Sensor signaleert naderende geboorte

Met de nieuwe generatie draadloze sensoren, die momenteel in ontwikkeling is en langzaam voor de praktijk beschikbaar komt, kunnen steeds meer signalen van het individuele dier automatisch worden vastgelegd, zoals een naderende geboort

Trustworthiness assessment of cow behaviour data collected in a wireless sensor network

Wireless sensor networks can be used for automated cow monitoring, e.g. for behaviour and locomotion monitoring. Sensor data should only be used when they can be trusted. The trustworthiness of sensor data can be assessed in a framework, from the acquisition at the node to their delivery to business applications, including any intermediary routing and processing. The trustworthiness assessment method has been evaluated with sensor data collected during one of the experiments within the WASP project. Sensor data are not trusted when the trustworthiness gets below a threshold. An alert is generated then and it is possible to find the cause by tracing back the trust of composing elements. The trustworthiness assessment method results in the detection of problems with nodes (e.g. detached node or exhausted battery). Most of these problems can be classified as true and most of them were not notified on the farm. Therefore trustworthiness assessment is worthwhile to improve automated cow status monitoring

Recording of dairy cows behaviour with wireless accelerometers

The daily behaviour of dairy cows reflects the health and well-being status. The behaviour can be monitored with accelerometers (used as a tilt sensor to measure the angle) in a wireless sensor network. The angle of a leg reflects the lying or standing behaviour, the angle of the head might reflect the eating behaviour. An experiment was carried out at an experimental farm during 50 days. Six cows were equipped with two 2D accelerometers, one attached to the neck and one attached to the right hind leg. The accelerometers were attached to wireless sensor nodes. The acceleration of the neck and leg was recorded every halve minute (average of seven measurements with 1 Hz measuring frequency). Based on calibration measurements, the acceleration of the leg and the neck were both transformed to the angle. A cow was standing when the angle of the leg was more than 45°, otherwise lying. The method to transform the acceleration to angle and behaviour appears to be appropriate, it is possible to monitor the cow's behaviour with a wireless sensor network equipped with accelerometers

Radio frequency identification of animals, the quality of products in the field.

In several parts of the world livestock animals (sheep, goats and cattle) are identified with radiofrequency identification (RFID) devices. These transponders can be read with handheld and stationary readers. The reading can be performed on the farm, during transport, in the sales yard and in the slaughterhouse. Especially when the RFID tags are read with a static reader the signal strength the transponders produce is very important (reading distance shall be sufficient if animal passes the reader). If the signal is insufficient it can result in misreads. In many countries RFID tags have to meet certain approval criteria to get allowance for use for identifying a certain species with those tags. The approval is mostly based upon tests that are performed by test agencies on new tags that the manufacturer has send to the test agency. The tags the manufacturer later on sell on the market can have a different quality as the original tested product or the quality of the RFID tags can be influenced by environmental conditions e.g. moisture. The reduced quality can increase the misread percentage. In the most RFID schemes there are no checks performed that safeguard the quality of the products sold on the marked. Schemes that monitor the quality of RFID products on the market could be introduced. This monitoring could e.g. be based upon RFID sample tags that are collected during slaughter. When a certain percentages of the recovered tags are outside specification the manufacturer should improve the quality of his product. If the manufacturer e.g. within a year does not succeed to improve the quality of that product approval for that product could be withdrawn

Recording and analysis of locomotion in dairy cows with 3D accelerometers

An automated method for lameness detection can be an alternative for detection by regular observations. Accelerometers attached to a leg of the dairy cow can be used to record the locomotion of a dairy cow. In an experiment the 3D acceleration of the right hind leg during walking of three dairy cows was measured and analysed. Nodes with a 3D accelerometer in a wireless sensor network were applied to measure with a frequency of 50 Hz. After data filtering, the data analysis was in two steps: first step detection and secondly the determination of step parameters. Variance analysis was used for step detection. For each step the parameters step length and step time were calculated. The steps and step parameters can be used in future research for gait analysis of lame and non-lame cows. The aim of this paper is to describe the collection and analysis of data in this experiment and to assess the possibilities for gait analysis. It can be concluded that the application of accelerometers in a wireless sensor network gives promising results. Step detection is possible and step parameters can be derived

Young stock rearing using automatically recorded data

The subject ‘young stock rearing’ is important for future dairy farming. So far there has been too little attention for young stock rearing. Proper care by monitoring health and growth of the young animals will lengthen life expectancy and increase milk production of the adult dairy cow. Due to the increasing farm sizes it becomes harder for the farmer to pay sufficient attention to all individual animals. Facilities like automatic milk feeders and water drinkers combined with weighing systems are used to gather information about the status of all individuals. The information consists of daily milk and water intake, body weight and other behavioural data. Models are developed to detect deviations in the normal pattern of this information. Only these anomalies are reported with instructions for standardized actions to be undertaken, the standard operating procedures. This paper provides the background for the alerts for health problems and for lagging growth in young stock till the age of 4 month