Prototipo de un sistema de radio telemetría de parámetros comportamentales basados en movimiento en bovinos de la raza hartón del valle en la Universidad Antonio Nariño

This study contributes to addressing the scarcity of information regarding behavioral indices in cattle, specifically in the Hartón del Valle Creole breed. In this context, a bovine monitoring prototype is implemented to transmit motion and body temperature parameters to the The Things Network (TTN)...

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Detalles Bibliográficos
Autor principal:	Delgado Arteaga, Ana Sofia
Otros Autores:	Gómez Peña, Guido
Formato:	Tesis/Trabajo de grado - Monografía - Pregrado
Lenguaje:	Español
Publicado:	Universidad Antonio Nariño 2025
Materias:	Monitoreo remoto en Bovinos índice comportamental Transmisión LoRa- WAN Remote monitoring in cattle Behavioral index LoRaWAN data transmission
Acceso en línea:	https://repositorio.uan.edu.co/handle/123456789/12510
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Descripción
Sumario:	This study contributes to addressing the scarcity of information regarding behavioral indices in cattle, specifically in the Hartón del Valle Creole breed. In this context, a bovine monitoring prototype is implemented to transmit motion and body temperature parameters to the The Things Network (TTN) and Ubidots platforms. The development of the monitoring device captures parameters that, in future advancements, will aid in classifying behavioral indices. The monitoring system is based on movement tracking, utilizing sensors that measure position, angular velocity, and acceleration of head and neck movements, as well as abrupt body movements of the animal. Additionally, it records surface body temperature. This work presents the electronic design of the proposed monitor and its integration with web platforms through the LoRaWAN communication protocol. The system is implemented under a "low-cost.approach, utilizing Arduino development boards based on ESP32 + LoRa, along with commercial sensors. The obtained data is displayed on the TTN platform for visualization. The acquisition of these data, coupled with computational algorithms, aims to infer animal behaviors associated with health issues or other stressors, providing early insights to producers and their teams. The research methodology follows a quantitative and qualitative descriptive approach applicable to testing procedures. Additionally, the correct functioning of data collection and visualization in the monitor, TTN, and Ubidots was verified.