Februar 19, 2018

Connected Cabin

The connected cabin holds the potential to sustainably improve aircraft turnaround operations. Today, the aircraft cabin is a black box during boarding, with no information about the current status. But the future connected cabin provides a valuable set of sensor information.


A hardware prototype environment of a connected aircraft cabin was developed and used in field trials in close cooperation with Eurowings. In the following figure, the field test setup is shown with seat sensors from the automotive industry. This sensor network was successfully tested in a mockup environment previously. The individual seat sensors efficiently indicate the seat status and aggregated seat row conditions (prediction of boarding progress) are sent to a central processing unit. This unit provides aircraft-wide status information for the operator. Furthermore, a sensor floor was installed in the aircraft aisle to additionally detect specific passenger positions (density, congestion) and walking speeds. This prototype sensor environment allows for reliable detection of passenger positions. It is expected that a future connected cabin will also provide information about the status of the overhead compartment and allow a dynamically adapted seat allocation (see seatNow concept).

connected cabin - sensor environment


To emphasize the capabilities of the connected cabin, the following figure depicts results from the sensor floor for two different boardings (slow and fast boarding) and one deboarding event. Herein, the x-axis shows the position along the aircraft aisle and the y-axis shows the time. Consequently, this kind of representation exhibits the maximum walking speed of passengers and indicates congested areas in the aisle. The slow boarding scenario clearly consists of more congested areas (waiting queues), while the fast boarding shows mainly unconstrained passenger movements in the aircraft aisle. A preliminary analysis of the average unconstrained (maximum) speed of passengers results in 0.78 m/s, with a standard deviation of 0.31 m/s during boarding and a speed of 0.99 m/s with 0.24 m/s during deboarding.

Technology-supported distance measuring

The COVID-19 situation further emphasizes the need for precise position information to ensure the physical distance between passengers and to facilitate associated boarding/deboarding concepts. Commonly utilized receiver signal strength measurements can lead to false-positive and false-negative encounter classification, lowering the reliability and user acceptance of technology-aided social distancing options. The influence of environmental conditions is further increased in areas with limited space, as well as concave and metallic surroundings, such as aircraft cabins. These environments naturally provide demanding conditions for wireless signals, due to possible reflections, scattering, and attenuation of transmitted signals. A three-dimensional ray-tracing simulation, simulating signal propagation with respect to these propagation phenomena, supports the issue of non-reliable distance determination in the aircraft cabin.

Future localization framework for the connected cabin visualizing a Bayesian Monte Carlo sample (purple points) positioning. The necessary inputs are the coordinates of the stationary nodes (green and red squares) and the measured distances from these (black circles).

While Global Navigation Satellite Systems (GNSS) already provide the art localization technology for outdoor positioning, additional technologies, like WiFi, Ultra-Wide Band (UWB) or Bluetooth Low Energy (BLE) are emerging to provide reliable and locally available technologies for indoor applications. Due to the possibility of providing stationary communication devices in the cabin, absolute positioning can be realized in addition. This also allows usage of more versatile hardware, as market penetration does not factor in anymore since passengers can be equipped with customized hardware during boarding and deboarding. A smart sensor environment is key element to monitor and manage passenger activities in the aircraft cabin by providing an advanced situational awareness about individual positions and system states (e.g. occupation of the aisle or status of overhead compartments). This information will be used as input to ensure safe, operationally efficient, and passenger-oriented processes. Upcoming sensor technologies will lead to new product developments and services for seamless travel.


The complete list of publications can be found here: references.