Smart technologies to improve the management and resilience to climate change of livestock housing: a systematic and critical review
Articolo
Data di Pubblicazione:
2025
Citazione:
Smart technologies to improve the management and resilience to climate
change of livestock housing: a systematic and critical review / Bordignon, Francesco; Provolo, Giorgio; Riva, Elisabetta; Caria, Maria; Todde, Giuseppe; Sara, Gabriele; Cesarini, Francesco; Grossi, Giampiero; Vitali, Andrea; Lacetera, Nicola; Pezzuolo, Andrea. - In: ITALIAN JOURNAL OF ANIMAL SCIENCE. - ISSN 1594-4077. - (2025). [10.1080/1828051X.2025.2455500]
Abstract:
Smart technologies such as sensors, data analytics, and automated systems could play a crucial
role in enhancing the resilience of livestock housing to climate change. By providing precise
and timely data, these technologies enable better resource management, early detection of
stressors, and adaptive responses to environmental changes. However, a comprehensive and
critical evaluation of their potential role and current applications in improving the sustainability
and adaptability of livestock systems to climate change is still lacking. This research provides a
first investigation of the role of smart technologies in addressing climate change challenges
within the livestock sector and identifies critical areas for future research and development. A
systematic and critical review of 131 papers published between 2018 and 2024, focusing on the
application of smart technologies to enhance the resilience of livestock housing to climate
change, was carried out. The articles were categorised based on the main livestock farming systems
(dairy cows, pigs, poultry, small-ruminants, and pasture-based systems) and the type of
smart technologies used, including wearable and non-wearable devices for monitoring animal
health and behaviour, as well as systems for controlling environmental conditions in livestock
housing. The results revealed that while smart technologies are predominantly used to monitor
animal behaviour and health, their application in controlling environmental conditions is still
limited. Wearable devices are extensively used in dairy cows and small ruminants, whereas nonwearable
devices are more common in pigs and poultry. Future research should focus on
advancing sensor technology, integrating data-driven management, and enhancing communication
between sensors and farmers.
role in enhancing the resilience of livestock housing to climate change. By providing precise
and timely data, these technologies enable better resource management, early detection of
stressors, and adaptive responses to environmental changes. However, a comprehensive and
critical evaluation of their potential role and current applications in improving the sustainability
and adaptability of livestock systems to climate change is still lacking. This research provides a
first investigation of the role of smart technologies in addressing climate change challenges
within the livestock sector and identifies critical areas for future research and development. A
systematic and critical review of 131 papers published between 2018 and 2024, focusing on the
application of smart technologies to enhance the resilience of livestock housing to climate
change, was carried out. The articles were categorised based on the main livestock farming systems
(dairy cows, pigs, poultry, small-ruminants, and pasture-based systems) and the type of
smart technologies used, including wearable and non-wearable devices for monitoring animal
health and behaviour, as well as systems for controlling environmental conditions in livestock
housing. The results revealed that while smart technologies are predominantly used to monitor
animal behaviour and health, their application in controlling environmental conditions is still
limited. Wearable devices are extensively used in dairy cows and small ruminants, whereas nonwearable
devices are more common in pigs and poultry. Future research should focus on
advancing sensor technology, integrating data-driven management, and enhancing communication
between sensors and farmers.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Bordignon, Francesco; Provolo, Giorgio; Riva, Elisabetta; Caria, Maria; Todde, Giuseppe; Sara, Gabriele; Cesarini, Francesco; Grossi, Giampiero; Vitali, Andrea; Lacetera, Nicola; Pezzuolo, Andrea
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