Background
Robotic technology has a wide range of applications, particularly when it is backed by a comprehensive network of sensors and data, as is the case with unmanned aerial systems (UAS). For agricultural applications, UAS-based aerial imagery can provide information about crop stress and yield and is a common tool for in-field data collection. However, UAS technology can be expensive, especially for smaller farms. UAS technology is also not suitable for continuous monitoring as is needed by applications such as automated irrigation management.
Plant stress can be extrapolated by measuring air pressure, humidity, temperature, and soil moisture in multiple applications across an agricultural field, but has not been widely explored in the field.
Invention Description
Researchers at Arizona State University have developed a system for real-time terrestrial mapping and adaptive sampling of environments, allowing for optimal environmental monitoring. This system estimates metric, semantic, and topological properties of a scene, with potential applications in fields such as agricultural and ecological monitoring. This system uses a sensor network consisting of EarthPod probes that sample physicochemical properties, and a multi-spectral 3D imaging system, are used together for data collection. This technology aims to facilitate next-generation 4D environmental monitoring, enabling the observation of dynamic changes in environmental characteristics over time in 3D.
Potential Applications
- Agriculture (e.g., farms, growers, agronomists)
- Tree mapping
- Environmental monitoring
Benefits and Advantages
- Highly accurate & probabilistic digital twins for Earth’s ecosystems
- Real-time imaging and adaptive sampling of terrestrial environments
- Advanced sensor capabilities to collect point sample measurements
- Able to observe dynamic changes in environmental characteristics over time in 3D