Wireless Sensor Networks (WSN) are the technology that enables efficient and cost-effective Precision Agriculture (PA). Before PA, farmers were only able to make use of aircraft and satellite imagery, or other map-based systems, to precisely target their growing areas. Precision Agriculture provides the benefit of real-time feedback across a range of site and crop variables. As one would conclude from its name, Precision Agriculture gives detailed information not only in the size of the monitored crop area, but also in the delivered amounts of fertilizer, water, and so forth. PA technology can identify one plant for nurturing and monitoring just as easily as an entire area measured in hundreds of square feet.
The collection of data, monitoring, and application of materials to the crops results in lower costs and higher yields, with less harmful effects on the environment. Each targeted location is only given what is necessary for its growth, at the right time, and for the most appropriate duration. The WSN used in agriculture is very much like those used in Industrial Controls, Security Systems, Building Automation, and other industries. The required components of a WSN system are a centralized control unit with user interface, power elements, communication gateways and routers, and most importantly, sensors.
However, unlike other systems, Precision Agriculture requires that a unique software model be used for each particular crop or plants, soil type, and geographic area. This unique software model means that each location receives a customized, ideal amount of fertilizer, water, and pesticide.
In general, it is recommended that data collection be done hourly. More frequent monitoring does not provide any further useful information and has the drawback of burdening the WSN with excess data transmission and power consumption. On the other hand, less frequent monitoring can be useful in areas that have very uniform stable climatic conditions or with certain slow-growth crops.
A general Agricultural application can be utilized in:
- Animal tracking
- Large crop area monitoring
- Studies of biomass
- Forest / vegetation monitoring
- Forest fire prevention
- Crop yield improvement
Even though agriculture is traditionally considered to be land-based, the ideas analyzed here are also useful with respect to water and underwater ecosystems. For instance, a WSN can be utilized in monitoring algae growths and kelp beds. Water temperatures for marine plants is often as important as air temperatures for farms. A similar comparison can be made between pH and sunlight levels
WSN sensors can be used to track the following variables:
- Soil moisture
- Carbon Dioxide (CO) Gasses
- Barometric pressure
- Soil acidity / pH
Data from the sensors are incorporated by the modeling software in a feedback loop that activates the Control Network. This generates the ideal amounts of agricultural inputs to each individual location at the respective appropriate times.
The Control Network is responsible for:
- Water Pressure
- Valve / Irrigation Operation
- Animal Control (i.e. opening and closing gates)
- Pesticide Dispersal
- Fertilizer Dispersal
- Heating / Cooling
- Sunlight / Shading (typically in an enclosed growing area, such as a greenhouse)
As the costs involved in purchasing communications infrastructure and sensors continue to decrease, more farmers are choosing to implement Wireless Sensor Networks in their operations. This trend is particularly noticeable in urban farms and micro-farms. In both of these situations, crop yields are of utmost importance as farmers are likely to have particular space requirements and very small areas for their production. In some situations, farming is being done using 4- to 8-foot-high trellises on highrise rooftops or next to residential housing.
Because WSN technology allows for monitoring and targeting of each specific crop, Precision Agriculture is extremely practical and cost-effective to implement in any growing area. Such an approach can also scale easily using additional communication hubs and sensors.