What are the challenges of building a smart agriculture system?

Smart agriculture systems call on a variety of IoT capabilities to improve farming production and deliver new monitoring capabilities.

For large-area, more traditional farming, sensors placed within the ground may record real-time data on soil moisture, temperature and pH, while environmental sensors may record sun exposure, rainfall, wind speed, air temperature and humidity. Aerial drones may also be used for surveillance of crops and pests.

For smaller, indoor farming, LED lighting, precise control of photoperiod, and soil and environmental sensors can reduce the cost of energy and increase yields.

The challenges of a smart agriculture system include the integration of these sensors and tying the sensor data to the analytics driving automation and response activities. When integrated, the use of data analytics can reduce the overall cost of agriculture and contribute to higher production from the same amount of area through precise control of water, fertilizer and light. Smart methods allow for farming on smaller and more distributed lands through remote monitoring, whether indoor or outdoor.

To successfully deploy a smart agriculture system, consider setting up a communications network that can integrate a limited number of sensors across a large area of farmland. This will require third-party network provisioning or setting up a private network consisting of access points and uplinks to a private backhaul network, which channels all the data traffic to centralized monitoring software or an analytics head-end system.

The communications network you choose is critical due to the reliability of the network. Topology of the land, wind and rain can affect point-to-point communications technologies for some private network types. Mesh networking technology, which is used by many utility companies, is more reliable and can withstand network failures. This technology is less prone to failure due to environmental conditions, but such a network is more expensive to deploy.

Choosing sensor brands and types of sensors are typically the easiest tasks when building a smart agriculture system. Setting up monitoring and automation software packages to implement actions, such as watering triggers, alarms and notifications, will require software expertise that some agricultural experts will find challenging. For example, how often should a crop be watered? What is the minimum level of soil moisture that should be permitted before starting a watering routine? Software integration with sensors and agricultural equipment is a time-consuming activity, but also one where seasonal conditions and crop expertise need to be considered.

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