Abstract: Systems, methods, and software for determining whether or not a monitored space is occupied by one or more humans and/or animals. In some embodiments, one or more radio-frequency (RF) receivers monitor(s) one or more RF frequencies for changes in received signal strength that may be due to changes in occupancy of the space being monitored. The received signal strength is analyzed using nonparametric online change-point detection analysis to determine change-points in the received signal(s). One or more statistical measures of the received signal(s), such as mean and variance, are used in conjunction with the change-point detection to determine a probability that the occupancy of the monitored space has changed. In some embodiments, additional sensors and/or machine learning can be used to enhance the performance of the disclosed occupancy-detection methodologies.

Abstract: Aspects of the present disclosure include methods and systems for commissioning and authenticating devices for joining a local network that improve the security of the network and make it more difficult for unauthorized devices to gain access to the network. In some examples, communication channels that have a more limited range and direction as compared to radio frequency communication are employed for exchanging information to join the network, such as cryptographic keys. The communication channels may include acoustic or optical channels. In some examples, techniques for deriving temporary and/or dynamic keys are disclosed.

Abstract: Systems, methods, and software for determining whether or not a monitored space is occupied by one or more humans and/or animals. In some embodiments, one or more radio-frequency (RF) receivers monitor(s) one or more RF frequencies for changes in received signal strength that may be due to changes in occupancy of the space being monitored. The received signal strength is analyzed using nonparametric online change-point detection analysis to determine change-points in the received signal(s). One or more statistical measures of the received signal(s), such as mean and variance, are used in conjunction with the change-point detection to determine a probability that the occupancy of the monitored space has changed. In some embodiments, additional sensors and/or machine learning can be used to enhance the performance of the disclosed occupancy-detection methodologies.