MOBILE DEVICE BASED INVENTORY MANAGEMENT AND SALES TRENDS ANALYSIS IN A RETAIL ENVIRONMENT

1 . A method for calculating sales trend of a product at a store shelf based on crowdsourcing, comprising the steps of:

receiving, by a retail store server, availability data of a product measured on a shelf in the retail store from a portable device, wherein the availability data is in the form of a picture acquired of the product on the shelf;

identifying products on the shelf using tags attached to the shelves;

calculating sales velocity and sales trends of the product from the identified products; and

transmitting the sales velocity and sales trend of the product to one or more third parties' systems in a supply chain of said retail store,

wherein products and their locations on retail store shelves have been cataloged in a product database.

2 . The method of claim 1 , further comprising triggering a warning message if the retail store shelf is empty.

3 . The method of claim 1 , wherein identifying products on the shelf using tags comprises the steps of:

identifying the tags on the shelves using tag template information and information regarding a distribution of tags on the retail store shelves that is read from a tag database;

mapping the identified tags to a shelf and its corresponding assortment of items;

identifying products in the picture by reading product templates related to the identified tags from the product database; and

transmitting a list of identified products and their quantities to the server.

4 . The method of claim 3 , wherein identifying the tags is performed by a first image processing application, and identifying products in the picture is performed by a second image processing application.

5 . The method of claim 3 , further comprising filtering the results of identified products based on product dimensions, to eliminate false positives.

6 . The method of claim 1 , wherein calculating sales velocity and sales trends of the product comprises the steps of:

receiving for each product p a timestamp t and a number of items n of product p on the retail store shelf, where the product information is organized as pairs p(t, n);

ordering product pairs p(t, n) according to the timestamp t to generate an ordered sequence;

calculating a least square line fit for the sequence to estimate a sales' velocity; and

comparing changes in a slope of the fitted line to determine a change in the sale's velocity over time.

7 . A method for minimizing a products out-of-the-shelf time based on data collected by mobile applications, comprising the steps of:

receiving, by a retail store server, data acquired by a mobile application regarding a number of missing product items on a shelf in the retail store;

calculating the product's turnover;

receiving, by the retail store server, a request for an optimized replenishment route;

generating an optimized replenishment route from the products' turnover calculation that minimizes out-of-the-shelf occurrences; and

transmitting the optimized replenishment route to the mobile application for display to a user.

8 . The method of claim 7 , wherein the product's turnover is calculated by a first sales trend calculation application.

9 . The method of claim 7 , further comprising updating demand forecasts of the reported missing product items in a product localization and turnover database.

10 . The method of claim 7 , wherein the optimized replenishment route is calculated by a second sales trend calculation application.

11 . The method of claim 7 , wherein the data of number of missing product items on a shelf acquired by the mobile application is in the form of a picture,

wherein products and their locations on retail store shelves have been cataloged in a product database, and

wherein the method further comprises identifying products on the shelf using tags attached to the shelves.

12 . The method of claim 11 , wherein identifying products on the shelf using tags comprises the steps of:

identifying the tags on the shelves using tag template information and information regarding a distribution of tags on the retail store shelves that is read from a tag database;

mapping the identified tags to a shelf and its corresponding assortment of items;

identifying products in the picture by reading product templates related to the identified tags from the product database; and

transmitting a list of identified products and their quantities to the server.

13 . The method of claim 12 , wherein identifying the tags is performed by a first image processing application, and identifying products in the picture is performed by a second image processing application.

14 . The method of claim 12 , further comprising filtering the results of identified products based on product dimensions, to eliminate false positives.