Our challenge

Reasons for increased energy use can be e.g. malfunctioning control units in the ventilation systems, district heating systems, or that the use of the building has changed. There is also a need to compare buildings to identify and decide on upgrading equipment and renovation measures for reduced energy use and improved function. Large property owners such as municipalities have a large number of buildings with tens of thousands of values that are monitored and can generate alarms. There it is very time-consuming to analyze, sort and manage deviations.

The current situation

We have a lack of systems/products/services that enable optimization of energy use in society. Large property portfolios have an unnecessarily high energy consumption, there are also no good tools to balance the consumption between properties, which leads to the power requirement being higher than it could be with efficient tools.

What do we want to achieve?

The project aims to develop innovations to analyse the energy demand of buildings under different circumstances by using historical data taking into account weather conditions, building information and the use of the building. This data is used to predict future energy needs in buildings, to balance energy needs between buildings, and to reduce total energy consumption.

The project will contribute to new knowledge, solutions, processes, working methods and methods that lead to efficient energy and resource use in buildings, interaction with neighboring sectors, functionality and well-being.

  • IoT and IoT security

    We work on tools for connecting and authenticating IoT devices, eg. sensors, that are useful if you need your own IoT devices to develop your services. We also monitor the communication to ensure that no one has hacked in and taken over your device.

  • Energy optimization

    By including data sets about construction, analysing energy use patterns, activities in the buildings, microclimate, etc. which is a combination of data sets that are not included in today’s property controls, you can make more informed decisions about energy measures.

  • Machine learning

    We work with machine learning to automatically recognize what are normal patterns in data, and what are deviations.

  • Augmented reality

    Use your sensor data, open data and geographical information to create useful information and present it as augmented reality. Contact us if you are interested in creating applications on our platform!

Goal

The overall goal of the project is to, through data collection and the use of machine learning methods/artificial intelligence, reduce the total energy use by up to 15% within large property holdings. This will be achieved through increased understanding and balancing energy based on property operations and use.

Target groups

The project’s main target group is owners of, and companies managing, large building stocks. Primarily, properties in Skellefteå, Piteå and Kristianstad are included, but we will take in needs from, and spread the results to other owners of large building stocks in Sweden.