Actas de congresos
Ad Hoc Wireless Sensor Networks Applied To Animal Welfare Research
Registro en:
9781892769688
Livestock Environment Viii - Proceedings Of The 8th International Symposium. , v. , n. , p. 1009 - 1012, 2008.
2-s2.0-63149109603
Autor
Cugnasca C.E.
Saraiva A.M.
Naas I.D.A.
De Moura D.J.
Ceschini G.W.
Institución
Resumen
Ad hoc Wireless Sensor Networks (AWSN) are arrays of miniaturized electronic devices that embed sensors and have communication capabilities that allow them to interconnect using a radio network. They are available with different technologies, configurations, and sensing capabilities, and can be used on different network topologies. As an AWSN is composed of a large number of compact low-cost and energy-constrained sensor nodes, it offers unprecedented flexibility and mobility, which makes them suitable for environmental data acquisition in the field, and allows fine-granular observations. The sensors are easy to deploy and can be used to detect previously unrecognized relationships and behaviors in natural systems, which cannot be detected by conventional approaches. In many cases, power consumption is still an issue. Research related to biological and environmental systems can be enhanced with AWSNs. Monitoring and control of the quality of indoor environment is very important for animal health and welfare and directly impacts productivity and quality. The goal of this work was to evaluate the capability and usefulness of an AWSN in studies related to animal housing environment. An AWSN has been set up and applied to monitor environmental variables in an animal housing facility. The network is composed of several sensing nodes and a gateway that links the network to a microcomputer. They were distributed over strategic points inside an animal housing facility to allow us to collect data about those environmental variables in real time. The inherent flexibility and mobility of the nodes allowed us to move them through the facility to determine different profiles of temperature, humidity and luminosity across the facility. Model based on this data can be derived to enhance animal welfare.
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