Abstract: A system includes a bin detector comprising an antenna, a bin configured to accommodate at least one item and having a bin unique identifier, at least one processor to receive a weight of the at least one item from at least one sensor in communication with a scale, and at least one battery to power the system, the bin detector to transmit a first signal, receive a second signal in response to the first signal for each of the at least one item and determine an item unique identifier for each of the at least one item, and transmit the bin unique identifier, the item unique identifier for each of the at least one item, and the weight information to the processor to transmit the bin unique identifier, the item unique identifier for each of the at least one item, and the weight information to a server computing device.

Abstract: Aspects of the subject disclosure may include, for example, a communication system that receives location data associated with mobile devices over a time period and evaluates the location data to predict hours of operation of an enterprise. The communication system operates by: selecting a first group of mobile devices based on geographical proximity to the enterprise; analyzing the location data to identify a subset of the first group predicted to correspond to employees of the enterprise; selecting a second group of the mobile devices by filtering the subset from the first group; analyzing the location data corresponding to the second group over the period of time to determine aggregate time periods when the second group are in the geographical proximity to the enterprise; and predicting the hours of operation of the enterprise according to the aggregate time periods. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a communication system that receive location data associated with mobile devices over a time period and evaluates the location data to predict hours of operation of an enterprise. The communication system operates by: selecting a first group of mobile devices based on geographical proximity to the enterprise; analyzing the location data to identify a subset of the first group predicted to correspond to employees of the enterprise; selecting a second group of the mobile devices by filtering the subset from the first group; analyzing the location data corresponding to the second group over the period of time to determine aggregate time periods when the second group are in the geographical proximity to the enterprise; and predicting the hours of operation of the enterprise according to the aggregate time periods. Other embodiments are disclosed.