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dc.contributor.authorSallis, P
dc.date.accessioned2011-08-04T23:04:36Z
dc.date.available2011-08-04T23:04:36Z
dc.date.copyright2011
dc.date.issued2011-08-05
dc.identifier.citationKeynote address at the 5th International Conference on Mathematical Modelling and Computer Simulation. Manila, Philippines, 24-26 May, 2011
dc.identifier.urihttp://hdl.handle.net/10292/1580
dc.description.abstractThis presentation describes an international research collaboration relating to micro-environment data monitoring and modelling for applications in agriculture. The particular area of agriculture in focus at this time is grape crop production. In viticulture, timely and accurate environment impact information is critical for decision-making precision. Climate in particular, plays a significant role in determining crop yield and quality. A fit-for-purpose wireless sensor network (WSN) terrestrial telemetry architecture is described together with a description of its implementation from concept, through design and development, to deployment in the field. Details of the sensors, their calibration and testing will also be provided. The sensor arrays are housed in a framework with their own (solar) power supplies, GPS, Wi-Fi transmitter and micro-computer for in situ signal processing and data communications protocol processing. Data is passed from individual sensor arrays at parameterised intervals through a coordinating node (a gateway) to an Internet enabled upload process to a central server. This server acquires data from all the international locations. Monitoring software on the server provides immediate real-time reporting to each location while also populating a ‘public’ website, which illustrates analysed data in terms of actual and trend information. This information system and its use is outlined. Processing the monitored data for a variety of purposes requires geostatistical analyses and mathematicalmodelling. Some data is interpolated (using inverse distance weighting, kriging, etc) for use with GIS applications (some examples will be given) and in the case of estimation or prediction of single data values or events, models with more sophistication such as the ensemble Kalman filter (EnKF) are used. The real-time monitoring system and web-based information system are designed for use by decision-makers. Some examples of this information being used by crop managers will be described, as will some research projects underway by members of the international scientific team.
dc.publisherAUT University
dc.titleSensing instrumentation for micro-environment data management
dc.typeConference Contribution
dc.rights.accessrightsOpenAccess


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