Conserving the historic environment: thermal monitoring of The Hill House, by Charles Rennie Mackintosh

Location aided commissioning of building automation devices enabled by high accuracy indoor positioning

Development of an IoT and BIM-based automated alert system for thermal comfort monitoring in buildings

Maintenance is crucial for any building throughout its entire lifespan. The primary goal of building maintenance is to maintain all components and facilities in their original and functional condition to ensure continuous efficient operation. The widespread adoption of maintenance software has paved the way for more efficient communication within maintenance management, improving the effectiveness and efficiency of maintenance activities. Previous research has highlighted several challenges in the implementation of Information and Construction Technology (ICT) systems in maintenance management. This study aims to explore the key challenges associated with the use of ICT systems in maintenance management, with a specific focus on office buildings in Malaysia. A qualitative approach was adopted for this study, involving semi-structured interviews. A total of five interviewees were selected from three (3) office buildings. The findings show that two types of ICT systems—the Building Automation System (BAS) and the ARCHIBUS system—were utilised in the maintenance management of the three office buildings. This study identifies various issues and challenges that arise when implementing these ICT systems, including a lack of professional expertise in operating the systems, inaccurate information, risks of connection loss, time consumption, limitations in capability, cybersecurity threats, and financial constraints. Common issues faced across different management teams and ICT systems include a shortage of qualified personnel, time inefficiencies, and limitations in system capabilities. These challenges must be addressed promptly to enhance the efficiency and value of ICT systems in maintenance management. Effective building maintenance in office buildings is essential to ensure that all services and facilities operate smoothly and to prevent any potential downtime.

The smart building having multiple subsystems are gaining momentum due to the growing trend of smart cities. These multiple subsystems interact with each other through a communication channel and coordinate through a building management system (BMS) for the effective operation of the smart building. The communication channels are prone to vulnerabilities (cyber attacks) which may lead to anomalies condition. However, with a proper prediction of future data beforehand various types of anomalies can be avoided. The task of predicting data requires extensive knowledge of the system model as well as the process. In view of this, the paper proposes a prediction technique known as the Dynamic Mode Decomposition (DMD) which can predict future temperature profile data with the help of available past data in an equation-free environment. The temperature data of the major component of BMS i.e. heating, ventilation, and air conditioning (HVAC) system is predicted using past temperature data with the help of DMD. After the prediction of the temperature profile, the concept of a process control chart is used for analyzing the HVAC system as normal or anomalies condition. The effectiveness of the proposed method for prediction of data using DMD where all system states may not be observable and the analysis of predicted data using the process control chart is verified using different test scenarios. Finally, from the result, it can be highlighted that DMD predicts the data effectively without the need for a system model, and the process control chart helps to identify the presence of anomalies.

An inquiry into the use of indoor CO2 and humidity ratio trend data with inverse modelling to estimate air infiltration

The David Booth Conservation department and Building Operations department at the Museum of Modern Art (MoMA), in collaboration with the building automation firm TEC Systems, Inc., developed during the museum’s last expansion a web based platform to monitor, evaluate, alert, and report on environmental conditions in gallery and non-gallery spaces, onsite storage, archives and libraries, conservation studios, workshops, and offices. The platform is connected to the Building Management System (BMS) and draws temperature and percent relative humidity (%RH) data from nearly 300 sensors across all art-containing spaces. TECConnector was developed as a web server on NodeJS and taps directly to the Enterprise Buildings Integrator (EBI) server to query data from historical trends and convert them into JSON formatted objects. This tool has considerably facilitated and enriched the dialogue between the conservation and operations teams, providing tools to better understand and act on the museum environment, while also bringing awareness to the needs of and requirements for collection care.

Post occupancy evaluation and internal environmental monitoring of the new BREEAM “Excellent” Land Rover/Ben Ainslie Racing team headquarters offices

Background/Objectives: To improve a thermal load by increasing internal thermal effect of a building from direct solar radiation through an increase of glass windows.Methods/Statistical analysis: Through the establishment of test beds of the same size, the data of temperature, humidity, solar insolation and PMV of each test bed with or without external louver are acquired to analyze thermal environmental with the simulation.Findings: For the analysis of thermal environment, the amount of energy consumption has been analyzed through the simulation and the data of temperature, humidity, solar insolation and PMV have been acquired for the analysis. With the simulation, about 20% energy saving has been confirmed and the daily averages of temperature and humidity between 8AM to 7PM have been calculated to calculate the maximum temperature difference to be 9.4℃. The solar insolation between 9AM and 7PM was 300W/m2 or below.Improvements/Applications: The improvement of thermal effect with an external louver has been confirmed. It may be applied to the louver system to improve building thermal environment, awning to control direct solar radiation, blind to improve uniformity of illumination intensity toward building during daytime, external blind and ceiling louver system.

Data centers are the key infrastructure for information services. The monitoring of the thermal environment of the data center computer room is an important work for its safe operation. This paper proposed a mobile robotic system for data center thermal environment measurement, which can freely sample the temperature and humidity data around the facilities within the computer room. On one hand, measuring the temperature and humidity in a mobile way can obtain far more environmental data than fixed-point sensors. On the other hand, the mobile robot can be used instead of manual inspection. In addition, a temperature field reconstruction method is provided based on the sampled temperature data. Theoretically, the temperature of locations that have not been measured can be evaluated by interpolating sample temperature around them. The reconstruction of the temperature field can present the variation of the temperature more clearly and help find the hot spots or locations with low cooling efficiency during the operation. Lastly, experiments are carried out to study the measurement error of the mobile robotic system and an error correction method is proposed. After that, the relationship between the temperature reconstruction error and the layout of sampling points is investigated.

A building management system (BMS) established to control the system of building services would not incorporate records of occupants’ views nor integrate real-time occupants’ response for any system fine tuning to satisfy individual demands in a dynamic manner. This study proposes a humanized adaptive baseline information technology (HABIT) algorithm to enable such fine tuning according to the occupants’ feedback to optimize the acceptance of the indoor environment. Apart from solving the complaints from occupants, the proposed algorithm also integrates the collective real-time feedback from end-users with a balance of the imposed design conditions to determine the optimum operation condition of the system. In the study, the temperature set point of an air-conditioning system in certain Hong Kong offices was used as an illustrative example to demonstrate the operation of the algorithm. Survey results on occupants’ views and indoor environmental conditions of the offices were used to determine the input parameters of the algorithm. With the proposed algorithm, HABIT could be used for updating the design set point of the existing BMS. Practical application: This study provides a new notion of humanized adaptive baseline information technology (HABIT) for air-conditioned spaces of a single temperature set point. The occupants’ views and indoor environmental conditions of the offices are used as input parameters of the algorithm in determining the optimum temperature set point for maximizing the occupants’ satisfaction. The algorithm could be built into existing building management systems (BMS) for determining the air temperature set point of a centralized air conditioning system.

The precise assessment of personal thermal comfort (PTC) aims to optimise thermal indoor environments and enhance occupants’ wellbeing and productivity while reducing energy use. Individual variations are investigated using invasive methods like surveys and contact sensors that limit the model’s integration in Building Automation Systems. Vision-based assessments provide non-invasive alternatives. The literature lacks a comprehensive modelling approach that considers PTC factors without overlooking application challenges. The paper proposes a guiding three-phase conceptual framework for vision-based PTC assessment considering personal and environmental factors, with a novel third phase for long-term deployment and enhancement derived from Human-Building Interaction concepts.

The precise assessment of personal thermal comfort (PTC) aims to optimise thermal indoor environments and enhance occupants’ wellbeing and productivity while reducing energy use. Individual variations are investigated using invasive methods like surveys and contact sensors that limit the model’s integration in Building Automation Systems. Vision-based assessments provide non-invasive alternatives. The literature lacks a comprehensive modelling approach that considers PTC factors without overlooking application challenges. The paper proposes a guiding three-phase conceptual framework for vision-based PTC assessment considering personal and environmental factors, with a novel third phase for long-term deployment and enhancement derived from Human-Building Interaction concepts.

The use of CO2 as a pumped secondary volatile heat transfer medium is demonstrated for a server room application. The condenser of the primary refrigerating system using propane comprises an additional air cooled heat exchanger for condensing CO2 when the ambient temperature is sufficiently low. This free cooling arrangement reduces the compressor operation time to less than 30% of the year in the Danish climate. The performance has been measured and recorded by utilising the building management system and the refrigeration plant controller, and it is evaluated against the design conditions. Characteristics of the control system are analysed, and observations during the first years of operation are reported. Measurements confirm that that the free cooling system alone will maintain the design cooling capacity of 100 kW supplying air at 25°C to the server room, when the ambient temperature is 13°C or lower. The design pressure is 70 bar for the CO2 cycle and evaporation temperatures close to 20°C have been recorded at part load conditions.

Building Systems Division of Yamatake-Honeywell Co., has developed a new TY4700 Comfort Sensor that revolutionizes indoor comfort control. Thermal comfort depends on many factors-the new sensor's output temperature signal is a combination of air temperature, radiant temperature and air velocity. The comfort sensor consists of a sensor unit and a processor unit. The sensor unit has a compact, light but accurate compound sensing element which detects air temperature, radiant temperature and air velocity. The processor unit uses the input data to provide an output signal representing the room's thermal comfort/discomfort factor. Building automation (BA) systems can combine this output with humidity data and stored knowledge of tenant's clothing and physical activity to calculate the ISO7730 standard Predicted Mean Vote (PMV) thermal comfort index, which ensures maximum comfort for tenants and minimum energy expenditure for building operators. >

Indoor thermal environment simulation of jade carving design process based on light sensing texture image processing