Intelligent sensors can be deployed within infinite agricultural applications, enabling automatic data exchange to machine learning platforms through the Internet of Things (IoT).
Deep learning technology can interpret data from sensors placed on a farm to offer real scale solutions to challenges such as plant and animal health, nutrient management, environmental monitoring or financial decisions.
Sensors can be placed directly in environments such as fields and livestock buildings to continuously monitor conditions in real-time, giving detailed insights through machine learning platforms.
Deployment of sensors is applicable to conventional challenges such as crop health and yield improvement at a real-farm scale. Producers do not have to be experts in the field to gain value-add insights into enhanced farm management.
Real-time monitoring with applied sensor intelligence allows farmers to make timely, effective decisions to safeguard factors such as crop and animal health, while reducing inputs and costs.
Sensor applications for livestock are infinitely extensible and are capable of monitoring environmental conditions in fields and buildings alongside assessing animal health and behaviour through GPS collars and tags for improved livestock management.
Enhance crop yields through sensor deployment in arable fields to monitor and analyse factors such as weather conditions, growing environment, nutrient and water availability for informed management to achieve maximum harvests.
Improve sustainability through the deployment of environmental sensors to monitor soil health, air and water quality on farms to ultimately enhance the environmental quality of farmland.
Sensor technology is uniquely scalable for expansion and can be adapted to any current platform or agricultural application to provide real-world, innovative solutions.