Livestock health and behaviour can be tracked using GPS and accelerometer technology attached directly to the animal using collars or tags, while crop health can be monitored with drone imagery analytics and field sensors.
Advances in animal monitoring enable animal health and behaviour to be analysed continuously in real-time to ensure that poor health, illness or disease are quickly diagnosed and resolved.
Closely monitoring animal health using collars with smart interpretation of data using artificial intelligence enables real-time monitoring of livestock. Alerts are sent to the farmer to resolve any problems, ultimately improving welfare with improved management.
Real-time monitoring can detect early symptoms of livestock illness through analysing patterns of movement and behaviour. Crop disease can be detected through sensor monitoring of symptomatic environmental conditions or through detailed drone image analysis.
Improved health of both livestock and crops ensures optimal performance and growth, translating into enhanced farm production.
Sensors can be placed in environments or directly onto an animal to transmit data automatically. This data is then interpreted through machine learning platforms to provide effortless, intelligent insights into plant and animal health.
Artificial intelligence and applied machine learning optimise data interpretation from sensors, translating thousands of data points into a readable, informative structure that gives value-add management insights for farmers.
Increase production and enhance harvests through improved plant health and nutrient management. Sensor monitoring and analytics allow farmers to assess growing conditions while drone imagery enables targeted action on nutrient and pesticide applications.
Machine learning platforms provide advanced management tools such as intelligent data, monitoring and alerts for farmers to easily promote and improve livestock and crop health at the touch of a button.