VECTOR-BASED CHARACTERIZATIONS OF PRODUCTS AND INDIVIDUALS WITH RESPECT TO PERSONAL PARTIALITIES

1 . A system for ordering a life of a customer; the system comprising:

a sensor that is configured to obtain readings of the sensed customer physical characteristic or sensed customer activity over time, the readings forming a time series of data, the sensor configured to transmit the time series of data onto the network;

a network coupled to the sensor,

a control circuit, the control circuit being coupled to the sensor and the network, the control circuit configured to:

receive the times series of data and transform the time series of data into a frequency series of data;

determine a primary frequency of the frequency series of data;

determine whether a primary frequency has changed by more than a predetermined amount compared to a baseline frequency indicating a disorder exists in an order to the life of the customer;

when the primary frequency has changed by more than the predetermined amount, determine an action; such than when the action is implemented, the disorder is minimized.

2 . The system of claim 1 , further comprising:

a data storage device that is configured to store a plurality of customer partiality vectors of a customer, wherein each of the customer partiality vectors comprises a value for a customer that is programmatically linked to a strength of the value, wherein the customer partiality vectors of the customer collectively define the order to the life of the customer, wherein the data storage device includes a mapping between the primary frequencies of a sensed customer physical characteristic or a sensed customer activity, and actions;

and wherein the action is determined by the mapping, and such that the order as defined by the customer partiality vectors is maximized when the action is implemented.

3 . The system of claim 2 , wherein the actions in the mapping change over time.

4 . The system of claim 2 , wherein the mapping is determined by an analysis of the actions taken by other customers having the same or similar order as the customer.

5 . The system of claim 1 , wherein the readings are associated with a heartbeat, a pulse, a calorie expenditure, a breathing characteristic, a temperature, a motion, or a blood pressure of the customer.

6 . The system of claim 1 , wherein the action is the provision of a product or a service.

7 . The system of claim 1 , wherein the control circuit is deployed at the cloud.

8 . The system of claim 1 , wherein the control circuit is disposed locally at a customer site and not remotely from the customer.

9 . The system of claim 1 , wherein the action is sending a message to the customer.

10 . The system of claim 1 , wherein the age of the customer is used at least in part to determine the action.

11 . A method for ordering a life of a customer, the method comprising:

obtaining readings of the sensed physical characteristic of the customer or the sensed customer activity over time, the readings forming a time series of data, and transmitting the time series of data to a control circuit;

receiving the times series of data at the control circuit and transforming the time series of data into a frequency series of data;

determining at the control circuit a primary frequency of the frequency series of data;

determining at the control circuit whether the primary frequency has changed by more than a predetermined amount compared to a baseline frequency indicating a disorder exists in the order of the life of the customer, and when the primary frequency has changed by more than the predetermined amount, determining an action according to the mapping, such than when the action is implemented, the disorder is minimized and the order as defined by the customer partiality vectors is maximized.

12 . The method of claim 11 , further comprising:

storing a plurality of customer partiality vectors of a customer in a data storage device, wherein each of the customer partiality vectors comprises a value for a customer that is programmatically linked to a strength of the value, wherein the customer partiality vectors of the customer collectively define an order to the life of the customer, and storing a mapping between primary frequencies of a sensed customer physical characteristic or a sensed customer activity, and actions; and

wherein the action is determined according to the mapping, such than when the action is implemented, the disorder is minimized and the order as defined by the customer partiality vectors is maximized.

13 . The method of claim 12 , wherein the actions in the mapping change over time.

14 . The method of claim 12 , wherein the mapping is determined by an analysis of the actions taken by other customers having the same or similar order as the customer.

15 . The method of claim 11 , wherein obtaining the reading comprises obtaining a heartbeat, a pulse, a calorie expenditure, a breathing characteristic, a temperature, a motion, or a blood pressure of the customer.

16 . The method of claim 11 , wherein the action is the provision of a product or a service.

17 . The method of claim 11 , wherein the control circuit is deployed at the cloud.

18 . The method of claim 11 , wherein the control circuit is disposed locally at a customer site and not remotely from the customer.

19 . The method of claim 11 , wherein the action is sending a message to the customer.

20 . The method of claim 11 , wherein the age of the customer is used at least in part to determine the action.