Abstract: A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events.

Abstract: Systems and methods for predictively responding to real-time sensor data from an computer-augmented environment are provided. A system may receive sensor data from the computer-augmented environment. The system may obtain a feature model, a prediction model, and a filter criteria. The system may derive, based on the feature model and the sensor data, a first event. The system may determine the first event is associated with an authorized event identifier in the filter criteria. The system may forecast, based on the authorized event identifier and the prediction model that a second event occurs after the first event. The system may transmit an action message to the computer-augmented environment, the action message indicative of the second event. Updates to the feature model, the prediction model, and/or the filter criteria may occur in batch using machine learning and statistical analytics while the real-time platform predictively responds to the sensor data.

Abstract: Systems and methods for predictively responding to real-time sensor data from an computer-augmented environment are provided. A system may receive sensor data from the computer-augmented environment. The system may obtain a feature model, a prediction model, and a filter criteria. The system may derive, based on the feature model and the sensor data, a first event. The system may determine the first event is associated with an authorized event identifier in the filter criteria. The system may forecast, based on the authorized event identifier and the prediction model that a second event occurs after the first event. The system may transmit an action message to the computer-augmented environment, the action message indicative of the second event. Updates to the feature model, the prediction model, and/or the filter criteria may occur in batch using machine learning and statistical analytics while the real-time platform predictively responds to the sensor data.

Abstract: A cable clamp has two identical moulded components that can be clamped together about a cable. Each component has a yoke with a ratchet bar at one end and two short arms at its opposite end spaced by a gap and having ratchet teeth on their inner faces. The ratchet bars on each component extend in the gap between the arms on the other component and the cable extends through the aperture between the two yokes and between the two ratchet bars. The yokes can be squeezed together about the cable, causing the ratchet bars to slide over the engaging teeth, which prevents the two components being subsequently separated.

Abstract: A cable clamp has two identical moulded components that can be clamped together about a cable. Each component has a yoke with a ratchet bar at one end and two short arms at its opposite end spaced by a gap and having ratchet teeth on their inner faces. The ratchet bars on each component extend in the gap between the arms on the other component and the cable extends through the aperture between the two yokes and between the two ratchet bars. The yokes can be squeezed together about the cable, causing the ratchet bars to slide over the engaging teeth, which prevents the two components being subsequently separated.