Among public buildings, museums represent a special case with respect to environmental management. Not only do they have to be comfortable to humans, but must also provide conditions that adhere to more stricter environmental standards in order to preserve the cultural heritage objects in their custody [1
]. There is an ongoing discussion regarding the general applicability of these standards and there are studies focused in assessing the possibility of establishing wider windows of temperature/humidity conditions tuned more specifically to distinct kind of objects [2
]. This is a very ambitious, although necessary endeavor, since the confluence of higher energy costs and the effects of climate change will be affecting the way buildings are constructed, refurbished and managed [5
Depending on the building, there may be competing effects from mechanical cooling/heating and the location, age, and construction material of the buildings. The outdoor conditions may play a role in changing the indoor conditions, sun may warm some walls or windows during daytime while in the winter time excessive cooling may occur that could result in condensation. Additionally, as doors are opened for visiting groups of people, drafts may propagate across multiple rooms and potentially connect the indoor to the outdoor environment. The inherent dynamic changes in the environment are hard to capture with a limited number of sensors and there is a need to better understand how these fluctuations may change daily or seasonally. Furthermore, architectural design and Heating, Ventilation and Air Conditioning (HVAC) operation can lead to the formation of microclimates that are distinct from their surroundings. Any approach to change museum environmental conditions based on existing standards will have to be based on longer term and robust results to be accepted both by private art collectors/donors of art and also by insurance companies [6
Towards that goal, the first necessary step is to have information of the dynamics of the environmental fluctuations inside the buildings in a comprehensive way throughout long periods of time to ascertain seasonal, architectural and visitor’s impact on the local micro-environment [1
Typically, HVAC systems are designed to operate in a quasi-steady state with feedback to the established operational settings relying generally on sensors located at the supply and return vents of the rooms. Closed control loops may be employed to maintain temperature or relative humidity constant with minor fluctuation around the set-points. However, using a single or a handful of sensors may not be enough to predict in a comprehensive way the micro-environmental fluctuations. Generally, the physical environments of art exhibitions are intrinsically complex, responding to prior architectural design (churches, castles, ancient buildings) and many times cannot be modified. Thus, new platforms [7
] aiming at providing a denser mapping of environmental conditions are desirable to understand how new environmental standards may affect current collections [1
]. Furthermore, a correlation of this local dynamic environmental information with the response of the art pieces should be a necessary part of the endeavor [18
]. This correlation is a very laborious task which needs to encompass not only measuring the response of suitable test vehicles in a laboratory coupled with modeling [21
], but also the assessment of the validity of such models by directly monitoring the actual works of art. The latter presents its own set of difficulties since often it has to overcome curatorial distrust regarding the appearance, position and possible damage to the object by sensors.
Wireless sensor networks have evolved to fulfill the application of dense and precise measurement of environmental conditions in real time [10
]. Such precise measurement can be done even under dynamic conditions, when air is mixed from the top to the bottom of each room, and temperature and air humidity are acquired at the same air pressure (e.g., Mollier diagrams) [23
]. The advantage of wireless sensors is the ability to combine sensing, analytics and control while being easily deployable in existing galleries and being easily repositioned as required by changing exhibitions. The wireless sensor network eliminates the traditional need of extension cables to provide power and capture sensor data, while the sensors’ small size allows them to be placed nearby art objects without being visually obtrusive. The second advantage of wireless sensing is the embedded computational capability that enables multiple sensing points to be attached to the same radio-transmitter, thus reducing the cost per sensing point.
Beyond the traditional sensor signal monitoring of temperature, relative humidity, air flow or pressure, recent trends are to create platforms that would include additional sensors like noise, illumination, and air quality sensing. These new sensing platforms are going beyond simple environmental monitoring, as they try to quantify in real time the impact of fluctuating environmental conditions on exhibited objects [18
]. One other possibility is a control mechanism where optimization of the environment can be implemented based on constrains (like optimizing the number of people in galleries such that temperature and humidity will not fluctuate outside a desired range). Recently wireless sensor networks were applied to adjust illuminations in galleries and demonstrating that a wireless node can act simultaneously as a sensor and actuator [26
]. Dense sensor networks are enabling a holistic understanding of how the local microenvironment are dynamically changing in the museum.
Beyond environmental monitoring, there is a sustained activity in optimizing wireless communications and ensure that data integrity, security and dynamic sampling can be easily integrated. Many of the current research areas [27
] focus on energy efficient routing, congestion control, congestion avoidance, extending connectivity and expanding coverage. All these advancements can expand current monitoring platforms capabilities by enabling dynamic data sampling and modeling based on automatically triggered events.
This paper describes the sensing platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, and presents examples of the kind of local environmental information obtained as well as physical analytical modeling of the sensed data as correlated with outside conditions and visitor flow. In this project, the Low-power Mote Technology (LMT) by IBM (Armonk, NY, USA), along with IBM’s Measurement and Management Technologies (MMT) solution, were utilized. The MMT platform supports sensor anomaly detection, real time data processing and thresholding. Furthermore, physical based models can be used to interpolate values from the collected sensor data at the sensing points [32
]. LMT supports several types of sensors, for the various measurements of interest in a museum and their characteristics will be discussed in the corresponding sections.
The Cloisters is characterized by distinct historical and architectural features. For stylistic reasons, the design of The Cloisters centers on a massive masonry construction. Like many medieval castles in Europe, the building was also meant to conserve heat during winter and reduce thermal gain during the summer. However, the composite nature of the building, with medieval stone windows inserted in a modern matrix, and galleries opened to gardens, somewhat limits the quality of the envelope. At its inception in 1938, The Cloisters were heated by the standards of the day with oil heat, but no provision was made for air conditioning, or full humidity control. At the time, architects wanted to minimize the use of modern mechanical systems, to create an intimate relationship between visitors and the collection. Reducing their size to the utmost reasonable limit, the visual appeal of heating grilles was just as, if not more important, than their efficiency. The system provided some humidity in the winter, so the relative humidity (RH) values would not drop below 30%, but no dehumidification was performed throughout the year. The relative humidity ranged between 50% and 90% during the summer, falling down to 30% in the winter, with temperatures in summer frequently above 27 °C, and wide fluctuations throughout, especially in the spring and in the fall. It is mentioned in the museum archive that in order to avoid condensation on the stained glass collection, the entire air washing system was turned off to provide humidity when the outside air fell below −12 °C [21
]. Despite the introduction of an air washing systems, pollutants caused by oil heating, mostly chlorides and sulfates, are mentioned in early museum reports. In 1969, a “demineralizer” was introduced in the Campin and the Tapestry rooms (see Figure 1
A for a floor plan), along with a localized controlled environment. In 1987, the Treasury room was equipped with a similar system [33
]. It is only in 2005 that the long deferred task of installing a full-scale climate control system throughout the galleries was finally realized at The Cloisters. However, some specific issues are still being addressed, such as the problem of condensation on windows.
Condensation is quite common in temperate climates due to the thermal gradients that form across the window panes when the indoor/outdoor weather conditions are significantly different. In general, glass is considered to be a relatively stable material, but it can deteriorate in inadequate environmental conditions, depending on the chemical composition of the materials used in its production. For example, by prolonged contacts with liquid water or highly moist air in acidic environments, alkaline and alkaline earth metal ions in glass are exchanged by hydrogen containing ions from water, and are leached out to the surface, forming a hydrated layer. In alkaline environments hydroxide ions from water attack the silicate network of glass, thus causing the glass dissolution [34
]. Glass rich in potassium and calcium contents, which was often used for medieval stained glass windows, is typically vulnerable to the former alteration process. The formation of a hydrated layer at the surface leads to various degradation phenomena, such as formation of micro cracks, pits, crystalline efflorescence and encrustation. In order to prevent stained glass from those environmentally induced weathering phenomena, the installation of protective glazing [35
], which is a transparent sheet material (modern, more stable glass or plastic) placed at the outside of the original window, is widely adopted. Still, even after the installation of protective glazing, air circulation in the interspace between the original window glass and protective glazing is an important factor to prevent the condensation and high humidity [36
]. Condensation risk can be assessed using forecasted weather data combined with models that predict heat conduction across glass windows. We discuss such a model that was developed for day ahead prediction of condensation risk during winter months.
Air quality is an important aspect of indoor environmental condition in museum as chemical pollutants may impact metal, wood and textile objects. Most commonly the air quality is assessed using metal coupons (silver, copper, lead) exposed to the environment and quantifying the corrosion product building up on the surface. Air quality standards are developed to quantify the maximum amount of pollutants that can be tolerated in museum environments. In this study corrosion sensors fabricated from silver and copper were deployed in multiple galleries to measure long term trends in air quality change, and the MMT platform calculated in real time the corrosion rate of the sensors based on a sliding window algorithm [37
]. While our study demonstrates that the environmental conditions within the galleries are very stable, the dense sensor networks installed in 5 galleries enabled micro environmental studies of visitors’ impact and long term air quality. The data from the dense sensor networks can be used to improve long term microclimate understanding in galleries, provide real time insight into short term fluctuations, and quantify the connection between the indoor and outdoor climates.
2. Materials and Methods
2.1. Monitoring Technology
There are several monitoring technologies for museums and their common, desirable characteristics is that they should: (1) provide sensitive, accurate and high frequency measurements for an extended period of time and (2) be visually unobtrusive—e.g., no visible probes or wires around art objects. Wireless sensor networks fall within these categories, allowing untethered devices to be powered by batteries, which can be hidden behind works of art [38
]. Since our interest is developing accurate microclimate models within a museum, it is necessary to have multiple sensing points in every gallery that facilitate dense monitoring in space and high frequency in time (one data point per minute). As a monitoring technology we use a wireless sensor network platform, where the radios (called motes due to their small form factor) provides automatic data collection. Motes are composed of sensors, a microcontroller, and a radio. Sensor data can be acquired continuously at fixed time intervals or data acquisition can be triggered by external signals that can be used to start the data collection and to determine its duration. One aspect that sets apart our monitoring platform from other platforms [11
] is the integrated analytics and modeling capabilities, beyond data acquisition, that convert raw data measurements into information that can be easily used by curators. Furthermore the power efficient sensors combined with advanced wireless communications allow extended period of operations on batteries without the need for frequent replacement.
The spatial coverage of the sensor deployment is shown in the floor plan in Figure 1
A where the motes were placed at different heights in the galleries. For example, in the Late Gothic Hall the sensor placement height ranged from 0.5 m up to 11 m. One driving consideration for sensor placement was the investigation of temperature stratification in galleries and second acquisition of enough sensing points for modeling. The majority of the motes were placed around art objects in close proximity of walls and were concealed to not interfere with the aesthetics of display art objects. The temperature and humidity sensors were positioned to face the gallery and air was allowed to freely flow across the sensor surface.
The data from the wireless sensor network is supplemented with external data sources like outdoor weather and air quality measurements. The real time data stream from motes enables an immediate insight on environmental changes due to visitor flow or change in air quality.
A typical sensor mote, with a default one temperature and one humidity sensor integrated into the processing board, is shown in Figure 1
B. Additionally the following sensors can be added to the motes: air quality, visitor presence, and door position. Next we briefly mention the basic characteristics of each sensor and its purpose. All of the sensors use high precision components (some off-the-shelf and some custom-developed at IBM) and are implemented using low power design in order to prolong the mote battery lifetime and thus minimize the number of required maintenance steps.
The temperature transducer is based on a semiconductor diode element (TMP112 with 12-bit resolution, Texas Instrument, Dallas, TX, USA) with an accuracy of 0.5 °C. For example, air temperature measurement is used for evaluating the thermal stratification along the height of a gallery and also slight temperature gradients between different galleries. The relative humidity (RH) sensor is based on a capacitive element (SHT21, 14-bit resolution, Sensirion, Stafa, Switzerland), with an accuracy of ±2%. The RH transducer is useful for evaluating air moisture levels. There are also alternative high precision humidity measurement methods based on capacitance changes like quartz humidity that are characterized by high sensitivity, high temperature stability, immunity to electromagnetic interference and fast response time. The differential sensors and the new switching sensor methods are cost effective while at the same time fulfill the requirement for high precision measurements [39
The dew point was calculated from temperature and relative humidity measurements and is as an indicator of condensation risk on windows, water condensation over painted glass or appearance of condensation on the walls. Dew point measurements are also relevant to understand the acceleration of corrosion rate measurements that relates to air quality consideration within the museum.
All the deployed sensors were adjusted by comparing their data with those of calibrated scientific level temperature and relative humidity sensing devices by exposing them to the same ambient environment. Temperature and relative humidity sensors readings were within the sensors accuracy specification and were compared with calibrated sensors used by curators during the study period. We note, that the long term stability of LMT sensors were validated in a data center environment [41
The air quality sensor uses a chemically sensitive resistive element to detect pollutant gas concentrations (Figure 1
C). The resistive air quality sensor measures the change in the film thickness as gaseous molecules get absorbed on the metal film surface and transform the top layers of the sensor element from metallic to insulating layer. As a way of example, sulfur-bearing gases will get absorbed on the silver surface and transform it into silver sulfide (Ag2
S). While silver is electrically conductive, Ag2
S is nonconductive and reduces the physical thickness of the conductive layer increasing the resistance of the metal layer. Similarly, moisture on the top of a copper sensor in combination with sulfur bearing gases will form Cu2
S and CuO. Both silver and copper thin films are used to determine the rate at which the film thickness is changing. Silver sensors are very sensitive to interaction of sulfur bearing gases (H2
) while copper is sensitive to the combined effect of SO2
gases. Other contaminants like CO2
will not impact corrosion sensor reading but their minimization is important to maintain visitor comfort in the museum. The resistive signals from the air quality sensors are digitized by a 24-bit resolution analog-to-digital converter. Corrosion sensor reading were validated using side by side comparison with metal coupons whose corrosion byproduct was measured using coulometric reduction [42
]. The corrosion rate readings for both techniques are within 10% which is comparable to the accuracy in measuring film thickness in both techniques. Both corrosion measurement techniques were used in the past to create ASHRAE standard recommendation for air quality control in mission critical facilities [43
Some LMT motes have a movement sensor, which is based on a passive infrared diode. These motes are strategically placed within galleries (i.e., access points, particular art objects of interest) and their measurements help estimate the number of visitors in a given gallery. Automatic measurements of visitors’ paths in a given gallery can be valuable to learn about their cultural interests and also, in general, for space utilizations in order to arrange exhibitions such that crowding can be avoided. Estimating the number of visitors in real-time is also useful for modeling the relationship between human presence impact on microclimate—below we expand on this point.
Finally, based on the architectural design of the museum, direct external air flow is possible through corridors and galleries. To account for these effects, LMT has sensors that monitor the position of several doors—detect when each of the doors is open or closed. The insight provided by a simple reed switch is relevant to use it in the models discussed below—given that the doors are a direct link between the galleries and the outside climate.
2.2. Modeling Techniques
Two different types of modeling were implemented, each with its own particular characteristics, which utilize the data produced by our sensing technology. The sensor data serves for both techniques as a set of boundary data.
For the first modeling technique an interpolation method is used, where temperature and air moisture are estimated using a smooth bivariate interpolant to the scattered sensor data that is locally a quintic polynomial in two variables [44
]. This method is valid in locations where the temperature is smoothly varying on short distances (Figure 2
A) but most likely is losing accuracy near air inlet and outlet in galleries. We note that display cases and large objects are excluded from the simulations (white rectangular areas in Figure 2
A). Clearly, this method quickly loses accuracy with increasing distance from the sensor. Sensor data interpolation is however useful in case a real-time control of the environmental conditions needs to be implemented, for example to eliminate condensation on the windows.
The second type of modeling comprises physics-based models, incorporating Computational Fluid Dynamics (CFD), which provide very detailed environmental conditions of the museum galleries. CFD modeling is the basis for microclimate models and it uses sensor readings from the wireless sensor network as input for prescribing boundary conditions. The CFD models also require a mesh of the physical space, i.e., the dimensions, the location of windows and doors, objects of art, etc. The CFD model implemented generates air flow and temperature distribution across the whole three dimensional space. Specific details of the CFD model, including the use of sensor data for prescribing boundary conditions, are provided in [45
]. Here we note that the East wall of Late Gothic Hall displays a historic tapestry hung from the top. Temperature distributions resulting from the simulations along the wall could then be used as input data sets for tapestry modeling to understand fabric expansion under temperature and humidity variation in the gallery [46
]. Having three-dimensional temperature distributions (Figure 2
B) would also enable museum curators to pinpoint the most stable locations in the galleries (i.e., with fewest environmental fluctuations). Furthermore, CFD modeling would allow conducting other studies, such as analyses of the impact people (which can be represented as moving heat sources in the model) may have on micro-climatic conditions and works of art housed in the museum.
With the interpolation and the CFD models, it is possible to simulate important physical phenomena in the heat and mass transfer process, like natural convection (buoyancy effects). The latter is an important factor to take into account within the context of simulating heat and mass transfer inside buildings. Furthermore, a hierarchy of models of varying complexity can be included as part of the framework. For instance, in addition to temperature sensor data, a model may take relative humidity sensor data as input in order to simulate the distribution for the air moisture in a room, in addition to that of air and temperature [32
In general, CFD modeling is computationally more intensive than statistical modeling, but CFD it is more accurate. In the museum context, CFD modeling is useful for planning installations of works of art and for achieving long term object preservation goals. Interpolation models, being faster but less accurate, are useful for continuous optimization and adjustments of the HVAC systems of the museum.
2.3. Museum Characteristics
The Cloisters has multiple galleries with tall ceilings, interconnected with open corridors. The museum has large stained glass windows and several doors that directly connect most of the galleries to the outside environment. The physical characteristics of the museum or building envelope, i.e., its walls, windows, doors, and roof, affect the heat loss rate of the building.
Psychrometric charts are commonly used by building managers to quantify the stability of the environmental conditions using the dew point and air mixing ratio as a measure of the moisture in the air. The dew point quantifies the amount of moisture in the air, while the mixing ratio measures the amount of water (expressed in grams) in one kg of dry air. Psychrometric charts are usually plotted with data from an extended period of time, in order to capture seasonal changes. In this study, we aggregated the data from all sensors (Figure 3
) across a one year period to demonstrate the very stable environmental conditions within the monitored galleries [47
]. There are more than 1 million data points plotted in the image and only less than 1% of them are outside of the recommended range. The negligible number of outlier points in the psychrometric charts indicates the very stable environmental conditions in the galleries.
Simultaneous monitoring of the environment in multiple galleries and entrance doors status (open/close) enables one to detect air circulation from the main entrance to other galleries. The dew point gradient changes across multiple galleries in response to a draft from an open door. One such case is shown in Figure 4
, where the dew point drop in the main entrance halls is propagated throughout the galleries. Three of such events are highlighted by the red vertical bands across Figure 4
A. If the galleries are farther situated from the main entrance, the changes in dew point are smaller (Figure 4
B). The data was acquired from the period 26 April to 6 May 2013. We note that not all changes observed in the Main Hall can be detected in other galleries. While some of the galleries doors are open during the summer to the inner garden of the Cloister, the temperature and relative humidity remain very stable in the galleries demonstrating the HVAC system can compensate for change in temperature and relative humidity. The HVAC system tended to compensate for changes when doors were opened or to instantaneous environmental fluctuations.
Current standards for environmental parameters in the museums recommend a tight temperature and relative humidity ranges. These standards were established more than 70 years ago and are followed as industry best practices. In many buildings the environmental conditions are measured by one or a few sensors that may not be located in the ideal measurement place (traditionally the sensors are attached to a wall in close proximity of air inlet/outlets). Deploying dense wireless sensing has the advantage to assess the environmental conditions, across the whole building, in all three dimensions and understand air stratification, the environmental connections between rooms and the insulating properties of the building walls, windows and doors.
A good understanding of the microclimates that may form in large galleries or exhibition rooms have the potential to enhance the utilization of the galleries and determine the best location where art objects may be placed with minimized risk. The same principle of microclimates can be easily extended to hospitals, schools, museums, convention centers and eldercare facilities where air quality and fluctuations in the environmental conditions can have a significant impact on health and wellbeing of people.
There is a need to develop comprehensive platforms that combine sensor data with statistical and physical modeling and contextual information about building layout, building construction material that allow easy access to the data and can be used both as a real time monitoring tool as well as a repository of long term trends. Ultimately these platforms need to be combined with risk models for art objects that can estimate the impact environment on art object in a realistic environment rather than laboratory experiments [24
]. Such efforts should rely on wireless sensor network which can be easily placed and rearranged in these buildings to comprehensively model the environment in areas where sensors cannot be easily placed [10
]. This work is an attempt to establish such baseline sensing and modeling technique where analytics can be used in real time to adjust environmental conditions in response to visitor presence or outdoor air environmental conditions.