Cattle health and behavior monitoring
Czech Republic
The local demonstrator includes facilities of the Institute of Animal Science Prague (IAS) and the Lesprojekt (LESP) company in the Czech Republic. The demonstrator´s goal is to increase the use of farm animal health and behavior monitoring systems to predict and prevent health and performance issues. The user-friendly solution based on wireless sensor nodes, cloud technologies and artificial intelligence agents will help farmers improve herd management and better understand the condition of individual animals and the herd status.
Experimental farm of Institute of Animal Science
The demonstrator aims to communicate with the management systems currently used on farms and wants to avoid complicating daily farm routines by creating another separate system.
The focus is on the following topics:
• Rumen function and rumen milieu chemical parameters (pH, ORP, temperature) are important nutrition and health indicators. University of West Bohemia (UWB) aims to develop a system that continuously monitors pH, temperature and redox potential inside the bovine rumen. The sensor system consists of wireless ruminal probe, collar device serving as a retransmitter and gateway sending harvested data to the cloud. The probes should suit both farm (disposable bolus) and research (repeated use bolus) purposes. Additionally, an application for analysis and processing of the measured values is going to be developed.
• Definition of stakeholders´ requirements for a positioning system
• Development of a system able to determine whether a cow is inside or outside the barn
• Automatic collection of positioning data
• Identification of locations of interest (e.g. feeding alley) and monitoring and analysis of behavioural patterns of the cow
• The measured data from the network of distributed sensors (cow sensors) will be collected through a wireless connectivity technology so as to allow daily monitoring of the cow parameters and simplify the adoption of this technology.
• Data will be collected by customized data feeders of a cloud-deployed SensLog system and stored, using AFarCloud common data model.
• Analytical views of the data will be computed using cloud functionality and visualised using IVIS platform and/or cartographic rules (WebGLayer or HSLayers NG libraries).
