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	<guid isPermaLink="true">https://www.scipedia.com/public/itinerantes._Ahumada_Hernandez_2025a</guid>
	<pubDate>Thu, 28 Aug 2025 18:36:44 +0200</pubDate>
	<link>https://www.scipedia.com/public/itinerantes._Ahumada_Hernandez_2025a</link>
	<title><![CDATA[GANADOGO: APLICACIÓN MÓVIL PARA EL CONTROL Y GESTIÓN DE GANADO MEDIANTE GPS Y GEOREFERENCIACIÓN]]></title>
	<description><![CDATA[<p><strong><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">GanadoGo</span></span></strong><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;"> es una innovadora aplicaci&oacute;n m&oacute;vil dise&ntilde;ada para optimizar la gesti&oacute;n ganadera en el municipio de Sampu&eacute;s, Colombia. Mediante la integraci&oacute;n de geolocalizaci&oacute;n GPS y dispositivos micro:bit, la aplicaci&oacute;n permite el seguimiento y monitoreo del ganado en tiempo real, mejorando el control y minimizando las p&eacute;rdidas. La implementaci&oacute;n de GanadoGo representa un avance significativo en la eficiencia productiva, el bienestar social y la sostenibilidad ambiental. Este proyecto apoya el desarrollo rural y econ&oacute;mico de la regi&oacute;n, en consonancia con los planes de desarrollo nacionales y sectoriales, a la vez que mejora la seguridad alimentaria, promueve la inclusi&oacute;n social y fomenta el uso responsable de los recursos naturales.</span></span></p>]]></description>
	<dc:creator>Helmer Ahumada Hernandez</dc:creator>
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	<guid isPermaLink="true">https://www.scipedia.com/public/Du_et_al_2023a</guid>
	<pubDate>Fri, 06 Oct 2023 20:56:04 +0200</pubDate>
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	<title><![CDATA[Research on Personalized Tourism Recommendation Algorithm]]></title>
	<description><![CDATA[<p>Project recommendation plays an important role in tourism management. It can not only promote the overall development of tourism, but also improve the satisfaction of tourists. However, in the process of tourism recommendation, there are some problems, such as insufficient personalized recommendation, low satisfaction with recommendation, inaccurate recommendation and so on. Therefore, this paper proposes a personalized tourism recommendation algorithm based on remote network control technology, which classifies the tourism needs of different groups and summarizes the data. On this basis, the tourism resources database is constructed, and the tourism resources are numbered. Combined with map list, real-time location of tourists, weather conditions, traffic conditions and other information, it provides tourists with more accurate and practical tourism recommendation services. Finally, through remote network control technology, the matching of tourism resources and demand can be realized, and the accurate transmission of personalized recommendation data can be ensured, and the recommendation algorithm can be promoted. The research results show that under the remote network control technology, personalized recommendation algorithm can improve the matching rate of all tourism resources, realize the rational development of tourism resources, and meet various needs of tourists.</p>]]></description>
	<dc:creator>Dongshu Cheng</dc:creator>
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	<guid isPermaLink="true">https://www.scipedia.com/public/Ghaffari_2019a</guid>
	<pubDate>Sun, 21 Jul 2019 16:01:04 +0200</pubDate>
	<link>https://www.scipedia.com/public/Ghaffari_2019a</link>
	<title><![CDATA[Providing a new scheduling method in fog network using the ant colony algorithm]]></title>
	<description><![CDATA[<p>Fog computing provides reliable computing, customized and by guarantee dynamic environments for the end-users, so that more and more people tend to use fog environments every day in their workplace. Virtualization is an integral part of fog. The purpose of using fog computing systems is to minimize the cost of using a virtual machine by service providers and also to maximize revenue from providing service to consumers&#39; applications. Scheduling is a process that considers several parameters simultaneously to optimize the execution of requests in fog computing networks, such as the queue duration of requests and the speed of virtual machine, and the priority of requests, and these parameters result in the success or failure of a request on virtual machine. In this study, we provided a new method of scheduling using ant colony algorithm, which can perform scheduling and execution of tasks with higher quality.</p>]]></description>
	<dc:creator>Elham Ghaffari</dc:creator>
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