<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Panagiotis Stamatis</style></author><author><style face="normal" font="default" size="100%">Christos Goumopoulos</style></author><author><style face="normal" font="default" size="100%">Achilles Kameas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using ubiquitous computing technology to realise scalable intelligent agricultural environments</style></title><secondary-title><style face="normal" font="default" size="100%">In Proceedings of the 3rd IET International Conference on Intelligent Environments(IE07)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">AmI</style></keyword><keyword><style  face="normal" font="default" size="100%">machine learning</style></keyword><keyword><style  face="normal" font="default" size="100%">precision agriculture</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">24-25 September </style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">http://daisy.cti.gr/files/56_Using Ubiquitous Computing Technology to Realise Scalable......pdf</style></url></related-urls></urls><pub-location><style face="normal" font="default" size="100%">Ulm University, Germany</style></pub-location><pages><style face="normal" font="default" size="100%">564-571</style></pages><abstract><style face="normal" font="default" size="100%">&lt;div align=&quot;justify&quot;&gt;
Wireless networks allow the deployment of sensing systems and actuation mechanisms at a much finer level of granularity than has been possible before. This paper is focused on connecting sensor data with actuators through a decision-making layer with learning capability. The&lt;br /&gt;
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decision making process regarding the provision of agricultural resources is extended this by on-line monitoring significant plant and environmental parameters and by applying machine-learning algorithms for inducing rules by analysing logged datasets to determine the significant thresholds of plant-based parameters.
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