There is tremendous growth in the data we can access from many sources including satellites, machinery, networked in-field sensors, Internet of Things technologies, and mobile phone apps. These data are heterogeneous in their meaning, their format and the communication systems that carry them. Collection of the data is often distributed across sizeable areas, involves third parties and multi-tiered device capabilities, and carries an ongoing risk of hardware failures.
If these rich monitoring data are going to be used to inform decisions, they must be captured, organised, and transformed using coherent and reliable methods and in ways that ensure that they can be trusted. To reach the Digiscape goal of building a variety of different agricultural and land management decision support tools efficiently, then methods are needed to combine these monitoring data with model-based forecasts and other analyses and then to provide them to decision-makers.
We are building Senaps-LAND, a data staging service that is specifically designed for land sector applications. Senaps-LAND transforms raw data into “product-ready” information suitable for Digiscape’s services and applications, and allows stored or real-time sensor data to be combined with the predictive models required by each of the Digiscape applications. Senaps-LAND is being constructed using CSIRO’s existing Senaps technology.
The science challenges / questions we’re addressing:
The project is led by Dr Thierry Rakotoarivelo.