Systems and methods for generating a home score and modifications for a user

1. A computer-implemented method for evaluating and gamifying maintenance for a property by a user, the computer-implemented method comprising:

retrieving, by one or more processors, home data for a first property;

determining, by the one or more processors and using a first trained machine learning evaluation model, one or more home score factors based upon at least the home data;

weighting, by the one or more processors, each of the one or more home score factors to generate one or more weighted home score factors;

generating, by the one or more processors and based upon the one or more weighted home score factors, a home score for the first property;

determining, by the one or more processors and using a second trained machine learning evaluation model, that one or more additional properties are similar to the first property;

retrieving, by the one or more processors, past hazard data associated with a second property of the one or more additional properties;

generating, by the one or more processors and based upon at least the past hazard data and at least one of the one or more weighted home score factors, a home modification recommendation for the first property; and

performing, by the one or more processors and responsive to an indication to train the first trained machine learning evaluation model including a condition that the home score is accurately representative of the first property, additional training of the first trained machine learning evaluation model using at least (1) the one or more home score factors, (ii) the home data for the first property, and (iii) home data for at least some of the one or more additional properties.

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

receiving an indication that the user implemented a modification in accordance with the home modification recommendation; and

modifying, based upon at least the past hazard data, the home score to create a modified home score in response to receiving the indication.

3. The computer-implemented method of claim 1 , wherein each of the one or more home score factors has an equal weight.

4. The computer-implemented method of claim 1 , wherein the one or more home score factors are one or more first home score factors and generating the home modification recommendation includes:

determining one or more second home score factors based on at least the past hazard data;

comparing the one or more second home score factors with the one or more first home score factors to determine a particular second home score factor is greater than a corresponding first home score factor; and

generating the home modification recommendation such that the home modification recommendation corresponds to the particular second home score factor.

5. The computer-implemented method of claim 1 , wherein the home score is a first home score, and generating the home modification recommendation includes:

determining, based upon at least the past hazard data, a home modification implemented for the second property that caused an improvement to a second home score corresponding to the second property; and

generating the home modification recommendation such that the home modification recommendation includes the determined home modification.

6. The computer-implemented method of claim 5 , further including:

modifying the home score based at least upon the improvement to the second home score.

7. The computer-implemented method of claim 1 , wherein the one or more home score factors include: (i) a fire hazard score, (ii) a safety score, (iii) a weather hazard score, (iv) a property feature hazard score, and (v) a potential hazards score.

8. A computing device for evaluating and gamifying maintenance for a property by a user, the computing device comprising:

one or more processors;

a communication unit; and

a non-transitory computer-readable medium coupled to the one or more processors and the communication unit and storing instructions thereon that, when executed by the one or more processors, cause the computing device to:

retrieve home data fora first property;

determine, using a first trained machine learning evaluation model, one or more home score factors based upon at least the home data;

weight each of the one or more home score factors to generate one or more weighted home score factors;

generate, based upon the one or more weighted home score factors, a home score for the first property;

determine, using a second trained machine learning evaluation model, one or more additional properties as similar to the first property;

retrieve past hazard data associated with a second property of the one or more additional properties; generate, based upon at least the past hazard data and at least one of the one or more weighted home score factors, a home modification recommendation for the first property; and

perform, responsive to an indication to train the first trained machine learning evaluation model including a condition that the home score is accurately representative of the first property, additional training of the first trained machine learning evaluation model using at least (i) the one or more home score factors, (ii) the home data for the first property, and (ill) home data for at least some of the one or more additional properties.

9. The computing device of claim 8 , wherein the non-transitory computer-readable medium further stores instructions that, when executed by the one or more processors, cause the computing device to:

receive an indication that the user implemented a modification in accordance with the home modification recommendation; and

modify, based upon at least the past hazard data, the home score to create a modified home score in response to receiving the indication.

10. The computing device of claim 8 , wherein each of the one or more home score factors has an equal weight.

11. The computing device of claim 8 , wherein the one or more home score factors are one or more first home score factors, and generating the home modification recommendation includes:

determining one or more second home score factors based on at least the past hazard data;

comparing the one or more second home score factors with the one or more first home score factors to determine a particular second home score factor is greater than a corresponding first home score factor; and

generating the home modification recommendation such that the home modification recommendation corresponds to the particular second home score factor.

12. The computing device of claim 8 , wherein the home score is a first home score, and generating the home modification recommendation includes:

determining, based upon at least the past hazard data, a home modification implemented for the second property that caused an improvement to a second home score corresponding to the second property; and

generating the home modification recommendation such that the home modification recommendation includes the determined home modification.

13. The computing device of claim 12 , wherein the non-transitory computer-readable medium further stores instructions that, when executed by the one or more processors, cause the computing device to:

modify the home score further based at least upon the improvement to the second home score.

14. The computing device of claim 8 , wherein the one or more home score factors include: (i) a fire hazard score, (ii) a safety score, (iii) a weather hazard score, (iv) a property feature hazard score, and (v) a potential hazards score.

15. A tangible, non-transitory computer-readable medium storing instructions for evaluating and gamifying maintenance for a property by a user that, when executed by one or more processors of a computing device, cause the computing device to:

retrieve home data fora first property;

determine, using a first trained machine learning evaluation model, one or more home score factors based upon at least the home data;

weight each of the one or more home score factors to generate one or more weighted home score factors;

generate, based upon the one or more weighted home score factors, a home score for the first property;

determine, using a second trained machine learning evaluation model, one or more additional properties as similar to the first property;

retrieve past hazard data associated with a second property of the one or more additional properties;

generate, based upon at least the past hazard data and at least one of the one or more weighted home score factors, a home modification recommendation for the first property; and

perform, responsive to an indication to train the first trained machine learning evaluation model including a condition that the home score is accurately representative of the first property, additional training of the first trained machine learning evaluation model using at least (i) the one or more home score factors, (ii) the home data for the first property, and (411) home data for at least some of the one or more additional properties.

16. The tangible, non-transitory computer-readable medium of claim 15 , wherein the tangible, non-transitory computer-readable medium further stores instructions that, when executed by the one or more processors, cause the computing device to:

receive an indication that the user implemented a modification in accordance with the home modification recommendation; and

modify, based upon at least the past hazard data, the home score to create a modified home score in response to receiving the indication.

17. The tangible, non-transitory computer-readable medium of claim 15 , wherein each of the one or more home score factors has an equal weight.

18. The tangible, non-transitory computer-readable medium of claim 15 , wherein the one or more home score factors are one or more first home score factors, and generating the home modification recommendation includes:

determining one or more second home score factors based on at least the past hazard data;

comparing the one or more second home score factors with the one or more first home score factors to determine a particular second home score factor is greater than a corresponding first home score factor; and

generating the home modification recommendation such that the home modification recommendation corresponds to the particular second home score factor.

19. The tangible, non-transitory computer-readable medium of claim 15 , wherein the home score is a first home score, and generating the home modification recommendation includes:

determining, based upon at least the past hazard data, a home modification implemented for the second property that caused an improvement to a second home score corresponding to the second property; and

generating the home modification recommendation such that the home modification recommendation includes the determined home modification.

20. The tangible, non-transitory computer-readable medium of claim 15 , wherein the one or more home score factors include: (i) a fire hazard score, (ii) a safety score, (iii) a weather hazard score, (iv) a property feature hazard score, and (v) a potential hazards score.