The concept of a “digital twin” as a model for data-driven management and control of physical systems has emerged over the past decade in the domains of manufacturing, production, and operations. In the context of buildings and civil infrastructure, the notion of a digital twin remains ill-defined, with little or no consensus among researchers and practitioners of the ways in which digital twin processes and data-centric technologies can support design and construction. This paper builds on existing concepts of Building Information Modeling (BIM), lean project production systems, automated data acquisition from construction sites and supply chains, and artificial intelligence to formulate a mode of construction that applies digital twin information systems to achieve closed loop control systems. It contributes a set of four core information and control concepts for digital twin construction (DTC), which define the dimensions of the conceptual space for the information used in DTC workflows. Working from the core concepts, we propose a DTC information system workflow—including information stores, information processing functions, and monitoring technologies—according to three concentric control workflow cycles. DTC should be viewed as a comprehensive mode of construction that prioritizes closing the control loops rather than an extension of BIM tools integrated with sensing and monitoring technologies.

There is increasing public concern about poultry welfare; the quality of animal welfare is closely related to the quality of livestock products and the health of consumers. Good animal welfare promotes the healthy growth of poultry, which can reduce the disease rate and improve the production quality and capacity. As behaviour responses are an important expression of welfare, the study of behaviour is a simple and non-invasive method to assess animal welfare. The use of modern technology offers the possibility to monitor the behaviour of broilers and laying hens in a continuous and automated way. This paper reviews the latest technologies used for monitoring the behaviour of broilers and laying hens under both experimental conditions and commercial applications and discusses the potential of developing a precision livestock farming (PLF) system. The techniques that are presented and discussed include sound analysis, which can be an online tool to automatically monitor poultry behaviour non-invasively at the group level; wireless, wearable sensors with radio-frequency identification devices, which can automatically identify individual chickens, track the location and movement of individuals in real time and quantify some behavioural traits accordingly and image processing technology, which can be considered a direct tool for measuring behaviours, especially activity behaviours and disease early warning. All of these technologies can monitor and analyse poultry behaviour, at the group level or individual level, on commercial farms. However, the popularity and adoption of these technologies has been hampered by the logistics of applying them to thousands and tens of thousands of birds on commercial farms. This review discusses the advantages and disadvantages of these techniques in commercial applications and presents evidence that they provide potential tools to automatically monitor the behaviours of broilers and laying hens on commercial farms. However, there still has a long way to go to develop a PLF system to detect and predict abnormal situations.

Current feeder space recommendations in laying hen welfare guidelines are inconsistent among and within countries. One determining criterion forming the recommendations (e.g. 12.0 cm/hen for the EU guideline) is that all birds can feed simultaneously. However, if there are other resources in the environment, as in enriched colony housing (ECH), it is unknown whether group-housed hens will choose to feed simultaneously. This study assesses the impact of feeder space on feeding behavior of 60 laying hens (W-36) in ECH using a ultra-high frequency radio-frequency identification-based tracking system. The feeder spaces investigated were 12.0, 9.5, 8.5 and 6.5 cm/hen, achieved by blocking portions of the overall feeder access to keep hens at the same stocking density. Each feeder space treatment, randomly assigned over the course of the experiment, lasted for 7 consecutive days. Feeding behaviors were characterized as daily time spent at the feeder (TS, min/hen-day), daily frequency of visits to the feeder (FV, #/hen-day), and maximum or average percentage of hens feeding simultaneously (MPB, APB, %). Group-average daily feed intake (FI, g/hen-day), water use (WU, g/hen-day), and hen-day egg production (HDEP, %) were also measured. The results revealed that at 12.0 cm/hen, where unoccupied feeder space was present, a maximum of 59.0±1.4% (average of 31.7±0.3%) hens fed simultaneously. No significant differences were detected among 12.0, 9.5 and 8.5 cm/hen in TS (293±10, 286±10 and 281±10 min/hen-day) and MPB (59.0±1.4, 57.3±1.4 and 53.3±1.4%) (P>0.05). The outcome of no significant differences also held true between 12.0 and 9.5 cm/hen in APB (31.7±0.3 v. 30.8±0.3%) and between 9.5 and 8.5 cm/hen in all response variables measured (P>0.05). However, there were significant differences in APB between 6.5 cm/hen and all other treatments; in TS and FV between 6.5 and 9.5 cm/hen; and in MPB between 6.5 and 12 cm/hen (P<0.05). Considerable inter-hen variability was observed in TS (CV varying from 28.0% to 32.1%) and FV (CV varying from 26.5% to 27.8%). All the feeder spaces tested showed no significant impact on FI, WU or HDEP (P>0.05). The results revealed that synchronous feeding of hens in the ECH did not increase with increasing feeder space. However, it is worth noting that lower feeder space may lead to aggression or frustration which was not quantified in the current study.

The number and size of free-range laying hen (Gallus gallus domesticus) production systems are increasing within Australia in response to consumer demand for perceived improvement in hen welfare. However, variation in outdoor stocking density has generated consumer dissatisfaction leading to the development of a national information standard on free-range egg labelling by the Australian Consumer Affairs Ministers. The current Australian Model Code of Practice for Domestic Poultry states a guideline of 1500 hens/ha, but no maximum density is set. Radio-frequency identification (RFID) tracking technology was used to measure daily range usage by individual ISA Brown hens housed in six small flocks (150 hens/flock – 50% of hens tagged), each with access to one of three outdoor stocking density treatments (two replicates per treatment: 2000, 10 000, 20 000 hens/ha), from 22 to 26, 27 to 31 and 32 to 36 weeks of age. There was some variation in range usage across the sampling periods and by weeks 32 to 36 individual hens from the lowest stocking density on average used the range for longer each day (P<0.001), with fewer visits and longer maximum durations per visit (P<0.001). Individual hens within all stocking densities varied in the percentage of days they accessed the range with 2% of tagged hens in each treatment never venturing outdoors and a large proportion that accessed the range daily (2000 hens/ha: 80.5%; 10 000 hens/ha: 66.5%; 20 000 hens/ha: 71.4%). On average, 38% to 48% of hens were seen on the range simultaneously and used all available areas of all ranges. These results of experimental-sized flocks have implications for determining optimal outdoor stocking densities for commercial free-range laying hens but further research would be needed to determine the effects of increased range usage on hen welfare.