Subterranean Water Pressure Sensors

1 . A computer-implemented method of measuring water pressure on a foundation, the method comprising:

receiving, by one or more processors and from one or more sensors, foundation environment data for an environment surrounding the foundation of a structure;

analyzing, by the one or more processors, the foundation environment data to determine one or more properties of the foundation environment, wherein the one or more properties of the foundation environment include at least a foundation water pressure;

generating, by the one or more processors and based at least upon a determination of whether the foundation water pressure reaches a predetermined threshold, a likelihood of damage to the foundation; and

generating, by the one or more processors, an alert based at least upon the likelihood of damage to the foundation.

2 . The computer-implemented method of claim 1 , wherein the foundation environment includes one or more of the foundation, soil, atmosphere, a drain tile, a water pipe, a septic tank, a sewage pipe, a pump, or a sump pit.

3 . The computer-implemented method of claim 1 , further comprising:

communicating, from the one or more sensors to the one or more processors, the foundation environment data wirelessly.

4 . The computer-implemented method of claim 1 , further comprising:

analyzing, by the one or more processors, the foundation environment data to determine one or more properties including one or more of a chemical composition, a core analysis, a quantity, a humidity, a flow rate, a level, a temperature, a pressure, a capacitance, or a resistance of the foundation environment.

5 . The computer-implemented method of claim 1 , wherein the one or more sensors include one or more of a moisture, an electrical, an optical, an ultrasonic, an acoustic, a pressure, a transducer, a MEMS, a chemical, an odor, a thermal, an infrared, location, a bubbler, a float, a capacitance or a resistance sensor.

6 . The computer-implemented method of claim 1 , further comprising:

generating, by the one or more processors, a determination of one or more of a leak, a structural abnormality, a draining abnormality, an evaporation abnormality, or an operational abnormality in the foundation environment.

7 . The computer-implemented method of claim 6 , further comprising:

generating, by the one or more processors, a determination of an abnormal pump operation based upon correlating a sump pump evacuation rate with a historical pump evacuation rate under various conditions.

8 . The computer-implemented method of claim 1 , further comprising:

generating, by the one or more processors, a determination of a water table level by determining one or more of a capacitance or resistance between conductive materials.

9 . The computer-implemented method of claim 1 , further comprising:

generating, by the one or more processors, a determination of a sewage pipe structural abnormality based at least upon determining an odor in a foundation environment atmosphere.

10 . The computer-implemented method of claim 1 , further comprising:

determining, by the one or more processors, a fill level of a septic tank.

11 . The computer-implemented method of claim 1 , wherein determining a likelihood of damage to the foundation includes determining one or more of an impending, a potential or an actual damage to the foundation.

12 . The computer-implemented method of claim 1 , wherein generating the alert includes generating one or more of a visual alert, an audio alert, or an electronic alert.

13 . The computer-implemented method of claim 1 , wherein the alert is received by a mobile device.

14 . The computer implemented method of claim 1 , wherein one or more of:

analyzing the foundation environment data includes analyzing the foundation environment data based upon one or more of artificial intelligence, machine learning, a neural network, or deep learning to determine the one or more properties of the foundation environment; or

generating the likelihood of damage to the foundation includes generating the likelihood of damage to the foundation based upon one or more of artificial intelligence, machine learning, a neural network, or deep learning.

15 . A computer system for measuring water pressure on a foundation, the computer system comprising:

one or more processors; and

one or more sensors;

the one or more processors configured to:

receive from the one or more sensors foundation environment data for an environment surrounding the foundation of a structure;

analyze the foundation environment data to determine one or more properties of the foundation environment, wherein the one or more properties of the foundation environment include at least a foundation water pressure;

generate based at least upon a determination of whether the foundation water pressure reaches a predetermined threshold, a likelihood of damage to the foundation; and

generate an alert based at least upon the likelihood of damage to the foundation.

16 . The computer system of claim 1 , wherein the foundation environment includes one or more of the foundation, soil, atmosphere, a drain tile, a water pipe, a septic tank, a sewage pipe, a pump, or a sump pit.

17 . The computer system of claim 1 , the one or more processors further configured to:

analyze the foundation environment data to determine one or more properties including one or more of a chemical composition, a core analysis, a quantity, a humidity, a flow rate, a level, a temperature, a pressure, a capacitance, or a resistance of the foundation environment.

18 . The computer system of claim 1 , wherein the one or more sensors include one or more of a moisture, an electrical, an optical, an ultrasonic, an acoustic, a pressure, a transducer, a MEMS, a chemical, an odor, a thermal, an infrared, location, a bubbler, a float, a capacitance or a resistance sensor.

19 . The computer system of claim 1 , the one or more processors further configured to:

generate a determination of one or more of a leak, a structural abnormality, a draining abnormality, an evaporation abnormality, or an operational abnormality in the foundation environment.

20 . The computer system of claim 15 , wherein one or more of:

analyze the foundation environment data includes analyzing the foundation environment data based upon one or more of artificial intelligence, machine learning, a neural network, or deep learning to determine the one or more properties of the foundation environment; or

generate the likelihood of damage to the foundation includes generating the likelihood of damage to the foundation based upon one or more of artificial intelligence, machine learning, a neural network, or deep learning.