IoT and 5G will turbocharge precision farming

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Agriculture has been changing radically over the last 50 years. It has gained speed, greater productivity and scale, thanks to agricultural equipment that has led to more efficient cultivation of a greater amount of land. The late 19th and 20th centuries brought a series of mechanical innovations, such as tractors and harvesters. Today, a driving force behind increasing agricultural production at a lower cost is the Internet of Things (IoT). Seeds, irrigation, and fertilizers have also greatly improved production. The landscape of the field today is reminiscent of science fiction, with technology present in every corner. And the effect of this is incredible, getting much more out of each planted area.

Now agriculture is embarking on another revolution, one that has connectivity and data at its center. Artificial intelligence, big data, analytics, and emerging technologies, such as IoT and 5G, promise to increase the performance, sustainability, and resilience of rural properties. One of the great gains is the possibility of accessing production data remotely and in real-time, allowing the producer to make quick decisions, without having to wait until the end of the harvest to make adjustments.

IoT and 5G applications in agriculture include asset trackings such as farm vehicles, livestock monitoring, storage monitoring, and more. For example:

  • Livestock sensors can notify farmers when animals leave the herd so that farmers can fence them in.
  • Soil sensors can alert farmers to erratic conditions such as low irrigation and lack of acidity, giving the farmer time to reconcile the problem and produce better crops.
  • Autonomous tractors can be controlled remotely, providing significant savings in labor costs.

Monitoring plant and soil conditions is a simple use case, but it can lead to a fantastic return on investment for farmers. We’ve seen several great uses for agricultural IoT in this space:

  1. Soil moisture and nutrient sensor.
  2. Control the use of water for optimal plant growth.
  3. Determining customised fertiliser profiles based on soil chemistry.
  4. Determining the ideal time to plant and harvest.
  5. Weather conditions report.

It turns out that most IoT networks today do not support image transfer between devices, let alone autonomous image analysis, nor can they support high enough numbers and density of devices to monitor large fields accurately.

The distance the data needs to travel has a huge impact on the type of technology that should be used. If you measure something 10 meters away, you wouldn’t use the same technology as you would for something 1,500 meters away.

For short distances, you can use radio frequency identification (RFID) or near field communication (NFC), which is common in mobile phones. NFC or RFID can be used if you are labeling a bag of feed and need to know how many kilos of soya is in each bag.

If you are sending data to an object 10 meters or more away, Bluetooth or Bluetooth Low Energy (BLE) may be good options. A good example of this would be engineering a Bluetooth ear tag for pigs living in a small area, which would tell the end-user the pigs’ ages and important information about them.

If your application needs to send data over hundreds or even thousands of meters, you can look into low-power long-distance network (LPWAN) options.

More recently, narrowband Internet of Things (NB-IoT) and 5G have entered the scene to address bandwidth and connection density issues.

While mobile networks are already deploying many of these ICT technologies to deliver the aforementioned agricultural benefits, 5G will increase the impact of collectors due to low latency, high bandwidth, and support for many sensors communicating simultaneously. When combined with image recognition, satellite remote sensing, and big data, for example, 5G enables the automated operation of multiple unmanned agricultural machines to cover the phases of plowing, planting, and crop area management.

High-resolution images and video, taken by drones and autonomous vehicles and transmitted in real-time, can increase the protection of livestock and crops.  With its higher data transmission rate, lower latency, and the ability to connect numerous devices, 5G not only increases the speed and accuracy of data transmission but also improves the accuracy and stability of drone and robot control. Together with AI and the cloud, the fifth generation is driving precision agriculture and smart farm management.

In Brazil, producers in Rio Verde, in the interior of Goiás state, are already experiencing this revolution, thanks to a project by FAPEG (Fundação de Amparo à Pesquisa do Estado de Goiás), in partnership with Claro and Huawei. The foundation is contributing know-how and agricultural applications. The operator, in turn, is in charge of installing the 5G network, built with products from the Chinese company, which is also providing cloud and AI solutions.

5G, cloud, and AI are improving efficiency and reducing farmland inspection time from a week to an hour. Analysis of planting areas can reduce the use of fertilizers, pesticides, and herbicides. Smart irrigation systems help ensure proper irrigation in the right places at the right time.

Smart Farming

Smart agriculture is crucial for a sustainable food system and should therefore be implemented as soon as possible. It means big changes and big opportunities in the coming years. In Credit Suisse’s accounts, we are talking about possible productivity increases of 70% by 2050. The market for connected agricultural products and services could add $500 billion to global GDP by 2030.

Source: Credit Suisse Research Institute

Smart farming solutions can help save money and improve crop yields through various tools.

Drones

Agriculture could be one of the biggest potential markets for the use of commercial drones, given the large amount of land required for mapping, monitoring, and spraying.

Drones combined with advanced AI algorithms can become an efficient technique for aerial surveillance of crops and livestock, precision irrigation, planting and spraying, and identifying diseases. Drones also collect data through images or videos, which are stored in the cloud to create predictive models and guide farmers’ decisions. Data is becoming the most critical element in increasing the economic value of farms: it empowers farmers to make more profitable and sustainable decisions.

Autonomous machines

The use of autonomous vehicles increases efficiency by freeing up time and requiring less human labor. In addition, autonomous machinery reduces fuel consumption (due to more precise routing than human-operated tractors) and can be used for harvesting, planting, spraying, and other tasks that rely on sensors, GPS, and radars combined with machine learning algorithms.

It can be adapted to monitor plant development (planting, fertilising, harvesting) or support weather-related changes in the environment (debris, drought, dust, mud).

Smart irrigation systems

Precision irrigation denotes sensors that apply the exact amount of water required by the plants. This enables better yields while reducing water and electricity consumption.

In different climate zones, but particularly in the hottest ones, fertile soils are lost due to incorrect irrigation practices. Where rainfall is scarce, groundwater is pumped into the fields. The natural salts contained in the soil are dissolved and rise with the evaporation of water. These unsustainable methods have contributed to the loss of about a quarter of the land used for agriculture in the last 25 years.

Vertical farming

The United Nations estimates that urbanization will cause an annual loss of 1.6 to 3.3 million hectares of agricultural land over the period 2020 to 2030. Vertical farming – an indoor approach of controlling all environmental factors, such as light, moisture, and temperature, in order to produce more food through vertical harvesting – can help address land scarcity. We estimate that vertical farming could meet 80% of food demand in urban areas.

In addition, various high-tech farming methods for soil replacement (such as aeroponics, hydroponics, aquaponics) can help in the development of sustainable agriculture.

Today, many of these smart farming solutions are being supported by greater use of blockchain (to monitor the supply chain and food safety), IoT, and wireless technologies (to query and interpret crop, soil, or weather data).

With smart farming, farmers can grow higher quality crops and produce more and make farming more predictable and sustainable. Many organisations are already actively incorporating various technologies into their business models. In the next 50 years, the goal is to have 100% autonomous farms, which will play an important role in reducing the number of environmental problems, solving the shortage of agricultural workers, and bringing economic benefits. But for this to happen it will be necessary to solve some problems, such as unstable sensors, inefficient robots, AI applications in complex environments, and privacy and management problems brought by Big Data

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