AI news
The technology correctly distinguished distress calls from other barn noises with 97% accuracy
Artificial intelligence that could improve the welfare of farmed chickens by eavesdropping on their squawks could become available within five years, researchers say.
The technology, which detects and quantifies distress calls made by chickens housed in huge indoor sheds, correctly distinguished distress calls from other barn noises with 97% accuracy, new research suggests. A similar approach could eventually be used to drive up welfare standards in other farmed animals.
Each year, about 25 billion chickens are farmed around the world – many of them in huge sheds, each housing thousands of birds. One way to assess the welfare of such creatures is to listen to the sounds that they make.
“Chickens are very vocal, but the distress call tends to be louder than the others, and is what we would describe as a pure tonal call,” said Alan McElligott, an associate professor of animal behaviour and welfare at the City University of Hong Kong. “Even to the untrained ear, it’s not too difficult to pick them out.” Persuading farmers to adopt the technology may be relatively easy. Previous research by McElligott found that distress calls made by young chicks could predict the amount of weight gained and the number of deaths in the whole flock during its lifetime. “Also, the vocalisation of distress is just one welfare indicator, but there are a number of other physical factors such as lameness and leg burns which farmers should also be looking out for.”
Cayla is able to listen, search anwers on internet and talk back to the child
Parmi les entreprises qui étaient présentes au salon sur la mobilité intelligente baptisée «EcoMotion», qui s’est récemment tenu à Tel-Aviv, figure ITC (Intelligent traffic control), qui développe un logiciel capable de récolter des données en temps réel à partir de caméras de surveillance le long des routes et de manipuler les feux de signalisation en fonction des flux de circulation.
«ITC est parvenue à prouver mathématiquement que de nombreux embouteillages peuvent être empêchés, si on intervient assez tôt», explique Dvir Kenig, chargé des technologies de cette entreprise, citant une baisse de 30% de l’engorgement sur deux carrefours où le système a été mis en place.criterias include: -physical activity -meals -CO2 usage (cars, flights, food) -social contacts & tracking -medical history -political position/correspondence, volunteering -СНИЛС, ИНН, education, languages, prizes, -bank scoring -sport preferences
used for -medical appointments -biometrical payments integration -e-documents and e-IDs