Smart farming—a term that describes the use of modern information and communications technologies to improve agricultural practices—is ushering in a new, transformative era of sustainable food production.
From monitoring soil health to geolocating cows and using machines to pick crops, smart agriculture promises to help farmers produce more using fewer resources by harnessing a range of emerging and established Internet of Things (IoT) technologies.
However, while smart farming solutions can provide farmers with the tools to improve their operations, the technologies alone won't be enough; they must be supported by the right network capabilities. Specifically, they need network infrastructure that can deliver data instantly, manage machines in real time and, most importantly, stay on pace with IoT network requirements and advancements.
How is IoT moving the needle on smart farming?
IoT technologies can simply be described as connected smart devices that can collect, process and distribute data from different environments. Sensors are key to the concept, with numerous types being relevant for smart farming applications, including weight sensors, biosensors, GPS sensors, pH and electrochemical sensors, temperature sensors, optical sensors to measure soil quality, and airflow sensors to measure soil permeability.
Sensor-enabled IoT technologies are already opening up new ways of working. One application is precision farming, a management approach that employs sensors to collect live data on the health of soil, crops and cattle. The data is used to quickly diagnose problems or adjust growing conditions as necessary.
Geolocation services and sensors are helping monitor insect infestations and track cattle and other assets in real time, helping prevent hazards and reduce losses. Solar-powered robotic devices are being deployed in crop fields to improve their management efficiency and to mitigate labor shortages by autonomously treating and removing weeds. Meanwhile, in and around cities, vertical farmers are growing crops in large warehouses using enhanced sensor systems to collect data, which is then fed through artificial intelligence (AI) algorithms to determine optimal growing conditions.
It doesn't end there. Another ground-breaking though more nascent area of innovation in this space is the development of autonomous robot crop pickers that can replace seasonal workers, often in short supply, to handpick ripe fruit and vegetables.
What IoT network requirements enable you to take advantage of these advances?
While smart farming technology is becoming more accessible and affordable to farmers, especially with the price of some sensors falling, the right IoT network requirements are needed to take full advantage of the efficiencies on offer. While what is required will vary depending on individual use cases, 5G networking, the cloud and multi-access edge computing (MEC) will be key to help bring down the cost and maximize the gains. Here are some of the network features required.
For real-time access to in-field data, network reliability is key. Delays in data processing and sharing can result in suboptimal decisions being made because they're based on incomplete information. In the context of sustainable agriculture, this negates the purpose of precision smart farming, which relies on the most up-to-date data and real-time environmental monitoring.
Seamless data storage and access
While it's possible to run machine-to-machine data-gathering and to collect and receive sensor data on a local area network, to conduct smart farming at scale, the cloud and MEC are paramount.
The cloud allows farmers to sensor-monitor hundreds of different points and create an aggregated view of the data, which can then be analyzed by AI for insights. Without the cloud, data would be fragmented and stuck in silos. This will be particularly important for farmers who want to monitor hundreds of crops or cattle assets close together or run several autonomous machines at the same time.
The increased spectrum and bandwidth of 5G enables farmers to increase the scale of data collection, facilitating massive IoT for many millions of devices all connected in a small area.
For some devices and monitoring processes to maintain safety, such as critical systems and robotics, low latency is absolutely key. In this sense, 5G—with its lower latency and edge cloud, and where computation happens closer to the IoT device—can give farmers more authority over their systems, facilitating absolute control and monitoring of autonomous devices and near-instantaneous field intelligence.
Whether edge or central cloud services are required depends on the operation. As a rule, for critical applications like deploying IoT-supported autonomous machines, the proximity of servers making decisions can reduce latency. Additionally, the cloud can make many less critical IoT applications, such as non-urgent sensing, more affordable as it shifts the processing power from the sensor to the cloud.