Buildings account for a significant portion of global energy consumption and CO2 emissions. The construction sector, which includes both building and operation, contributes for 30–40% of global energy consumption emissions, air pollution, and global warming are all caused by the burning of fossil fuels. S. W. Hadley et al. Utilised a climate prediction model to estimate temperature changes up to 2025, with the lowest expected temperature fluctuation resulting in a 1.09 quadrillion British thermal units (BTU) energy increase for building cooling/heating. While renewable energy consumption and use may boost a country's GDP (gross domestic product), fossil fuel energy use has a major negative impact. Common ways to making buildings more efficient and sustainable concentrate on optimising building control systems utilising automation rules and dashboard visualisation, as B. Mataloto et al. Did with their Building Management System, or other IoT systems focusing on energy management, as. User participation with monitoring systems has the potential to save energy while also modelling people's behaviour and forming sustainable user communities.
Weather fluctuations, construction activities, adjustments in human behaviour, and changes in government policy all affect the energy savings and economic performance of buildings. The tenants' behaviour is known to have a considerable impact on energy usage and is one of the most crucial uncertainties when it comes to building energy savings. According to Owens and Wilhite, changing occupant behaviour alone might save roughly 10–20 percent of household energy consumption in Nordic nations. According to Yohanis Y. G.'s research on home energy behaviour, altering the perception of energy expenditure may result in significant energy savings. The study of O. Guerra Santin et al. in the Netherlands also shown the impact of occupant behaviour in the utilisation of energy for space and water heating. Furthermore, occupant behaviour in buildings is widely acknowledged as a major factor contributing to differences in measured and simulated energy consumption in buildings . These and other research have demonstrated that tenant behaviours may have a significant impact on building energy use as well as the cost-effectiveness of building upgrading. The majority of research, on the other hand, are based on human surveys.
Although there are various ICT-based solutions that handle the generation of energy consumption data, there is a dearth of investment in user participation and tactics that make it simple to comprehend, increase user interaction, and drive behavioural adjustments. Several benefits have been mentioned, including motivating individuals, boosting their knowledge, and raising their awareness, improving standard consumption patterns, promoting green and sustainable behaviour, lowering energy expenses, and gaining financial benefits. However, since real rewards aren't there, user involvement isn't assured. The main causes for this stem from the fact that, despite the fact that a lot of data is gathered around buildings, people don't comprehend it. In reality, users are generally passively exposed to sensors and so are not engaged for lengthy periods of time. These seem to be some of the most significant roadblocks to a real breakthrough in energy-saving ICT technologies. As a result, this study provides a technique for user data perception based on exact 3D Modeling Services for coloured model derived from facility management building information models (BIM) in order to convey data in an easy-to-read manner and give users a better realistic impression of energy savings.
Users interact with the system via this layer. It's a graphical user interface for viewing sensor data with temporal filters (time, day, weekday, and month of the year). It also includes other useful data, such as time averages, energy use, and statistics on environmental conditions.
The major goal of the built system is displayed in this layer, which is to enable visualisation of data gathered by different sensors in a way that is straightforward and easy to predict by any kind of user. In this approach, in addition to the standard display options of graphs and bars, a more attractive 3D visual representation of the monitored location is built. The building information model (BIM) contains a comprehensive geometric description of the building and its equipment, such as furniture, as well as department designations in the form of labels, allowing visualisation of where each sensor was mounted.
One of the kinds of data representation used in this project was an interface based on a BIM model. This technique enables laypeople to have a greater grasp of the environmental comfort where they are situated, as well as simplifying the levels of energy use to a set of colorimetric scales, allowing users to identify the regions and times when the most consumption occurs.
Because the suggested values are represented by colours that show the space's comfort level, this approach makes it simple for users to comprehend them. This is in addition to the traditional ways of presenting data in dashboards, such as bar graphs, tables, and graphs, and allows any user to clearly understand what is going on in the environment because it is easier for a layperson to interpret data through colour rather than a large number of numbers.
