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

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.

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.