Context-aware module for evaporative cooling in the outdoor built environment

Abstract

This paper introduces modular and context-aware evaporative cooling for the outdoor urban environment as a physical structure that could be implemented at various scales and physical contexts. We propose a technique for collecting occupancy and climatic data to create a computational context and optimise its operation. We then outline a concept for developing a predictive algorithm that would further enhance its performance. The research focuses on the interaction between the proposed system and the environment and establishes an evidence-based technique to balance the temperature drop and the humidity it generates. The study combines architectural design, mechanical engineering and computer science to enable the upscaled application of evaporative cooling to help reduce local heat accumulation in cities.

Keywords

responsive environments evaporative cooling mechatronics occupancy detection human-building interaction evidence-based design

Introduction

The Urban Heat Island (UHI) is a widely researched phenomenon across numerous fields, including Architecture and Urban Planning.^1,2 It refers to the local heat accumulation generated by urban structures and anthropogenic heat sources.³ Such heat accumulation is rising and increasingly limiting the use of outdoor areas in the built environment, which in turn compromises people’s health, well-being and social interaction. UHI prevention and mitigation strategies increasingly interfere with architecture and how architects think about the relationship between indoors and outdoors and how they design spaces between buildings. Water-based mitigators are amongst the most effective solutions to reducing air temperature in outdoor areas of the built environment.^4,5 Researchers in building physics and engineering have shown interest in Evaporative Cooling (EC) systems because they consume relatively little water and power while providing notable local temperature reduction and have established that their efficiency depends on the interaction between the system and the climatic context.^6,7 It is not only air temperature that changes with water-based cooling, but also air humidity, and therefore balancing between the two throughout the exchange between the system and the environment is one of the main challenges. At the same time, EC systems are infrequently included in the planning of outdoor public areas, and their full potential to alter the local climate in correlation with architectural intent is still rarely explored. Historic projects such as Tanner Fountain at Harvard University by PWP Landscape Architecture completed in 1984, Miroir d’eau in Bordeaux by Michel Corajoud completed in 2006 and the Eco-boulevard in Madrid by Ecosystems Urbano realised in 2007, exemplify the ability of water vapour to alter local climatic conditions in outdoor public spaces. They also show how vapour and infrastructure providing the vapour can be important architectural features.^8–11 In these projects, EC is an architectural element employed to intensify the use and augment occupants' engagement with space. There are many more examples of how water misting solutions are successfully used in urban environments on a small scale without an apparent architectural intent. At the same time, companies worldwide specialise in testing and developing evaporative systems for cooling, humidification, odour control and dust suppression for various industrial applications. This study focuses on how such a practical and technical knowledge can be combined with evidence-based architectural design and, in the longer run, linked to the lasting speculations of spatial boundaries that are not geometric nor solid and yet informative to human activity and social engagement.^12,13 It continues exploring the increased availability of wireless sensing devices coupled with the growing use of computational techniques in studying the built environment to understand and creatively explore meteorological conditions and microclimates as architectural elements.^14–16

Evaporative cooling uses water to cool the air, and several established techniques are applicable to the built environment.^4,5 This paper focuses on the water spraying or misting technique, whereby water is emitted into the air through nozzles under high pressure producing clouds of fine mist, which absorb ambient heat.⁵ The fine droplet size, determined by the water pressure and nozzle characteristics, ensures water evaporates before hitting the ground and avoids unwanted wetting of floor surfaces.¹⁷ The ambient temperature is reduced when these droplets evaporate into the air, and researchers report that evaporative cooling systems can reduce local air temperature up to 13°C depending on the existing climatic conditions as well as the size of the misting system.^18,19 EC in outdoor areas is most commonly used on a small scale, that is, private outdoor areas, restaurants and children playgrounds. There are several challenges to a broader application that we identify in the following section of this paper.

Background research

The challenges we recognise in the existing literature and recent research on EC in outdoor urban environments revolve around the three general questions: How to measure its efficiency and which outdoor thermal comfort indices can be used to model and evaluate EC’s impact on humans? How to make it controllable and responsive to improve its efficacy and make it applicable in varied climatic conditions? How to upscale and integrate EC systems into the planning and design of outdoor urban areas?

A systemic overview of the recent research on water mist spraying for cooling in the outdoor built environment, conducted by Dr Giulia Ulpiani points out that although EC qualifies as an efficient heat mitigator, there is no conclusive method for evaluation of the performance of outdoor EC systems, due to variety of metrics used and heterogeneity of experimental conditions related to the geographical location and climate classification, but also to site specifics including vegetation, shadowing and building materials that impact the evolution of the local climate.²⁰ Most of the studies in this overview focus on the local air humidity and temperature measurements, while wind direction and speed, droplet size and pump pressure were also identified among the relevant parameters.²⁰ Researchers also measure the effectiveness of EC by calculating air enthalpy at different times of the day.²¹ The Effective Temperature Index is also used for the evaluation of thermal comfort under the operation of EC in the past.⁷ Other thermal indices such as Physiologically Equivalent Temperature, Outdoor Standard Effective Temperature and Wet Bulb Globe Temperature encapsulate information of finer resolution and provide a comprehensive definition of thermal comfort and are also helpful to the examination of EC’s impact on humans.²² Furthermore, in addition to quantitative studies, analysis of qualitative data obtained through questionnaires gauging the individual and subjective perception of thermal comfort is used to evaluate outdoor evaporative cooling.²²

Water-based cooling solutions are traditionally used in warm and dry climates, but the applicability of evaporative cooling has also been demonstrated in more humid conditions because researchers have been able to monitor the evolution of both air temperature and humidity locally and more precisely under the operation of outdoor EC systems.^21,23 This capacity is extended further with the use of wireless sensor networks and computational techniques. However, our preliminary research reveals that only a small number of trial studies have been conducted to test computational techniques such as fuzzy logic in making outdoor EC systems responsive to the locally measured climatic conditions such as air temperature, relative humidity, wind speed and solar irradiation.²⁴ These are the early steps in introducing intelligence into the operation of outdoor EC systems that could expand its use, improve thermal comfort and make better use of resources. Our background research has identified a lack of studies that include aspects of occupants' behaviour to examine cooling systems in outdoor environments, while there is a clear shift toward the occupant centric approach to studying indoor environments.²⁵ The growing body of research demonstrates that a better understanding of occupant behaviour can help improve buildings' energy consumption.²⁶ Indoor environments have well-established boundaries that enable easier control of climatic parameters, influencing both occupant comfort and energy consumption.²⁷ Studies addressing indoor climates are more feasible because of the controllability and predictability of climatic conditions and are more common as most people work and spend more time indoors.^28–30 However, approaches based on the use of information and communication technology developed for indoor environments could be valuable to improving thermal comfort and energy consumption in outdoor environments. The principal differences between indoor and outdoor climate control are related to what generates computational context, what parameters are relevant for the operation of technical systems, such as EC, and what information processing techniques can be used to predict or optimise their operation. The application of sensing devices and computational techniques is not sufficiently exploited to address heat mitigation in outdoor environments.³¹ A rare example of such application is a study employing Wi-Fi counters to record occupants' presence in the outdoor area and uses simulation models and the Universal Thermal Climate Index values to evaluate the operation of the cooling system.³² It suggests how information on occupants' behaviour could be combined with climatic parameters to evaluate the operation of outdoor cooling systems and thus help improve the thermal comfort and therefore human well-being, and energy or resource consumption and therefore its environmental impact.

The gravity of research on EC of outdoor areas in the built environment is predominantly related to building physics and engineering.^33,34 Climatologists and urban planners continue to look for ways to manage the impact of UHI on the built environment.^2,35 Most research projects are based on numeric modelling and simulation, while the actual application of EC systems in urban environments at both systemic level and the aspect of placemaking is not sufficiently addressed. The small number of water misting prototypes constructed for research in the domain of building physics does not address the critical questions of how these solutions can be implemented in streets and squares of cities, and what are the spatial and material challenges for their implementation in the built environment. ^6,19,23,34 In recent history, only a handful of experimental projects have demonstrated the architectural potential of water misting in urban outdoor areas. Among them, the best known are short-lived structures built for large international exhibitions, such as the dome of the Pepsi Pavilion immersed into the artificial cloud, designed for the World Expo in Osaka by artist Fujiko Nakaya and the Experiments in Art and Technology group in 1970, the fog engulfed lightweight structure of the Blur Building on the Lake Neuchatel designed for the Swiss Expo by Diller Scofidio and Renfro in 2002, and the more recently Austria Pavilion at Milan Expo by Breathe Austria.^36–38

This paper outlines research as follows. Current drivers and challenges to the application of EC systems in outdoor urban environments are identified in the Introduction and Background research sections. The following section introduces research aims and the basis for the design study at the intersection of architectural design, mechanical engineering and computer science. It formulates research questions addressing design, manufacturing and computational techniques to enable the use of data obtained from the environment to optimise the system’s operation. The research methods section presents an evidence-based design study and simulation modelling that would enable prototype production and real-life testing. The results include graphs that demonstrate the correlation between input and output parameters and provide an insight into the system’s interaction with the environment that would enable a more comprehensive and upscaled application of EC in cities. We then outline how data acquired from a combined measuring of climatic parameters and occupants count can be used to develop a predictive algorithm that would further enhance the system’s operation. In the Discussion and Conclusion sections, we focus on how the presented results address current research challenges to the application of EC in outdoor urban environments. We discuss the limitations of the presented study and identify future research directions.

Research aims

This study aims to introduce a modular and context-aware water misting solution for the outdoor urban environment. First, we present a physical structure that could be implemented in various built contexts to facilitate the discharge of water vapour into the ambient air. Second, we propose a technique for collecting occupancy and climatic data to create a computational context and optimise the operation of the proposed solution by balancing temperature reduction and humidity generated by the system. The study’s objective is to enable efficient, upscaled, diversified and architecturally sound use of the proposed solution to help reduce local heat accumulation in cities.

Our background research identifies the lack of knowledge on how EC can be employed at a larger scale in cities and the deficiency of studies based on real-life experimenting that could examine broader implications on the use of public areas, including architectural aspects. It is established that EC solutions, although very efficient, are sporadically applied and not yet at a systemic level, integral to the planning and design of outdoor public places. Furthermore, the interaction with local microclimate is identified as essential, and it is found that the system’s ability to respond to changes in local meteorological trends is critical for its efficiency. Finally, our preliminary research identifies a possibility to expand studies using locally measured meteorological conditions and occupancy centric data for enhancement of EC systems.

To that end, this paper presents an innovative design solution that offers itself as the backdrop for further inquiry into developing a responsive local climate control system that could be applied in various outdoor built contexts and climates. This research addresses the following questions: (1) How to design a mechatronic system and manufacture a modular affordance for EC that is applicable to different built contexts? (2) How to employ wireless sensor networks and computational techniques to collect occupancy and meteorological data and establish an evidence-based technique for measuring the efficacy of EC systems? (3) How to enable the development of the computational method for predictive analysis and pattern recognition to advance the system’s context-aware capacity?

The first research question is resolved with a design study resulting in a design solution for the modular street fixture for EC. The second question is answered through simulation modelling, generating data and statistical graphs to provide evidence and insight into the system’s operation. The third question is addressed with a formulation of an approach to creating a database that would be used in developing an algorithm with pattern recognition capabilities.

Modular street fixture for evaporative cooling

The proposed module consists of a mechatronic system, water supply infrastructure and a supporting structure (Figure 1). The mechatronic system includes air temperature and humidity sensors, pressure plates used to determine the occupant’s presence, a microcontroller and an actuator that is a solenoid valve (Figure 2). Sensing devices gather the information that is processed and used to control the operation of the solenoid valve. Information processing will be presented in the next section. The water supply infrastructure that delivers EC comprises the solenoid valves, water supply lines and spray nozzles emitting water into the air under high pressure to absorb ambient heat. There is one valve per supply line.

Figure 1.

CGI of the proposed module.

Figure 2.

Mechatronic system.

In response to the water supply scheme and structural requirements, we have designed a tree-like supporting structure. Its role is to house air temperature and humidity sensors at the height of 1.5 m above the floor level, to hold supply lines and valves, and to position nozzles at the height of 3 m to maximise the water misting effect (Figure 3 and 4). There is a minimum of three overhead positioned nozzles per modular element, approximately 1.5 m apart. The holding structure is anchored into the ground. It consists of the trunk measuring 120 mm in diameter and branches with diameters varying from 40 to 80 mm spreading up to 2 m outward from the anchor. The entire holding structure comprises 47 distinct segments to ease fabrication, transportation and assembly (Figure 5). All components contain sleeve ends designed to allow quick manual assembly requiring only minimal human resources and basic tools (Figure 6). To date, we have produced a prototype of the supporting structure at the 1:2 scale using the HP Multi Jet Fusion 3D plastic powder printing (Figure 7). A segment is produced at full scale, while further research is needed to test the use of more resilient materials that are easily cleaned, maintained and repaired.

Figure 3.

Section of the supporting structure with component specification.

Figure 4.

Top plan of the supporting structure.

Figure 5.

3D printed segments of the supporting structure at 1:2 scale.

Figure 6.

Perspective drawing of the Sleeve Joint System.

Figure 7.

Photo of the assembled supporting structure prototype produced at the 1:2 scale.

The proposed solution can be employed as a single unit impacting the climate of 10 m² outdoor area, or multiple modules can be installed in clusters to affect larger zones (Figure 8). In line with the current Urban Design Guidelines for Victoria for placing objects in public spaces, EC modules could be placed along pedestrian routes at convenient places where people gather and tend to spend time and where seats usually are located.³⁹ Their positioning could help define a pedestrian path while staying outside view lines to significant landmarks and cultural elements. These modules can also double as lighting poles, and for this purpose, a light source is integrated into the supporting structure. The object is conceived as an architectural element that could be used to improve the amenity of outdoor public spaces.

Figure 8.

Multiple modules combined into a single EC system.

Unlike the most known experimental setups, the proposed EC module is structurally autonomous. The design integrates a supporting structure, water supply infrastructure and sensing devices into a single object. The proposed tree-like support, shaped according to both supply and structural requirements, is parametrically designed and would be digitally fabricated to enable any potential production in higher numbers. The approach based on parametric design and manufacturing technique would allow for multiple geometric variations to be produced, differing by the number of branches and their spans. The size and geometry of the supporting structure can be adjusted to different physical environments, while the number and location of water spray nozzles can vary according to specific meteorological conditions.

Evidence-based evaluation of the evaporative cooling system’s performance

The simulation method is developed to examine how environmental information gathered by sensing devices can be used to inform the operation of the EC system. The model presented in this section further develops the previously published approach for evaluating perceived benefits that would arise from the introduction of wireless sensor networks and computational techniques.⁴⁰ The input values used in the simulation model are retrieved from the weather database for the inner Melbourne area and generated as a provisional occupant’s count in an outdoor area of 10 m² that would be affected by the single module presented in the previous section.⁴¹ These values substitute measurements that would be taken at 10 min intervals between 10:00 a.m. and 6:00 p.m., each day during the summer period of 12 weeks in a real-life scenario. The simulation modelling relies on an algorithm that was developed using Python programming language to process input information. The algorithm is structured into three phases. Each phase provides an output as two variables, the percentage of active nozzles% and the duration of release periods defined in min. The accumulative effect of these two parameters is directly proportional to water consumption and air humidity generated by the system. The two initial simulation stages are solely concerned with climatic parameters, namely, air temperature and humidity, while the final includes occupants’ count. The simulation is structured into these three phases to enable the comparison of results acquired from three different ways of interaction between the system and the environment. The number of input parameters increases, and the applied computation technique grows in complexity from phase to phase, and the system progresses from automated toward autonomous.

In the first phase, the algorithm controls water release periods and the number of active spray nozzles according to the current air temperature without considering previously measured values (Figure 9(a)). The misting system activates at 25°C and aims to maintain local air temperature in that range. The algorithm triggers the system to adjust the number of active nozzles and the duration of misting periods to maintain local air temperature at the specified range. It provides an alternative to operating at full capacity in a continuum.

Figure 9.

The code developed in Python programming language to examine the correlation between air temperature and percentage of activated nozzles and release periods, when (a) the system responds to the current temperature and (b) the system responds to the rising temperature trend.

In the second phase, the algorithm accounts for the change in the temperature trend instead of the current temperature. It compares current and previous air temperature values to establish if the trend is increasing. If the temperature stagnates or decreases, the system responds to the current temperature value, but if the temperature is rising, the system intensifies water release periods and the number of active nozzles to manage rising heat (Figure 9(b)). The algorithm amends the system’s operation for 60 min following the detection of the increasing temperature trend to pre-empt overheating. The proposed simulation method provides the means to examine the impact of the system’s early activation. Pre-emptive water misting is to help the system avoid catching up with weather conditions since the EC becomes fully effective only after a period of activity. Incorporating the change of air temperature trend instead of only current temperature is the initial step toward developing the system’s predictive capacitates. Such prediction could help to reduce the time gap between peak temperatures and the system’s activation and therefore increase thermal comfort.

In the third modelling phase, an additional input category is added to help develop the predictive capacity of the system. Along with local air temperature values, in this phase, the occupants' count is included in the algorithm as an input parameter that would be provided by pressure sensors embedded in the floor surface. At this research stage, occupancy count is generated randomly to enable structuring the computational technique before the real-life data would be available, as the proposed use of occupants count requires continuous monitoring over a prolonged period. From this provisional data set replacing values that would be taken at ten-minute intervals, the peak usage times are established first. The value determining the peak usage is the total of six occupants detected within 10 m² in six measuring’s times. During an hour leading to peak occupancy established in that way, the algorithm intensifies EC through longer release periods and more active nozzles (Figure 9). In actual implementation, a developed version of the proposed algorithm would enable the system’s activation ahead of the peak occupancy periods. The presented simulation allows for an evidence-based evaluation of the system’s operation when deployed to achieve favourable conditions during peak usage. It shows how beneficial occupants' detection is, in addition to air temperature, in informing the operation of the EC system. To that end, the concept for developing a more robust computational technique is presented at the end of the next section. (Figure 10)

Figure 10.

The code developed in Python programming language to examine the correlation between air temperature and percentage of activated nozzles and release periods, when the system responds to the rising temperature trend and occupancy peaks.

Results

Results obtained through simulation are presented as graphs illustrating the correlation between input parameters and the system’s performance. The graph resulting from the first phase shows the system response to the current air temperature (Figure 11). The graph resulting from the second phase shows systems adjustment to the rising temperature trend (Figure 12). And the graph resulting from the third phase shows a combined response to the rising temperature trend and potential occupancy peaks (Figure 13). Colour coding is consistent across the three graphs capturing each simulation phase. The green curve shows measured temperature values [°C], while blue and red lines are for the two parameters capturing the system’s performance, water release periods [min] and percentage of active nozzles %. The orange curve, shown in the third graph only, is for the occupancy count, an input taken into consideration only in the third phase.

Figure 11.

Phase 1 Graph showing the correlation between air temperature and percentage of activated nozzles and release periods, when (a) the system responds to the current temperature and (b) the system responds to the rising temperature trend.

Figure 12.

Phase 2 Graph showing the correlation between air temperature and percentage of activated nozzles and release periods, when the system responds to the rising temperature trend.

Figure 13.

Phase 3 Graph showing the correlation between air temperature, occupancy count and percentage of activated nozzles and release periods, when the system responds to the rising temperature trend.

The graphs show that all three presented operation modes generate considerably less humidity than if the system would operate continually at total capacity. Statistical overview identifies the potential benefit of introducing an algorithm to control the system’s operation instead of simply choosing between on and off state. The comparison between the first two modes of operation reveals exactly how much more humidity resulting from longer release periods and a higher percentage of active nozzles is generated if the increasing temperature trend change is taken as the input instead of only current temperature values. The final graph shows that the combined response to the rising air temperature trend and predicted occupancy peaks would further increase the duration of water release periods and the percentage of active nozzles.

In the third phase, the system responds to the current air temperature, temperature change trend and occupancy peaks. These occupancy peaks are established in advance and from the randomly generated occupancy data set. The role of such a dataset is only to help structure the simulation model. In a real-life scenario, the data set enabling prediction would be acquired over a prolonged period and would require more than a linear relation between values measured from the environments and the system’s performance. We, therefore, establish a concept that would alleviate potential shortcomings of the oversimplified correlation between input and output parameters. The approach based on advanced computational techniques would be developed using data generated via presented simulation means. For this purpose, the presented algorithm is developed further to generate a database of scenarios capturing input parameters, including air temperature, the change of air temperature trend and the occupancy count, along with output parameters describing the performance of the system, as a combined impact of release periods and percentage of active nozzles. These scenarios would be used to train the computational system and develop a pattern recognition technique to optimise the EC system’s operation further.

This research phase remains at the conceptual level but also results in a tool and a way to generate and structure data needed for further computational development. The algorithm uses the provisional occupancy count and historical meteorological data for the specific location to generate any number of scenarios defining the system’s response. Scenarios include the timestamp, air temperature and occupancy input values, and a set of numeric values describing the output as the actual performance observed across the prolonged period. The sample database we have created includes 1000 scenarios capturing parameters across 8-h periods. The performance of the system is proportional to the number of active nozzles and the duration of release periods, maintaining consistency with the simulation modelling presented in the previous section. However, the proposed upgrade includes significantly more data that is structured to enable easier and more reliable overlaps. Data scenarios include input values to enable their further correlation with output parameters. Output values are given as current and in the context of past measurements to enable more comprehensive pattern recognition.

Discussion

There is an increasing interest in adapting indoor climates according to occupants' behaviour.²⁵ But it is not the same in the research concerned with outdoor environments because it is more challenging to control microclimates in the open air. This study is inspired by the expanding field of research on indoor climate control incorporating human behaviour.²⁶ It relates to approaches addressing indoor climate control through the use of sensing devices and computational techniques.^28,30 And it develops a computational technique specific to EC systems in outdoor environments by formulating a particular computational context and introducing a three-phase algorithm. The proposed technique focuses on air temperature and humidity as the principal parameters, while it allows for adding additional climatic factors relevant for outdoor climate control, such as wind speed and direction. In the Background research section of this paper, it is identified that these parameters are critical for the operation of EC in outdoor environments, as is the ability of the EC system to adapt to changes in its climatic context.^20,23,24 Therefore, the proposed technique departs from the approach based on maintaining fixed climatic conditions, develops a way to respond to climatic changes and introduces occupancy count in its final phase to further examine the system’s operation and develop a predictive capacity. Such examination would help balance thermal comfort and resource consumption in outdoor conditions and enable further research into EC systems application in outdoor environments with goals and tools analogous to those utilised in studies addressing the occupant component in indoor climate control.^29,30

The presented the modular solution can be applied at a large scale in different climatic contexts and respond to changes in the surrounding environments. The findings of other researchers have established that multiple small-scale, strategically distributed water-based mitigators could be effective for large outdoor areas.^20,22 We, therefore, explore the use of the modular solution comprising a mechatronic system, water supply components and a supporting structure. The presented results show how the proposed module could help mitigate overheating in outdoor urban areas and enable further research. The three presented simulation phases, examining different interactions between the module and the surrounding environment, outline the development of the advanced computational system and provide the basis for prototype production. Therefore, the outcomes of this study have both practical dimensions and the capacity for further development through research that combines architecture and computer science. The presented evidence-based technique allows further testing and examination of how the system interacts with the context to enable the inclusion of more input parameters and a more comprehensive understanding of such interaction.

The exchange between the EC system and its climatic context is identified as essential in our preliminary research.^6,7 The presented results include an algorithm developed to adjust the system’s performance according to locally measured air temperature and occupancy levels. It controls the release of water vapour and minimises humidity generated by the system, thus making it more efficient and applicable in varied climates and not only in hot and arid conditions, where EC is traditionally used. The presented research focuses on the correlation between locally measured temperature, occupancy count and the amount of water released by the system that is the main contributor to air humidity. Future research development would include other climatic parameters. In the first place, it would address the system’s response to wind speed and direction, followed by the inclusion of solar irradiation and a more comprehensive understanding of outdoor thermal comfort using indices and quantitative means.

Our background research also suggests that to date, no conclusive method for evaluating the performance of outdoor evaporative cooling systems has been established.²⁰ Therefore, one of the contributions of this study is the evidence-based technique that generates statistical graphs showing a correlation between the key input and output parameters. The proposed technique would serve the purpose to reduce the amount of water discharged into the air while controlling the local temperature and help determine the most efficient pattern of water vapour discharge. For example, the technique could help establish if extended periods with lower intensity could be more efficient in controlling local air temperature and generate less humidity than shorter periods with higher intensity of vapour emission according to the given climatic context. Furthermore, we present an approach to creating a database of scenarios with structured measurements of climatic conditions, occupancy and performance. The database would be used to train the computational systems and develop pattern recognition algorithms. The development of the advanced computational system remains at the conceptual stage requiring further interdisciplinary collaboration, while the simulation model and the algorithm we have developed enables testing of the system ahead of the real-life trials. The limitations to this study arise from the reliance on occupancy detection means to study human behaviour, and future research would focus on including more complex aspects of human behaviour into the account. The proposed technique focuses on identifying a data pattern of measured values leading to occupancy peaks and, therefore, maximising its effect by reducing the time gap between peak occupancy times and the system’s activation.

The continuation of this study would benefit from deploying the proposed module and testing in real-life conditions. Besides enabling a more comprehensive examination of the interaction between the proposed system, local climate and occupants’ behaviour are discussed in the previous paragraphs; it would empower further design studies of how the proposed system fits into the built environment and how it could become an architectural element that improves the amenity of outdoor public spaces. Our design precedent review revealed that EC has been effective and, at the same time, very rarely employed by architects in the past. Our background research shows that to date, only a limited number of water misting prototypes are constructed for research purposes and that these do not address challenges involving their architectural role as physical objects that could be implemented in streets and squares.

Conclusion

The contribution of this study is threefold. It provides a design solution for a modular EC unit composed of the mechatronic system, water supply infrastructure and supporting structure. Secondly, it presents an evidence-based technique for the evaluation and control of the EC system’s performance. And finally, it offers a conceptual proposal for developing advanced computational methods to develop systems capacity further to respond to its environmental context and occupancy detection. Future research is to focus on creating a more robust correlation between human behaviour and climatic input, along with facing challenges for real-life implementation.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the University of Melbourne

ORCID iD

Djordje Stojanovic

References

Kim

Brown

. Urban heat island (UHI) intensity and magnitude estimations: a systematic literature review. Sci Total Environ 2021; 779: 146389.

Pena Acosta

Vahdatikhaki

Santos

, et al. How to bring UHI to the urban planning table? A data-driven modeling approach. Sust Cities Soc 2021; 71: 102948.

Memnon

Leung

DYC

Liu

. A review on the generation, determination and mitigation of Urban Heat Island. J Environ Sci 2008; 20: 120–128.

Dominguez

de la Flor

FJS

. The effect of evaporative cooling techniques on reducing Urban heat. In: Santamouris

Kolokotsa

(eds). Urban Climate Mitigation Techniques. London, UK: Routledge; 2016.

Osmond

Sharifi

. Guide to Urban Cooling Strategies. Sydney, NSW: Low Carbon Living CRC, 2017.

Ulpiani

Di Giuseppe

Di Perna

, et al Thermal comfort improvement in urban spaces with water spray systems: Field measurements and survey. Building Environ 2019; 156: 46–61.

Farnham

Nakao

Nishioka

, et al Study of mist-cooling for semi-enclosed spaces in Osaka, Japan. Proced Environ Sci 2011; 4: 228–238.

PWP Landscape Architecture. Cambridge, MA: Tanner Fountain, Harvard University, www.pwpla.com/projects/tanner-fountain-harvard-university (1984, accessed 20 July 2021).

JML. Le miroir d’eau France, UK: place de la Bourse Bordeaux. www.jmlwaterfeaturedesign.com/en/projects/le-miroir-deau-place-de-la-bourse (2006, accessed 20 July 2021).

10.

Ecosistema Urbano. The Eco-Boulevard in Vallecas. Madrid, Spain: Ecosistema Urbano. www.ecosistemaurbano.com/eco-boulevard/ (2007, accessed 20 July 2021).

11.

Soutullo

Olmedo

Sánchez

, et al Thermal conditioning for urban outdoor spaces through the use of evaporative wind towers. Building Environ 2011; 46: 2520–2528.

12.

Banham

Dallegret

. A Home is not a House. Art in America 1965; 4: 70–79.

13.

Lally

. Architecture of an Active Context. In ACADIA 2012: Synthetic Digital Ecologies, Proceedings of the 32nd Annual Conference of the Association for Computer Aided Design in Architecture, San Francisco, CA, 18–21 October 2012, pp. 269–276.

14.

Fox

Kemp

. Interactive Architecture. New York, NY: Princeton Architectural Press, 2009.

15.

Munitxa

Bogosian

. Sensing Urban Microclimates. In ACADIA 2015: Computational Ecologies: Design in the Anthropocene, Proceedings of the 35th Annual Conference of the Association for Computer Aided Design in Architecture, Cincinnati, OH, 22–24 October 2015, pp. 483–496.

16.

Noy

. A conceptual design of a wireless sensor actuator system for optimizing energy and well-being in buildings. Intell Buildings Int 2010; 2(1): 41–56.

17.

Yamada

Yoon

Okumiya

, et al Study of cooling system with water mist sprayers: fundamental examination of particle size distribution and cooling effects. Building Simulation 2008; 1: 214–222.

18.

Huang

Zhao

, et al. The research and application of spray cooling technology in Shanghai Expo. Appl Therm Eng 2011; 31: 3726–3735.

19.

Ulpiani

di Perna

Zinzi

. Mist cooling in urban spaces: understanding the key factors behind the mitigation potential. Appl Therm Eng 2020; 178: 115644.

20.

Ulpiani

. Water mist spray for outdoor cooling: a systematic review of technologies, methods and impacts. Appl Energ 2019; 254: 11364.

21.

Altaf

Klabwisas

Thu

, et al Performance of the outdoor evaporative cooling: A case study of Thammasat University Rangsit campus. In: ICUE 2020 on Energy, Environment, and Climate Change, Pattaya, Thailand, 20 – 22 October 2020. Asian Institute of Technology.

22.

Santos Nouri

Costa

Santamouris

, et al. Approaches to outdoor thermal comfort thresholds through public space design: a review. Atmosphere 2018; 9: 108.

23.

Desert

Naboni

Garcia

. The spatial comfort and thermal delight of outdoor misting installations in hot and humid extreme environments. Energy and Buildings 2020; 224: 110202.

24.

Ulpiani

di Perna

Zinzi

. Water nebulization to counteract urban overheating: development and experimental test of a smart logic to maximize energy efficiency and outdoor environmental quality. Appl Energ 2019; 239: 1091–1113.

25.

Park

Ouf

Gunay

, et al A critical review of field implementations of occupant-centric building controls. Building Environ 2019; 165: 106351.

26.

Osman

Ouf

. A comprehensive review of time use surveys in modelling occupant presence and behavior: data, methods, and applications. Building Environ 2021; 196: 107785.

27.

Jian

Liu

Pei

, et al. Occupants’ tolerance of thermal discomfort before turning on air conditioning in summer and the effects of age and gender. J Build Eng 2022; 50: 10409.

28.

Anik

SMH

Gao

Meng

, et al. A cost-effective, scalable, and portable IoT data infrastructure for indoor environment sensing. J Building Eng 2022; 49: 104027.

29.

Brik

Esseghir

Merghem-Boulahia

, et al Providing convenient indoor thermal comfort in real-time based on energy-efficiency IoT network. Energies 2022; 15: 808.

30.

Chaudhuri

Soh

, et al. A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings. Appl Energ 2019; 248: 44–53.

31.

Kuras

Richardson

Calkins

, et al. Opportunities and Challenges for personal heat exposure research. Environ Health Perspect 2017; 125(8): 085001.

32.

Dhariwal

Manandhar

Bande

, et al. Evaluating the effectiveness of outdoor evaporative cooling in a hot, arid climate. Building Environ 2019; 150: 281–288.

33.

Di Giuseppe

Ulpiani

Cancellieri

, et al. Numerical modelling and experimental validation of the microclimatic impacts of water mist cooling in urban areas. Energy and Buildings 2021; 231: 110638.

34.

Farnham

Zhang

Yuan

, et al. Measurement of the evaporative cooling effect: oscillating misting fan. Building Res Inf 2017; 45: 783–799.

35.

Elgendawy

Davies

Chang

H-C

, et al Planning for cooler cities: a plan quality evaluation for Urban Heat Island consideration. J Environ Pol Plann 2020; 22(4): 531–553.

36.

Nakaya

Duguet

. Fujiko Nakaya Fog. Paris, UK: Anarchive, 2012.

37.

DS+R. Blur Building, www.dsrny.com/project/blur-building (2002, accessed 20 July 2021).

38.

Breathe Austria. Making of Breathe Austria, www.breatheaustria.at/making-of-breathe-austria-austrian-pavilion-expo-milan-2015 (2015, accessed 20 July 2021.

39.

DELWP Victoria State Government. Urban Design Guidelines for Victoria. Melbourne, VIC: DELWP Victoria State Government, 2021, https://www.planning.vic.gov.au/policy-and-strategy/urban-design/urban-design-guidelines (accessed 20 July 2021).

40.

Stojanovic

Vujovic

. Towards Prediction and Optimization for Outdoor Evaporative Cooling Systems in Architectural Design. In: Towards a new, configurable architecture, the Proceedings of eCAADe 2021 Conference (eds Stojakovic

Tepavcevic

), Novi Sad, Serbia, 08-10 September 2021, paper no. 153, pp.401–408.

41.

Meteoblue. Weather database, www.meteoblue.com (2021, accessed 20 July 2021.