Abstract: A method for crowd prediction in an elevator system includes logging the number of calls across a period of time and generating a first time series for an average number of calls; collecting external influence data and generating a second time series for the external influence data; performing a cross-correlation test on the first and second time series; when a cross-correlation between the first and second time series is determined, performing a causality test on the first and second time series; and when a causal relationship between the first and second time series is determined, using the causal relationship to predict an expected number of calls in the elevator system.

Abstract: Provided are embodiments including a system a method for performing smart beamforming for reliable and secure wireless data transmission. The can embodiments include receiving at least one parameter of an elevator car operating in a hoistway, and determining a steering angle based on the received parameters. The embodiments can also include performing beamforming of an antenna array based on the determined steering angle, and transmitting data from the antenna array based at least in part on a beamforming process.

Abstract: Provided are embodiments that include a safety system and method for implementing presence detection. Embodiments can include a receiver that is configured to receive a signal from a transmitter, and a detection module that is configured to detect a signal strength of the signal. Embodiments can also include a processor that is configured to compare the signal strength of the signal with a signal strength threshold, and a task module that is configured to perform a task based at least in part on the comparison.