Biodiversity surveys are often required for development projects in cities that could affect protected species such as bats. Bats are important biodiversity indicators of the wider health of the environment and activity surveys of bat species are used to report on the performance of mitigation actions. Typically, sensors are used in the field to listen to the ultrasonic echolocation calls of bats or the audio data is recorded for post‐processing to calculate the activity levels. Current methods rely on significant human input and therefore present an opportunity for continuous monitoring and in situ machine learning detection of bat calls in the field. Here, we show the results from a longitudinal study of 15 novel Internet connected bat sensors—Echo Boxes—in a large urban park. The study provided empirical evidence of how edge processing can reduce network traffic and storage demands by several orders of magnitude, making it possible to run continuous monitoring activities for many months including periods which traditionally would not be monitored. Our results demonstrate how the combination of artificial intelligence techniques and low‐cost sensor networks can be used to create novel insights for ecologists and conservation decision‐makers.

The content of this paper is a snapshot of a current project looking at producing a real-time sensor-based building assessment tool, and a system that personalises workspaces using multi-agent technology. Both systems derive physical environment information from a wireless sensor network that allows clients to subscribe to real-time sensed data. The principal ideologies behind this project are energy efficiency and well-being of occupants; in the context of leveraging the current state-of-the-art in agent technology, wireless sensor networks and building assessment systems to enable the optimisation and assessment of buildings. Participants of this project are from both industry (construction and research) and academia.

Hospital operating theatre suites are a particularly resource- and energy-intensive component of the health sector. Reducing their carbon footprint presents a significant challenge due to the necessity of maintaining patient safety. In this paper, we apply a multidisciplinary methodology to investigate and assess various strategies aimed at reducing the carbon footprint in hospital theatres. The strategies evaluated include (i) the duration of theatre ventilation operation, (ii) the efficiency of the ventilation strategy, and (iii) heat recovery systems and technologies. These approaches are assessed using a combination of theatre space monitoring (via building management systems), computational air-flow modelling and mathematical models. We develop a robust methodology that applies these modelling techniques to general hospital suites, enabling the estimation of reductions in CO ₂ equivalent.

Biomimicry applications in different domains, from material science to technology, have proven to be promising in inspiring innovative solutions for present-day challenges. However, biomimetic applications in the built environment face several barriers including the absence of biological knowledge of architects and planners and the lack of an adequate common means to transfer biomimetic concepts into strategies applicable in the urban context. This review aims to create a multidimensional relational database of biomimetic strategies from successful precedent case studies in the built environment across different city systems and on different application scales. To achieve this, a thorough systematic search of the literature was implemented to map relevant biomimetic case studies, which are analyzed to extract biomimetic strategies that proved to be applicable and successful in an urban context. These strategies are then classified and documented in a relational database. This will provide a guide for architects and planners on how to transfer biomimetic strategies to strategies applicable in the urban context, thus bridging the gap of their lack of biological knowledge. The resulting matrix of strategies provides potential strategies across most of the different city systems and scales with few exceptions. This gap will be covered in a future work, currently in progress, to expand the database to include all city systems and scales.

Ophthalmology outpatient treatment in the NHS reached 5.5 million visits in 2020–21 and has accumulated a significant backlog due to the COVID-19 pandemic. A case study is described which brings together various disciplines to create a smart building environment. This chapter details what was done in order to aggregate digital and physical information in the iterative delivery of an Ophthalmology outpatient clinic. IoT people tracking, CO₂ Sensors and Discrete Event Simulation were applied alongside virtual, augmented and physical mock-ups and modular prototyping. There are complexities in assimilating large volumes of data (e.g. IoT) and challenges caused by various data formats and visual representations (e.g. hand-drawn, 2D drawings, AR and VR), however we show how an iteration approach can support advanced digital twin development for high technology healthcare building types. This work has informed rapid diagnostics, and shown how an empty commercial real estate space can be repurposed for healthcare. <!----> <!----> <!----> <!---->