In contrast to conventional hydronic heating systems, in which the air is used as a medium for the convective heat transfer, an alternative approach is based on the usage of infrared (IR) radiant heating foils. These foils, which are applied to the walls and the ceiling of a laboratory, can be controlled individually. This leads to the possibility of heating the room zonewise and only when a person is present in a zone. A local comfortable climate is provided only in occupied zones, with the remaining zones being kept at a lower base temperature. Consequently, the measurement system has to detect persons in each zone and to determine the putative thermal comfort at relevant locations in the room. For the first problem, we examined and evaluated different sensor types capable of localizing persons without infringing on their anonymity. For the second problem, we used the fact that the thermal comfort mainly depends on the operative temperature (Li et al., 2010; DIN EN ISO 7730, 2006; de Dear and Brager, 2002). According to Simone et al. (2007), this temperature can be measured directly by an easily producible, planar sensor. The sensors were integrated in a wireless sensor network which consists of Wi-Fi-capable microcontroller boards, wireless smart home equipment, a Wi-Fi router, and a server.
The challenge when designing a heating system is that it should be as energy
efficient as possible and yet must provide a comfortable room climate for the
occupants and take their wishes and needs concerning the usage of the system
into consideration (Hein et al., 2016a). These requirements have been
addressed by Braun et al. (2016) by applying copper traces in the shape of a
meander to the walls and supplying them with electrical energy. The system
was operated in such a way that the surface temperature was about
28
Heterogeneous architecture of the user-centered heating system. The communication is built around a Wi-Fi-capable router which is connected to the internet. The microcontrollers, which are used as temperature sensor nodes, as well as the controllers for the power electronics communicate via the resource-friendly message queue telemetry transport (MQTT) protocol. The HomeMatic components, like the thermostatic radiator valves (TRV), are accessible with the HomeMatic CCU2 Gateway. Users can interact through tablets, for instance; their commands, together with the sensor and actuator data, are stored and processed on the server and furthermore distributed in the network.
By theoretical reasoning and by experiments, we addressed the following
issues:
Which functional units are required to build a smart room climate
control, and what is a suitable system architecture? The system will
need to comprise several sensors (temperature, localization, etc.). This
places financial restrictions on the realization. What are the relevant deviations between the characteristics of the
functional units and the physical units used to implement the functional-unit
characteristics? How can the technical communication between the various physical units of
the heating system (sensors, heating elements, controllers) be organized? The
resulting system can be expected to be very heterogeneous, including
different data formats and communication standards.
Because of the individual requirements of the inhabitants and the differing constraints of the buildings where the heating system will be built in, the overlaying management system should be as open and flexible as possible. In the past, smart home system providers offered vendor-dependent solutions and are recently trying to create vendor-specific alliances. In contrast to that, users prefer vendor independence because they want to add devices of all available providers, if those are relevant for their use cases. Therefore, a middleware system or an accepted standard is necessary. Currently, there are promising concepts for user-friendly middleware platforms, like openHAB, Eclipse-SmartHome, or Qivicon offered by Telekom, which share the same conceptual ideas regarding their technology stack. The framework used by us for the operation of the measuring and control system is openHAB 2, an open-source framework which has gained more and more attention in the scientific community (Smirek et al., 2016). As usual, for middleware platforms like openHAB, a user interface, device abstraction, and opportunities to use different communication protocols are available. The openHAB system follows the OSGi specification, and therefore it is possible to create plugins, called add-ons, which extend current functionality and can be enabled or disabled at runtime. One common use case for such an add-on is to add a translation layer for another communication protocol. In the openHAB ecosystem, those translators are called bindings. There are more than 100 bindings available (in openHAB), so lots of technologies can be used, i.e., online weather services, smart light bulbs, and a variety of communication protocols like KNX, Z-Wave, and Modbus.
Simulation of the coefficient of performance (COP) of the combined heating system with the COP over the fraction of energy provided by the heat pump (the remaining necessary energy is provided by the heating foils) and the outdoor temperature.
Based on that framework, we had to divide the overall problem into smaller functional units, which are the heating system, the indoor localization of inhabitants, the thermal comfort measurement, and the user interface. Their resemblance as physical units was derived and finally combined to the overall system (Fig. 1).
The redevelopment of old building stock is feasible in different ways. Obvious and widespread building measures are the exchange of the old windows by better insulated ones or the application of an additional layer of building insulation (BDEW, 2015). But there are buildings where such measures are not applicable, e. g., listed buildings. Therefore, we have examined the combination of two heating technologies, which can be retrofitted in existing buildings, and the resulting synergy. In this concept, the existing hydronic system is detached from the old source of heat (gas or oil burner) and equipped with a heat pump. To take advantage of the heat pump's high coefficient of performance (COP), the amount of thermal energy provided by the heat pump is limited depending on the outdoor air temperature. The remaining share of energy is provided by infrared (IR)-radiant heating foils, which operate relatively independent of the weather conditions and are therefore on a constant level of performance. The simulation of this combined system, by varying the outdoor temperature and the fraction of energy provided by each heat source, shows that there exists an optimum of operation at every temperature on the interval (Fig. 2). If the weather is mild, the heat pump drives the heating system exclusively. The colder it gets, the more energy is provided by the heating foils. With such a simulation, the performance of the heating system is predictable for varying annual average temperatures in different regions.
The heating foils, which are powered by switching power supplies, are placed at the ceiling evenly and establish a comfortable room climate where necessary. The fact that the heating foils can be switched individually enables one to create different temperature zones in a room. But this also requires solutions for a zone-wise measurement of the occupants' thermal comfort and their location in the room. This measurement problem (selection of measurands, characterization of individual sensors, heterogeneous integration into a control system) is the subject of this paper (Hein et al., 2016b) and the following sections.
Signal processing for the thermopile array by dynamic masking (mask
The localization of an occupant is crucial for a lot of smart home use cases.
There are several strategies to obtain this kind of information, i.e.,
Bluetooth, RFID, infrared, or ultrasonic sensors
(Deak et al., 2012). In the context
of user-centered heating scenarios, the following questions are relevant:
Is it necessary to identify an occupant? Are camera-based solutions acceptable to occupants? Does a given solution measure
precisely and accurately enough? Would an occupant agree to wearing some kind of device? Are the installation costs economically justifiable? Is the installation possible in existing houses?
There exists a variety of sensors for the indoor localization of persons in a
heating zone. Owing to privacy and acceptance concerns (Arning and Ziefle,
2015), image generating and processing systems, like cameras, have been ruled
out. Radiating sensors, like radar or ultrasonic sensors, would be suitable,
but it is highly questionable in many societies, and certainly in Germany,
whether users would accept them in the living room or in the bedroom.
Excerpt of the output data of an experiment with six persons; row and column of sensor pixels and the resulting presence (1) and absence (0) of persons in the field of view of the listed pixels.
Output of the 4
Experimental results with a 16
For this reason, we focused our research on passive sensors like pyroelectric
infrared sensors (PIRs), thermopiles, thermopile arrays, and CO
A possible spatial distribution of the sensors for a maximum field of view
and a reliable detection has already been described in Kuki et al. (2013).
Four sensors were arranged in a square configuration to obtain an
8
By analogy with image processing methods, the sensor output data are arranged
in a 4
The determined maximum
The determined minimum
To suppress random noise,
Finally, a 3
At first, several experiments with a person at varying distances from the
sensor were carried out to validate the algorithm. The person was detected
reliably despite the high outdoor temperature of 30
Among the possible influencing effects are pets or other IR-radiating
objects, such as a kettle. They could lead to a false positive presence
detection and finally to the activation of the control loop. The sensitivity
of the algorithm to such effects was characterized by experiments. It was
found that the difference of the temperature of animal fur and the surface
temperature of clothing is quite small. Only the temperature of the human
skin of approximately 34
In an attempt to increase the resolution, we examined the thermopile array
Melexis MLX90621, which comprises 16
The goal of a user-centered heating system is the occupants' subjective
sensation of heat or, in other words, their sense of thermal comfort.
Consequently, this sensation has to be estimated by a technically measurable
quantity (Aswani et al., 2012). To this end, the predicted mean vote (PMV)
has been established in the ISO standard 7730 (DIN EN ISO 7730, 2006). This
standard has several drawbacks, e.g., the complex and only iteratively
solvable calculation of the PMV and the dependency on poorly measurable
quantities, such as the clothing level and the metabolic rate of a person. We
therefore considered the operative temperature as a possible controlled
variable. The comfortable operative temperature
Sensors investigated:
Arrangement of the heating foils in the demonstrator room (red). The black sphere marks the position of the globe thermometer or the single temperature sensor.
The operative temperature can be determined by a climate-measuring instrument
– we used the type Testo 480 – which comprises a probe for the air
velocity, a globe thermometer, and an air thermometer. At a typical indoor
air velocity of
Step response of the various temperatures at a selected location in the demonstrator room after turning heating foil pair 1 on.
Comparison of the measured temperature changes in case A (pair 3
powered), in case B (pair 1 powered), and in case C (pairs 1 and 3 powered
simultaneously). Also shown is the calculated sum of the results of cases A
and B (“Case A
Step responses of the operative temperature and of the PMV at a selected location in the demonstrator room in a closed-loop experiment with heating foil pairs 3 and 10 used as actuators.
Technology acceptance model (Davis et al., 1986).
Time series of measured temperatures and occupant presence in a naturally ventilated office over a period of 7 days. The comfortable operative temperature was calculated from the measured values by Eq. (3).
As the climate-measuring instrument cannot be deployed in living spaces for
size and cost reasons, we examined a round, planar temperature sensor with a
diameter of 30 mm (Fig. 6) as suggested by Simone et al. (2007) as an
alternative. Experiments in a room of approximately 40 m
This design is also influenced by the linear or nonlinear nature of the
controlled system. We carried out experiments to determine if the combined
action of several heating foils can be described by the sum of the actions of
the individual foils when operated alone (in other words, if the system can
be treated as linear; the system is nonlinear, as shown by Eq. (4), but small
temperature changes should warrant a linearization). This is indeed the case.
For instance, the difference between the added individual actions of two
pairs of heating foils and their combined simultaneous action was less than
0.5
We used a digital PI controller to control the operative temperature and
examined the response to a step in the reference variable from 21.5 to
22.5
For the development of a new system, it is recommended to examine the acceptance or factors that increase the probability of use. In this context, acceptance is the positive reception of a chance a in physical environment after a deliberate examination of the change that has taken place (Renn, 1986). In the focus of the technology acceptance model, according to Davis (1986), are the perceived benefit and the perceived usability. As shown in Fig. 11, these two factors influence the attitude directly and thus also the use of an innovation.
In addition to the perceived benefit of the system, the perceived usability is the second crucial factor for the acceptance of a system. To ensure the usability, a human–machine interface (HMI), which is adapted to the needs of its users, has to be designed and implemented. The user characteristics, as well as the technical and physical environment determine the context in which the system is applied (DIN EN ISO 9241, 2011). In former projects, our working group established a well-proven development process for user interfaces which consists of focus group interviews, card sorting, and usability testing (Bauer et al., 2014a). OpenHAB offers the possibility to design such an optimized user interface which is accessible by smartphones or web browsers. If the inhabitants are not familiar with such technologies, openHAB is flexible enough to embrace different solutions, like manual devices to set the desired temperature comparable to room thermostats.
Our system has to comprise several temperature sensors, localization units,
and possibilities for the inhabitants to interact with the system. Through
openHAB bindings, different technologies, like MQTT sensor nodes equipped with our operative temperature sensor,
HomeMatic components, and the control unit of the heat pump, are interconnected
via a Wi-Fi-capable router and managed by a small and energy-efficient PC.
The PC is used as the central control unit (CCU) on which the openHAB server
and a MQTT broker is running. The MQTT sensor nodes only send their measured
values when the temperature change is bigger than 0.25
Bringing together the MQTT temperature sensor measurements and the ones by
the HomeMatic components, Fig. 12 represents typical time series of
temperatures and occupant presence in a naturally ventilated office (of
approximately 20 m
The digital controller is also implemented on the openHAB framework. Every 30 s, the database is queried for the sensor and reference variable values, after which the controller output variables are calculated, and finally these variables are sent to the actuators. The reference variables are calculated from the values of wireless thermostats where the user can adjust the desired temperature in each room or, optionally, by a web interface and a mobile app. Furthermore, the energy supplying company can influence the room temperature within the bounds of the comfort temperature and with a lower priority than the user. This enables the supplying company to make use of load shifting and thus to use the available renewable energies more efficiently.
We have analyzed the requirements of a smart heating system and, in particular, the necessary sensors and their integration in a feedback control system which relies on both wired and wireless communication. The system comprises temperature and localization sensors as measuring elements and heating foils as actuators. The latter were characterized experimentally, and the results of this characterization served to parameterize a feedback controller with the so-called operative temperature as the controlled variable because it is an accepted measure of thermal comfort. The system components were studied in a demonstrator room, and the entire heterogeneous system has now been deployed in an apartment for further field studies during the heating season of 2016/2017.
The localization of room occupants by thermopiles was shown to work reasonably well and is especially advantageous in terms of data security and user privacy. It does, however, allow no personalization of heating services. With those users who wish such a personalization in mind, it needs to be analyzed if personal identification could and should be added to the current implementation. It would then be possible to create individual profiles of thermal comfort for each occupant of a building. A way of implementing such functionality could be via an occupant's cell phone connected to the local home network.
Another possible extension of the demonstrator system could be to search the internet for relevant data to corroborate conclusions made by the system. An obvious choice would be to more consistently exploit weather forecasts. Such approaches, often implemented by using web services or endpoints, are promising strategies to benefit from the current trend to digitalization, often referred to as Internet of Things (Bauer et al., 2014b).
The corresponding data set is available at
The authors declare that they have no conflict of interest.
The authors would like to express their sincere thanks to the
Bavarian State Ministry of Education, Science and the Arts for
partially funding the presented work within the E