Description

Background 
Animal behavior monitoring represents a class of wireless sensor network applications with enormous potential benefits for scientific communities and society as a whole. In this sense, the knowledge of the herd behavior phases (activity, inactivity) can be classified by measuring relevant behavior parameters such as the pitch angle of the neck, position and the movement velocity of the animals in the field. Such behavior classification is potentially useful as management tools in grazing and production optimization.

In order to monitor herd behavior, data relevant to their behavior should be measured, aggregated, processed and finally sent through a network to infrastructure facilities. In animal science applications, the natural mobility of the herd makes wireless sensor networks the perfect candidate for such monitoring of animal behavior parameters. The integration of local processing and storage allows sensor nodes to perform complex filtering and triggering functions, as well as to apply application-specific or sensor-specific data compression algorithms. Low-power radios with well-designed protocol stacks allow generalized communications among network nodes, rather than point-to-point telemetry. The computing and networking capabilities allow sensor networks to be reprogrammed or retasked after deployment in the field.

Aim
Researchers in the Animal Sciences are becoming increasingly concerned about the potential impacts of human presence in monitoring animals in field conditions. At best it is possible that chronic human disturbance may distort results by changing behavioral patterns, while at worst the disturbance can seriously reduce the animal production by increasing stress.

Sensor networks represent a significant advance over traditional invasive methods of monitoring. Sensors can be deployed prior to the sensitive period (breeding or calving). The results of wireless sensor-based monitoring efforts can be compared with previous studies that have traditionally ignored or discounted disturbance effects. Finally, wireless sensor network deployment may represent a substantially more economical method for conducting long-term studies than traditional GPS methods for outdoor monitoring or personnel-rich methods.

So the main goal of the project is an autonomous farm which can be monitored by wireless sensor networks. Self healing and self configuring characteristics of wireless sensor networks together with On-the-air-programming ability make the network dispensable of occasional servicing. This could also greatly increase access to a wider array of study sites, often limited by concerns about frequent access and habitability (Szewczyk et al. 2004).

Research Outline
Localization using wireless sensor network
Communication protocol: ZigBee
Animal behavior monitoring
- grazing time
- velocity
- position
- general behavior
Mathematical modeling og animal behavior (case study:dairy cows

 

StatusFinished
Effective start/end date15/02/200514/02/2008
ID: 214527502