METHOD AND SYSTEM FOR ACCURATELY ESTIMATING AMOUNT OF MATERIALS IN STORES
A method and system are disclosed for estimating quantities of stored materials. Stores data can be previously collected by a person (manual stores) using manually collected data and higher fidelity stores data can be collected by automated sensors from other similar stores (monitored stores). The system takes as initial input historical data from a set of monitored stores and historical data for a set of manual stores. The system continues to receive monitored stores data and manual stores data over time. The system applies a method to the input data to generate estimates of remaining material quantities in the set of manual stores since their latest manual data collection.
1 . A method for estimating inventory level of an unmonitored store, the method comprising:
receiving first data from one or more sensors providing inventory levels of one or more monitored stores;
receiving second data associated with the unmonitored store;
generating a model to estimate the inventory level of the unmonitored store based at least on the first data and the second data; and
estimating a current inventory level for the unmonitored store based on the model.
2 . The method of claim 1 , wherein the second data comprises at least one of historical resupply dates for the unmonitored store and historical inventory level measurements for the unmonitored store.
3 . The method of claim 1 or 2 , further comprising measuring the first data at a first frequency and measuring the second data at a second frequency lower than the first frequency.
4 . The method of any one of claims 1 - 3 , wherein the model is a first model, and the generating comprises generating the first model for a first seasonal time period, and the method comprises generating a second model for a second seasonal time period different from the first seasonal time period.
5 . The method of any one of claims 1 - 4 , further comprising:
receiving third data associated with the unmonitored store; and
updating the model to more accurately predict the inventory level of the unmonitored store based on the third data.
6 . The method of claim 5 , further comprising receiving fourth data from the one or more sensors associated with the one or more monitored stores.
7 . The method of claim 6 , further comprising applying the fourth data to the model to estimate a consumption rate of the unmonitored store.
8 . The method of claim 6 or 7 , wherein receiving the fourth data comprises receiving a most recent inventory level measurement for the one or more monitored stores.
9 . A computer program product including one or more non-transitory machine-readable media having instructions encoded thereon that when executed by at least one processor causes a process for estimating inventory levels of an unmonitored store to be carried out, the process comprising:
receiving first data from one or more sensors providing inventory levels of one or more monitored stores;
receiving second data associated with the unmonitored store;
generating a model to predict the inventory level of the unmonitored store based at least on the first data and the second data; and
estimating a current inventory level for the unmonitored store based on the model.
10 . The computer program product of claim 9 , wherein the second data comprises at least one of historical resupply dates for the unmonitored store and historical inventory level measurements for the unmonitored store.
11 . The computer program product of claim 9 or 10 , the process further comprising measuring the first data at a first frequency and measuring the second data at a second frequency lower than the first frequency.
12 . The computer program product of any one of claims 9 - 11 , wherein the model is a first model, and the generating comprises generating the first model for a first seasonal time period, and the method comprises generating a second model for a second seasonal time period different from the first seasonal time period.
13 . The computer program product of any one of claims 9 - 12 , the process further comprising:
receiving third data associated with the unmonitored store; and
updating the model to more accurately predict the inventory level of the unmonitored store based on the third data.
14 . The computer program product of claim 13 , the process further comprising receiving fourth data from the one or more sensors associated with the one or more monitored stores.
15 . The computer program product of claim 14 , the process further comprising applying the fourth data to the model to estimate a consumption rate of the unmonitored store.
16 . The computer program product of claim 14 or 15 , wherein receiving the fourth data comprises receiving a most recent inventory level measurement for the one or more monitored stores.
17 . A method for estimating a time at which an unmonitored store's inventory will be depleted, the method comprising:
receiving first data from one or more sensors providing inventory levels of one or more monitored stores;
receiving second data associated with the unmonitored store;
generating a model to estimate the time at which the unmonitored store's inventory will be depleted based at least on the first data and the second data; and
estimating the time at which the unmonitored store's inventory will be depleted based on the model.
18 . The method of claim 17 , wherein the second data comprises at least one of historical resupply dates for the unmonitored store and historical inventory level measurements for the unmonitored store.
19 . The method of claim 17 or 18 , further comprising measuring the first data at a first frequency and measuring the second data at a second frequency lower than the first frequency.
20 . The method of any one of claims 17 - 19 , wherein the model is a first model, and the generating comprises generating the first model for a first seasonal time period, and the method comprises generating a second model for a second seasonal time period different from the first seasonal time period.
21 . The method of any one of claims 17 - 20 , further comprising:
receiving third data associated with the unmonitored store; and
updating the model to more accurately estimate the time at which the unmonitored store's inventory will be depleted based on the third data.
22 . The method of claim 21 , further comprising receiving fourth data from the one or more sensors associated with the one or more monitored stores.
23 . The method of claim 22 , further comprising applying the fourth data to the model to estimate a consumption rate of the unmonitored store.
24 . The method of claim 22 or 23 , wherein receiving the fourth data comprises receiving a most recent inventory level measurement for the one or more monitored stores.
25 . A computer program product including one or more non-transitory machine-readable media having instructions encoded thereon that when executed by at least one processor causes a process for estimating a time at which an unmonitored store's inventory will be depleted to be carried out, the process comprising:
receiving first data from one or more sensors providing inventory levels of one or more monitored stores;
receiving second data associated with the unmonitored store;
generating a model to estimate the time at which the unmonitored store's inventory will be depleted based at least on the first data and the second data; and
estimating the time at which the unmonitored store's inventory will be depleted based on the model.
26 . The computer program product of claim 25 , wherein the second data comprises at least one of historical resupply dates for the unmonitored store and historical inventory level measurements for the unmonitored store.
27 . The computer program product of claim 25 or 26 , the process further comprising measuring the first data at a first frequency and measuring the second data at a second frequency lower than the first frequency.
28 . The computer program product of any one of claims 25 - 27 , wherein the model is a first model, and the generating comprises generating the first model for a first seasonal time period, and the method comprises generating a second model for a second seasonal time period different from the first seasonal time period.
29 . The computer program product of any one of claims 25 - 28 , the process further comprising:
receiving third data associated with the unmonitored store; and
updating the model to more accurately predict the inventory level of the unmonitored store based on the third data.
30 . The computer program product of claim 29 , the process further comprising receiving fourth data from the one or more sensors associated with the one or more monitored stores.
31 . The computer program product of claim 30 , the process further comprising applying the fourth data to the model to estimate a consumption rate of the unmonitored store.
32 . The computer program product of claim 30 or 31 , wherein receiving the fourth data comprises receiving a most recent inventory level measurement for the one or more monitored stores.