is not required.

Irrigation in a field

Smart Irrigation Application

Smart irrigation is a technology that makes irrigation more efficient. Areas traditionally inaccessible, for instance, can sometimes be planted and irrigated. Plants can even be watered individually, depending on need. That can save tremendous amounts of water that would otherwise be wasted by watering indiscriminately. 

Smart irrigation controllers use local weather data such as temperature, wind, solar radiation, and humidity to adjust an irrigation schedule. They can calculate evapotranspiration, the combination of evaporation from soil surface and transpiration by plants. Some systems measure moisture in the soil and transmit that reading to the controller.

WaterBit Carbon is one example of a smart irrigation sensor. The unit splits a field into “microblocks,” which can be a more extensive section of field or just a single row of plants, and it monitors soil moisture, soil temperature, plant health, and other factors. Then its remote valve controller lets a farmer manage how much water goes to different parts of the field.

Fresh food at restaurant

Next-Generation Farming 

Next-generation farming uses smart technology to increase food production and efficiency, often in places that don’t support traditional farming.

By taking advantage of agtech innovations, such as robots, sensors, predictive analytics, and AI, next-generation farming vastly changes how some farmers monitor and raise food crops. By automating much of the process, it creates new styles of farming with greater efficiency and volume of production.

Bowery, for instance, is an indoor farming tech startup growing hydroponic leafy greens in an industrial complex in New Jersey. A proprietary, automated system that controls the entire farm. Plants grow indoors in vertical systems of trays with sensors and cameras that control their water, light, and nutrient intake. The company says one square foot of the indoor farm is 100 times more productive than a same-size plot of arable land.

Key to Smart Agriculture

The key to smart farming is not only having sensors, agbots, and other machines that monitor plants and conditions. It’s also making sure everything is connected through IoT so the data gets back to the farmer, who can then use that information to more efficiently manage the crops or animals.

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