the basis for the intelligent control of air conditioning is the use of building bus systems instead of a conventional electrical installation. this bus system is used to collect sensor data and control the actuators that operate the electrical components such as lights or blinds.
for the prediction of user behavior, a data set is first created by recording the presence in a room. the data set enables the training of artificial intelligence and the subsequent prediction of the recorded time series.
the predicted user behaviour can be compared with the installed sensor technology during the running time by evaluation and comparison. this makes it possible for the first time to guarantee an optimal control behaviour of the heating or cooling system both depending on the prediction and on the actual values.
more and more machines, sensors and devices are networked via the internet. we already use many intelligent products in our everyday lives. however, the real benefits of using data from the internet of things lie in the combination of data with intelligent applications and services that the infrastructure of the internet of things makes possible.
it is conceivable here, for example, to link the system to weather forecasts or to the occupancy schedule of meeting rooms that are only used selectively. the energy-saving potential of the intelligent system has been demonstrated in several simulations. the anticipatory temperature control alone, i.e. also the less severe lowering of the temperature in order to restart the system as energy-efficiently as possible, saves a lot of energy.