초록 ▼

The present invention provides for a vending system wherein a monitoring system verifies that a product ordered by a vending customer is actually delivered through a delivery area to the customer. If the product ordered is unavailable either because of an out of stock situation or a blockage of the

The present invention provides for a vending system wherein a monitoring system verifies that a product ordered by a vending customer is actually delivered through a delivery area to the customer. If the product ordered is unavailable either because of an out of stock situation or a blockage of the delivery path for that product, the present invention allows the customer to request a refund or order a second product. Additionally, the present invention helps to prevent theft of product from the vending system.

대표청구항 ▼

The present invention provides for a vending system wherein a monitoring system verifies that a product ordered by a vending customer is actually delivered through a delivery area to the customer. If the product ordered is unavailable either because of an out of stock situation or a blockage of the

The present invention provides for a vending system wherein a monitoring system verifies that a product ordered by a vending customer is actually delivered through a delivery area to the customer. If the product ordered is unavailable either because of an out of stock situation or a blockage of the delivery path for that product, the present invention allows the customer to request a refund or order a second product. Additionally, the present invention helps to prevent theft of product from the vending system. of said subset of past values.35. A method as claimed in claim 34 which further comprises the step of determining the location of a first local minimum of said graph.36. A method as claimed in claim 33 wherein said prediction algorithm is suitable for data series which exhibit deterministic behaviour.37. A method as claimed in claim 33 wherein said prediction algorithm comprises the steps of: (i) forming a set of vectors wherein each vector comprises a plurality of successive past values of the series of data; (ii) identifying from said set of vectors, a current vector which comprises a most recent value of the series of data within said vectors; (iii) identifying at least one nearest neighbour vector from said set of vectors, wherein for each nearest neighbour vector a measure of similarity between that nearest neighbour vector and the current vector is less than a threshold value; (iv) for each nearest neighbour vector, determining a corresponding vector, each corresponding vector comprising values of the series of data that are a specified number of data values ahead of the data values of the nearest neighbour vector in said series of data; and (v) calculating a predicted value on the basis of at least some of the corresponding vector(s). 38. A method as claimed in claim 28 wherein said store of predictive algorithms comprises at least one auto regressive integrated moving average (ARIMA) algorithm.39. A method as claimed in claim 28 wherein said step (ii) of assessing the level of deterministic behaviour of said series of data on the basis of said selected plurality of past values is carried out in real time.40. A method as claimed in claim 28 wherein said step (iii) of selecting a predictive algorithm from a store of predictive algorithms on the basis of said assessment of the level of deterministic behaviour of the series of data is carried out in real time.4