Digital Transformation for Agriculture
Reducing inputs and optimizing outputs through data driven decisions
Planting the Seed for Innovation
Agriculture has long been an essential industry to the global economy. With the emergence of precision agriculture and vertical farming, the industry is poised for rapid growth. Through intelligent sensors and data analysis, your agriculture operations have the opportunity to drastically improve outputs while heavily reducing the amount of input resources required.
Problems Our Customers are Facing
A vast majority of the agriculture companies we work with face the same day-to-day problems:
Inefficient use of inputs
Many of our customers are concerned with the amount of resources they are using in their agriculture practices. Without an accurate way to measure how much water, fertilizer, etc. is needed, it is difficult to reduce costs and operate efficiently.
Human decision making
Much of the traditional agriculture process involves farmers manually making decisions, which can be time consuming and lead to costly human error.
Lack of data to improve processes
With only minimal amounts of data, it makes it hard to pinpoint exact areas for improvement in the agriculture process and minimizes the capabilities of advanced analysis to streamline activities.
Steps Towards Your Facility’s Digital Transformation
Data acquisition is required to begin any digital transformation in agriculture, with reliable data being essential to facilitating each of your subsequent transformation stages. Deploying sensors throughout your crops is an important first step. These sensors can be any type that will benefit your overall efficiency and precision, such as temperature, humidity, moisture, pH, and more. The sensors will allow you to gather data on the levels of each variable in question, and ultimately drive further analysis, prediction, and data driven decisions.
With a network of data collection devices deployed, you will require a method for aggregating the data to one centralized software system.
In the Agriculture industry, locations can range from highly remote countrysides to inner city closed facilities. Therefore, the technology for aggregation can vary greatly. WiFi 6 is excellent for inner city locations that can easily connect to a WiFi network, whereas LTE is the best option when WiFi is unavailable. For remote, large scale farms/facilities that spread hundreds or even thousands of acres, a more advanced LTE Mesh network is an ideal solution. If you are operating in more extreme remote locations, Satellite is the best choice as it can cover network connectivity virtually anywhere in the world. Regardless of the best communication system for you, all data is aggregated to our Systems Quality Control (SQC) interface where you can control workflows, visualize the data, and manage any day-to-day tasks and assignments.
Analysis is another important stage in the digital transformation process, in which advanced analysis models can be applied to your data.
Artificial Intelligence, Machine Learning, and Deep Learning can all be applied to the data you are gathering in order to make decisions. This includes various applications, such as analyzing moisture levels in real-time to make sure you are adding the perfect amount of water without wasting excess amounts. Taking the analysis to the next level by applying Machine Learning and Deep Learning allows your processes to continuously improve upon themselves by adjusting inputs to yield the highest quality output at the most efficient use of resources.
The final step in the transformation of your agriculture processes is to turn the analyzed data into actionable communications from either Machine to Human (M2H) or Machine to Machine (M2M).
M2M communications are effective for real-time action. For example, if your moisture sensors detect low moisture in the soil, they are able to communicate to a sprinkler system that will immediately disperse water until the soil has reached an ideal level of moisture. Hyper-spectral sensors are able to communicate via M2H by the sensors determining when a plant is at its optimal condition for harvesting, and sending an alert to your team.
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