Investigating low-cost wireless occupancy sensors for beds
Occupancy sensors are used in care applications to measure the presence of patients on beds or chairs. Sometimes it is necessary to swiftly alert help when patients try to get up, in order to prevent falls. Most systems on the market are based on pressure-mats that register changes in compression. This restricts their use to applications below soft materials. In this work we want to investigate two categories of occupancy sensors with the requirements of supporting wireless communication and a focus on low-cost of the systems. We chose capacitive proximity sensors and accelerometers that are placed below the furniture. We outline two prototype systems and methods that can be used to detect occupancy from the sensor data. Using object detection and activity recognition algorithms, we are able to distinguish the required states and communicate them to a remote system. The systems were evaluated in a study and reached a classification accuracy between 79 % and 96 % with ten users and two different beds.