Technical
framework for Community action to achieve the sustainable use of pesticides) is aimed at progressively limiting or eliminating altogether the use of pesticides in EU Europe. As such, in future years, the pressure will be on golf courses to limit the use of water and pesticides. The WaterGolf system, developed with financial support by the EU within an FP7 project by the same name, deals with the optimisation of water consumption of golf courses, but also with the enhancement of their maintenance and management, by providing an intelligent system to prevent and manage turfgrass diseases, the growth of weeds and fertility problems. Artificial intelligence has been applied in the
past to precision farming to achieve optimisation in the use of water and fertilisers, amongst others. However, in the case of turfgrass, little previous work on management through artificial intelligence can be found and no current technology is available to predict the onset of turfgrass problems (weeds and/or fungi). Several systems, such as Toro, Bailoy, UgMO, ETS-Controls or Rain Bird allow computerised control of golf courses, but they do not use intelligence systems. The objective of the project was to develop a
system based on a wireless sensor network and an embedded Artificial Intelligence (AI) system that provides support to the irrigation processes on golf courses. Based on the estimations provided by the expert partners of the project, the expected impact is to save approximately one third of current annual water usage. The system integrates underground sensors,
capable of measuring soil humidity, salinity and temperature; traditional atmosphere sensors and evaposensors, capable of monitoring turfgrass evapotranspiration, in order to gauge daily water consumption by plants. The measurements are then wirelessly transmitted through nodes to the coordinating device, where the AI driven software supplies suggestions for irrigation in different regions of the course, as well as informing of potentially looming turfgrass diseases and weeds.
System Overview
The general layout of the system (Figure 1) is composed of a central server and the client software. The central server is deployed as an API which is accessible through a web-service interface, allowing other systems to monitor a golf course. Further integration, such as direct
The software supplies suggestions for irrigation in different regions of the course, as well as informing of potentially looming turfgrass diseases and weeds
cooperation with a third-party irrigation system, is also envisaged. The client software is divided into the following subsystems:
- the main dashboard, which can be used as a desktop application to manage the entire system
- the server, which is in charge of the management and processing of all data fetched from the golf course and to deal with external requests
- the mobile-device application, in charge of managing remote notifications
- the consultancy system, which is a tool for the expert consultant to remotely advise the greenkeeper
Note that a complex network of advanced
sensors is also used in the system. The sensors used are underground sensors, which gather measurements of soil temperature, salinity, humidity; evapotranspiration sensors, which determine the evapotranspiration measurements of the turfgrass; weather stations, which measure air temperature, precipitation, wind direction and wind speed. All devices communicate with one another through a wireless network, and then the gateway gathers all the required measurements. Later on, the back-end retrieves this data from the gateway.
User interfaces
The system provides the following user interfaces (front-end), mainly for golf greenkeeper use, but access can also be
”
granted to the course’s turfgrass consultant: Desktop application
This is the default client software that is used by the greenkeeper on a standard stand-alone deployment. It allows the management of the entire system through web-method calls to the server API. Suggestions and irrigation recommendations are shown in the main screen, while all complex behaviours are only revealed to an advanced and password- protected user. It is developed using a 2-tier architecture: the user interface layer (for user interactions) and the middleware layer (for communications with the back-end). It is also possible to use it away from the golf course (at home, while commuting, etc.).
Mobile application.
It is based on the desktop application, but does not fully replicate all functionalities as it is a simplified version with read-only access to current notifications and data.
Consultancy application
The system provides adequate recommendations, but there is the possibility that complex and dangerous situations appear, which require the participation of a turfgrass expert. In this case, the greenkeeper can consult a turfgrass expert. This subsystem provides the turfgrass expert with the appropriate interfaces to access relevant data, communicate directly with the greenkeeper, and maintain the system remotely by using an expert system rule editor. An advanced indexing service is also provided for accessing to documental data. The service consists of a repository of relevant documents (informative, technical data sheets, specialised, technical, scientific papers, etc.) where the consultant must be able to manage documents.
Back-end application
This is the kernel of the system and is implemented as a dynamic link library (DLL). The library exports the classes and methods as web-services. The web-services interface has been developed using Windows Communication Foundation (WCF). It can be exported using the RESTful, SOAP or
Net.TCP technologies.
Intelligent System
Figure 2 shows a general layout of the intelligent system, which is hosted in the API and retrieves sensor-derived information and
Figure 1 (left): The general layout of the system is composed of a central server and the client software. The central server is deployed as an API which is accessible through a web-service interface, allowing other systems to monitor a golf course
Figure 2 (above) shows a general layout of the intelligent system, which is hosted in the API and retrieves sensor-derived information and stores it in a database
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