A Monitoring System for Laying Hens That Uses a Detection Sensor Based on Infrared Technology and Image Pattern Recognition.

Mauro Zaninelli,Valentino Bontempo,Fabio Luzi,Vittorio Dell’Orto,Giovanni Savoini,Veronica Redaelli

doi:10.3390/s17061195

Mauro Zaninelli, Valentino Bontempo + Show 4 more

Open Access

https://doi.org/10.3390/s17061195

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Abstract

In Italy, organic egg production farms use free-range housing systems with a big outdoor area and a flock of no more than 500 hens. With additional devices and/or farming procedures, the whole flock could be forced to stay in the outdoor area for a limited time of the day. As a consequence, ozone treatments of housing areas could be performed in order to reduce the levels of atmospheric ammonia and bacterial load without risks, due by its toxicity, both for hens and workers. However, an automatic monitoring system, and a sensor able to detect the presence of animals, would be necessary. For this purpose, a first sensor was developed but some limits, related to the time necessary to detect a hen, were observed. In this study, significant improvements, for this sensor, are proposed. They were reached by an image pattern recognition technique that was applied to thermografic images acquired from the housing system. An experimental group of seven laying hens was selected for the tests, carried out for three weeks. The first week was used to set-up the sensor. Different templates, to use for the pattern recognition, were studied and different floor temperature shifts were investigated. At the end of these evaluations, a template of elliptical shape, and sizes of 135 × 63 pixels, was chosen. Furthermore, a temperature shift of one degree was selected to calculate, for each image, a color background threshold to apply in the following field tests. Obtained results showed an improvement of the sensor detection accuracy that reached values of sensitivity and specificity of 95.1% and 98.7%. In addition, the range of time necessary to detect a hen, or classify a case, was reduced at two seconds. This result could allow the sensor to control a bigger area of the housing system. Thus, the resulting monitoring system could allow to perform the sanitary treatments without risks both for animals and humans.

Highlights

The internal temperature of housing systems should not exceed the 16–24 ◦ C range [1]; air humidity should be between 50% and 70% [1]; the concentration of atmospheric ammonia, caused by litter microbiological populations [2], should be limited to 20–25 ppm and not exceed this threshold for an interval of time of more than 8 h [3]; the concentration of carbon dioxide, caused by hens and heating systems [4], should be limited to 3000 ppm and this threshold should only be surpassed for intervals of time lower than 8 h [5]; the concentration of dust, that in different types of housing system can reach values of 6.5 mg/m3 and 80 mg/m3 [6]
The results showed that an algorithm, based on the Hybrid Support Vector Machine model, could be a valid tool in order to study the behavior of hens without the need of additional sensors, such as radio frequency identification (RFID) transponders
In a first phase of elaborations, carried out on thermografic images acquired during the sensor set-up, three different shifts of the mean floor temperature were investigated and the geometric features of the templates, to be used in the following pattern recognitions, were identified

Summary

Introduction

Different indexes have to be monitored and maintained within specific ranges. The internal temperature of housing systems should not exceed the 16–24 ◦ C range [1]; air humidity should be between 50% and 70% [1]; the concentration of atmospheric ammonia, caused by litter microbiological populations [2], should be limited to 20–25 ppm and not exceed this threshold for an interval of time of more than 8 h [3]; the concentration of carbon dioxide, caused by hens and heating systems [4], should be limited to 3000 ppm and this threshold should only be surpassed for intervals of time lower than 8 h [5]; the concentration of dust, that in different types of housing system can reach values of 6.5 mg/m3 and 80 mg/m3 (for respirable and inhalable dust, respectively) [6].

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