Apparatus and a method for sensing events from a remote location

A method for detecting the occurrence of first and second contemporaneous events in respective predetermined first and second sub-areas of a remote area, comprising the steps of:

• capturing electronic signals representing an image of the remote area including the predetermined first and second sub-areas;
• extracting a number of data values, representing only the predetermined first and second sub-areas of the image, from the electronic signals, wherein the number of extracted data values is a less than a number of data values representing the entire image of the remote area;
• and
• automatically comparing the extracted data values to reference image data values representing the first and second sub-areas before the respective first and second events have occurred to determine if the respective first and second events have occurred.

A method of monitoring a queue of people comprising the steps of:

• generating electronic signals representing successive images of the queue as seen from a remote location;
• extracting, from said electronic signals, first and second sets of successive data values representing a time sequence of images of respective areas surrounding an entrance into the queue and an exit from the queue, respectively;
• analyzing the data values representing each of the time sequences of images to detect motion into the queue and motion out of the queue;
• increasing a count of people in the queue when motion into the queue is detected;
• and
• decreasing the count of people in the queue when motion out of the queue is detected.

In a system for processing a group of items, a method of automatically determining an expected waiting time for an item entering a queue which feeds a set of servers, each of which process one item at a time, the method comprising the steps of:

• generating electronic signals representing successive images of the queue and the servers as seen from a remote location;
• extracting, from said electronic signals, data values representing sub-areas of the image including the queue and each of the servers;
• analyzing the image data obtained from each of the sub-areas for each of the servers to determine an expected service time for each server;
• averaging the expected service time for all servers to obtain an average expected service time;
• analyzing the image data obtained from the sub-area for the queue to determine the approximate number of people in the queue;
• and
• multiplying the determined approximate number of people in the queue by the average expected service time to obtain the expected waiting time in the queue for the item entering the queue.