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Information Science, Meteorology and atmospheric sciences, Communication engineering and systems, Computer hardware and architecture, Environmental and geological engineering, Remote sensing, Agriculture, Soil science, Environmental sciences (social aspects, Transport planning and social aspects of transport
In horseracing, “the going” is a term to describe the racetrack ground conditions. In Ireland presently, a groundskeeper or course clerk walks the racecourse poking it with a blackthorn stick, assesses conditions, and declares the going – it is a subjective measurement.
This thesis will propose using remote low-cost soil moisture sensors to gather high frequency data about the soil water content in the ground and to enable informed decisions to be made. This will remove the subjective element from the ground hardness, and look at the data in an objective way.
The soil moisture sensor will systematically collect high frequency data from the ground and store the data in a remote database using Internet of Things (IoT) technologies such as Message Queuing Telemetry Transport (MQTT), InfluxDB and Node-RED. The database will hold soil moisture readings, their timestamp and GPS location. From this data and data from an industry-standard Clegg hammer, the soil sensor will be automatically calibrated for the soil that it is sitting in regardless of the soil make-up, the sensor model, and the drainage of the soil.
The going of the soil will also be deduced. The primary soil saturation data is fused with secondary open source weather data. Weather forecast information is gathered spanning out 3 hours, 24 hours and 5 days, and estimates can be made regarding how the ground will behave. These estimates are automatically update every 3 hours. The data will also allow decisions to be made for irrigation planning.
Finally, the data will be visually displayed in real-time enabling a clear view of the soil moisture, current ground hardness, the going, rainfall and their forecasts. The system will propose how conditions will change if irrigation is applied.
McKeon, A.M. (2019) 'Predicting the Hardness of Turf Surfaces from a Soil Moisture Sensor Using IoT Technologies'.