Several drone startups emerged in recent years with the idea to deploy flying cameras and other sophisticated sensors that can collect data ranging from crop health or plant disease to real-time livestock monitoring.
The company’s AgroScout Sky app does the rest by integrating data collected by drones using AI technologies like deep learning and computer vision to autonomously detect, identify, and monitor diseases, pests, and other agronomic problems in field crops.
Its PrecisionAnalytics Agriculture platform then leverages machine learning and computer vision to monitor crop health and yields, as well as to produce several analytical reports.
The company specializes in monitoring the health of orchards and wineries by blending aerial imagery from drones and satellites using machine-learning algorithms for the early detection of pests or diseases.
However, the business case for near real-time geospatial intelligence – turning space-based imagery into actionable data using AI – has become strong enough to convince investors to pour loads of money into pure-play satellite startups like Satellogic.
Satellogic’s AI platform then turns images into data layers for various applications, such as identifying and counting objects like trees, detecting changes in a forest to prevent illegal harvesting, and predictive models in agriculture and forestry.
Ever-cheaper imagery from both drones and satellites, combined with the object- and pattern-detection capabilities of AI, are helping power the new era of agriculture.