Abstract
With the increase in energy prices and the drive to reduce carbon emission, this paper presents an investigation of the use of smart office environments to monitor and evaluate the sustainability and behaviour of employees and the utilisation of space and resources. This paper presents analysis of data in an office environment in a company in Derby city to attempt to understand the behaviour of employees, pattern of work, power consumption and performance of heating and air-conditioning systems. Data from occupancy, room temperature, CO2, humidity, lighting, air temperature, windows status are all collected and analysed. The data also included external environmental conditions. The results indicate some correlation between CO2 levels and the number of employees. They also show correlation between outside and inside environmental conditions. In addition, the utilisation of space was also monitored, and the results demonstrate low utilisation during most days, this was due to Covid-19 and to working from home and off-site patterns. However, the data is found useful to inform future decisions about the actual space needed for normal working conditions.
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17.1 Introduction
The main purpose of smart technologies is to collect data from the surrounding environment and assist users in day-to-day activities [1]. The application of smart technologies in manufacturing is discussed in terms of the automation of production and the benefit that this can bring due to the reduction of operational costs, human error and waste, which consequently increases productivity [2]. Current research lacks evidence on the outcomes of smart technologies in a workplace setting [3].
As times change and technology continues to advance—there is a need more than ever for people to be able to track and see what is going on in their working environments. There are a variety of reasons as to why there is now a need for this information to be gathered. Sustainability reasoning—not just an energy or emissions point of view, but staff well-being, and company health also fall under this category. This then also branches out to changes that are coming on the back of the pandemic. More people are working from home, leading to a condensing of the workplace size—hot desking, or people want to be more spread out in their working regions. Either way, space utilisation is a big issue for lots of businesses. When it comes to the office environment, research tends to discuss the utilisation and benefits to stand alone devices rather than considering the overall work environment embedded with smart technologies [4, 5]. In order for businesses to be able to make positive change, they need to identify what is it, that needs to be changed. They need to pinpoint strengths and weaknesses and continue to review and check them on a regular basis moving forward. Change/monitoring is in the best interest of everyone. Not only will it save money, cut emissions and increase productivity—it will also keep everyone in the know how as to what needs to be improved and how, especially with the cost-of-living crisis that is being faced.
By analysing the data that has been collected, it will be able to inform future decisions about space needed to satisfy for efficient working conditions; and carbon and energy savings.
As technology continues to advance, coming out of a pandemic, inflated energy prices—times are quite hard to predict. Things are very uncertain. This area is something that needs continuous further study as there is constant factors that change. However, the adoption of smart technologies in a work setting is an inevitable process [3], so it is important that the gaps start to be filled. The objective of this paper is to help addressing some of the current and on-going research and technology questions.
17.2 Methodology
In order to study the benefits of sensor data feed in office environment, a case study is presented in this paper. Figure 17.1 presents the first floor of the office environment. Details of the sensors are shown in Table 17.1. The rationale is based on a reasonable micro-SME office size to test the technology and data to address key findings that could be extrapolated in future installations of smart buildings.
First floor office environment sensor location at the company
This office is used as a case study of the technology development in terms of sensors, instrumentation, software platform; it also was used to reflect on small office culture during/post covid pandemic and energy use; but it is not meant to be for generalisation but as a case study to reflect upon future development.
The data was presented live to staff-office during the day via a monitor and it was anonymous and does not include any further information more than what the team could see in the office in-person in terms of attendance, etc. The purpose was for statistical analysis on the long term to link that with energy and other factors; and to test the smart technology.
Ethical concerns of monitoring will be addressed in a future paper; but in general, the data saved is anonymous and the main goal is to monitor energy use and space utilisation.
There was no staff with mobility issues in this study; however, this is an area of future work.
17.3 Data Analysis
Data processing has been carried out in the office environment, see Fig. 17.1. The data has been recorded for several months continuously for the day and the night from 17/11/2021 to 9/5/2022. The data was in an interval of five minutes each. The data shows the total number of people who have been occupying the office during this period. It also shows the amount of CO2 in ppm, humidity, temperature, outside temperature, outside humidity, wind speed, electricity consumption by the radiators and the total office power consumption in amperes. It has been noted that some data such as the total office power has only been recorded from the 11th of January.
17.3.1 Total Number of People
Due to Covid-19 not many people were working from the office as most of the employees were working from home. However, despite that fact, even the maximum number of people was only six people at one time in the office, the outcome showed promised results for the research as will be explained in detail later.
Figure 17.2 presents the number of people during the whole research period which never exceeded six people. Table 17.2 shows that it is rare to find more than three people in the office at the same time. Number of people from four to six represents circa 5% of the monitored time. The office was mostly occupied by one person and sometimes two or three people only.
Number of employees occupying the office every five minutes
17.3.2 Correlation Coefficient of the Data
To initially determine if there is a relationship among all the aspects of the research that are being recorded, the correlation coefficient has been applied among all data. Table 17.3 shows the result of applying the correlation coefficient. Figure 17.4 shows the colour representation (colour map) of the results.
Figure 17.3 shows that number of people has a strong relation with the amount of CO2 and temperature and reasonable correlation with the total office power and the RP Radiator while it has a weaker relation with the humidity, the outside temperature, the wind speed, the outside humidity, and the GP Radiator. This could mean that people existence in the office affects the amount of CO2 and the temperature and increases the total power consumption. As it is well known that the temperature and the humidity are having inverse relation, Fig. 17.3 clarifies that as it did show a strong inverse relation between the two variables. Figure 17.3 also shows that the temperature has the most effective relation with other aspects. It has a strong relationship with CO2, Humidity, number of people, outside temperatures, outside temperature and total office power, and less important relationship with the radiator and the GP radiator and almost no relationship with wind speed.
Correlation coefficient among all the aspects of the research work
Example shows how the CO2 is affected by the number of people during the day and the night
17.3.3 Number of People Verses CO2
Figure 17.4 presents an example of a whole week; it clearly illustrates how the number of people is affecting the amount of CO2 inside the office. Figure 17.4 also shows the day and the nights patterns, approximated as a square wave; the day has been categorized as 1 and the night as 2. When the number of people reached its peak on Thursday, the amount of CO2 has significantly increased to its peak as well. It is obvious that the amount of CO2 has dramatically decreased when there was no one in the office during the weekend. It must be mentioned that the level of CO2 in this figure is scaled between 0 and 1 then multiplied by six to match the number of people in scale and to fit and appear clearly in the figure for comparison purposes.
17.3.4 Number of People Verses Temperature
Similarly, Fig. 17.5 shows the strong relationship between the number of people and the temperature in the office. The temperature has gradually decreased to reach its lowest temperature during the weekend when the office was not occupied. Figure 17.5 shows clearly that the temperature increases in the daytime and decreases during the night. Again, it must be mentioned that the temperature values have been scaled to 0–1 and then multiplied by six to fit in the figure for comparison purposes.
The relationship between the number of people and the temperature in the office
17.3.5 Number of People Verses Total Office Power
As mentioned earlier, the total office power has been recorded much later than other records therefore, it demonstrated a fair correlation relationship with the number of people, but once the total office power plotted for one week within the recorded period it showed a strong relationship as indicated in Fig. 17.6. Figure 17.6 shows that the total office power is increasing significantly while the office is occupied and decreases dramatically when no people are in the office. The values of the total office power have been scaled to 0 and 1 and then multiplied by 6 to fit within the figure match with the number of people to enhance the comparison process.
Full week of records show how the total office power is highly affected by the number of people
17.4 Conclusion
From the results above, it can be concluded that current office facilities are not well utilised due to Covid pandemic or post-Covid culture of working from home. This indicates the need to utilise resources and facilities in a better way to enhance return on space investment. Also, the results show that with more people in the office, more energy consumption is presented. Temperature and CO2 readings seem to be proportional to the number of people who are working in the office at any one time. This also indicates the need in some cases for better ventilation which could lead to further energy consumption when windows are open in cold weather. Future work will include researching how the intelligent system can be developed to advise occupants on the best measure to be taken to save energy while at the same time maintaining air quality and environmental comfort. A wider scale of data will be collected over time, to see how different seasons impact the data, but to also see whether there does begin to be a more consistent, higher number of staff working in the building at a given time.
There will also be a comparison to another, larger site—where data can then be compared at both levels of space.
Further investment into greater number of sensors that will collect data for other elements—here further analysis can be undertaken to give even greater detail into the results.
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Acknowledgements
This paper is based on research work funded by Innovate UK, Knowledge Transfer Project (KTP), as a collaboration between Scenariio Ltd and Nottingham Trent University (KTP number 11968).
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Hall, J., Shakmak, B., Al-Habaibeh, A., Kanjo, E. (2023). The Analysis of Sensory Data from Smart Office Environment Towards the Development of an Intelligent System. In: Nixon, J.D., Al-Habaibeh, A., Vukovic, V., Asthana, A. (eds) Energy and Sustainable Futures: Proceedings of the 3rd ICESF, 2022. ICESF 2022. Springer Proceedings in Energy. Springer, Cham. https://doi.org/10.1007/978-3-031-30960-1_17
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