Dynamic Office Environments on the Users Terms
The project investigates and demonstrates how office environments can be efficiently utilized, thereby reducing energy consumption while simultaneously increasing user satisfaction and improving the experienced indoor climate. The indoor climate and workstations are visualized to the users by leveraging loT solutionslikemotion sensors and monitoring CO2 concentration and temperature.
The project investigates and demonstrates how office environments can be efficiently utilized, thereby reducing energy consumption while simultaneously increasing user satisfaction and improving the experienced indoor climate. The purpose is to take advantage of the inherent characteristics of the building to meet the users' requirements, while increasing energy efficiency.
The indoor climate and workstations are visualized to the users by leveraging loT solutions like motion sensors and monitoring CO2 concentration and temperature. This gives users the opportunity to decide a location which accommodates preferred indoor climate and facilities required for the task at hand e.g. silent zones or zones with the opportunity to collaborate with colleagues. The indoor climate is displayed both in real time and in a predictive format. Based on the mapping of user requirements and behavior, machine learning can ensure the best possible correlation between operation and use of the premises for increased energy efficiency. By gaining an overview of usage patterns, it will be possible to customize premises and operations as user requirements change. This ensures energy savings and greater knowledge of how office environments can be betler utilized in practice. The results will be relevant to contractors, architects, managers, property managers, users, etc. and can be implanted in a wide spectrum of buildings ranging from low to high technical complexity.
Based on the specific conditions of the case enterprise Implement Consulting Group the project explores the consequences of a “free seating” organization of the working environment. Free seating allows space-savings and thereby energy savings because more employees share fewer working stations.
Data and simulations in this report shows, that further major heat savings will be made possible by implementing variable temperature zones. Annually, Implement would be able to save around 10% of their heat consumption corresponding to 104.000 kWh or 68.900,00 DKK. If the temperatures in the zones are lowered with one degree, the calculated annual savings are increased to around 24%. Both cases result in a minor increase in electricity consumption for ventilation operated according to room temperature.
Introducing variable temperature zones in a dynamic office environment thus allows for important heat savings.
The qualitative analysis points out challenges and underlines the importance of being attentive to the quality of the space each employee is offered, and especially how it corresponds to the needs for caring out changing tasks.
The project develops a concept for an interface where machine learning combines the indoor climate
preferences of the individual employee with calendar information of current tasks and offers the employee suggestions for suitable, available working stations through an app. The energy savings will typically be of a size that makes the development of an app cost-effective.
If employees are presented with several choices between different areas with available working stations, varying temperature zones can become part of what qualifies the different working stations – and thus ensure employee satisfaction.
Companies who wish to obtain energy savings and increase employee satisfaction, by giving employees a free choice between fewer seats, should be particularly attentive to:
- Explore whether it will be useful to introduce varying temperature zones that qualify for different types of work in the company’s building.
- Optimize the quality of the space available for employees, in ways that makes it suitable for
- different types of tasks. For example, areas can be designed especially for concentrated individual work, collaboration or meetings with externs.
- Support an app or a similar system that makes it easy and simple for the employee to find the way to an available working station, suitable for the current task.
- Via machine learning and/or IoT solutions to integrate indoor climate preferences and indoor climate data in the suggestions of working stations made for to the employee.
Key figures
Category
Participants
| Partner | Subsidy | Auto financing |
|---|---|---|
| lmplement Consulting Group | ||
| CLIMAID IvS | ||
| Syddansk Universitet |
