AUTOMATED RESUPPLY BASED ON SENSOR DATA
System for resupplying a consumable good based on sensors placed to measure the level or flow of a good, and using the data produced in predictive systems to determine the likelihood of running out of a good before resupply is likely to arrive, and triggering an order which arrives before supply is exhausted.
1 . A system for estimating a time to reorder consumable goods comprising:
(a) a likelihood of resupply arriving table indicating a likely time for arrival of goods being shipped to a consumer;
(b) a likelihood of running out table indicating a likely time for goods running out by said consumer based upon a sensor sensing said consumable goods;
(c) a consumer configuration table including configuration settings by said consumer;
(d) an order generation engine that determines a time to said reorder said consumable goods based upon said likelihood of resupply arriving table, said likelihood of running out table, and said consumer configuration table.
2 . The system of claim 1 further comprising a combination engine that determines a first likelihood based upon said likelihood of resupplying arriving table and said likelihood of running out table.
3 . The system of claim 2 wherein said order generation engine determines said time to said reorder said consumable goods based upon said first likelihood and said consumer configuration table.
4 . The system of claim 1 wherein said likelihood of resupply arriving table is further based upon at least one of a shipping and an order processing time for said consumable goods.
5 . The system of claim 4 wherein said likelihood of resupply arriving table is further based upon a vendor of said consumable goods.
6 . The system of claim 5 wherein said likelihood of resupply arriving table is further based upon a geographic source of said consumable goods and a geographic destination of said consumable goods.
7 . The system of claim 1 wherein said consumer configuration table is further based upon a day of week preference.
8 . The system of claim 1 wherein said consumer configuration table is further based upon a month preference.
9 . The system of claim 1 wherein said consumer configuration table is further based upon a season preference.
10 . The system of claim 1 wherein said consumer configuration table is further based upon a preference to whether said consumable good is early or late.
11 . The system of claim 1 wherein said likelihood of running out table is further based upon aggregate user data.
12 . The system of claim 1 wherein said likelihood of running out table is further based upon aggregate sensor data.
13 . The system of claim 1 wherein said likelihood of running out table is further based upon aggregate environmental data.
14 . The system of claim 1 wherein said likelihood of running out table is further based upon an aggregate model based upon aggregate user data, aggregate sensor data, and aggregate environmental data.
15 . The system of claim 14 wherein said likelihood of running out table is further based upon an estimating engine based upon user data, sensor data, and environmental data.
16 . The system of claim 1 wherein said estimating engine is further based upon said aggregate model.
17 . The system of claim 1 wherein said consumable goods are maintained within a carafe that includes said sensor integrated therein.
18 . The system of claim 1 wherein said sensor is provided together with said consumable goods and said order generation engine automatically provides said reorder of said consumable goods.
19 . The system of claim 1 wherein said order generation engine provides said reorder of other consumable goods different than said consumable goods.
20 . The system of claim 1 wherein said order generation engine is configurable to different said consumable goods for said sensor.