Abstract: The following relates generally to light detection and ranging (LIDAR). In some embodiments, a homeowners insurance quote is produced based upon data received from a LIDAR camera. For instance, in some embodiments, a system: receives light detection and ranging (LIDAR) data generated from one or more LIDAR cameras; analyzes the LIDAR data to determine or identify one or more features or characteristics of a home; and generates an electronic homeowners insurance quote based upon, at least in part, the one or more features or characteristics of the home determined or identified from the LIDAR data.

Abstract: A computer system including sensor and alternative power technologies for enhancing waste disposal and energy efficiency using is provided. The computer system may be configured to receive waste data and recycling data from at least one sensor located proximate to a waste bin, and determine a level of waste in the waste bin based upon the received waste data, and a level of contamination of the waste bin based upon the received recycling data. The computer system may be also configured to determine whether collection of waste in the waste bin or decontamination of the waste bin is required. The computer system may be further configured to generate an alert including information corresponding collection or decontamination of the waste bin, and transmit the alert to one or more client devices associated with at least one user.

Abstract: A computer system for analyzing and mitigating risks associated with a building is provided. The computer system is configured to: (i) receive environment data from the at least one sensor; (ii) receive building data from the at least one database; (iii) utilize a trained machine learning model to determine at least one potential risk associated with the building based upon the environment data and the building data; (iv) generate a building risk profile that includes the at least one potential risk associated with the building; and/or (v) generate a risk mitigation output based upon at least one of the building risk profile and the at least one potential risk, wherein the risk mitigation output includes at least one of a risk alert, a risk mitigation recommendation, and risk mitigation instructions. Computer systems for analyzing and mitigation risks associated with a city, a user, and an event are also provided.

Abstract: The following relates generally to light detection and ranging (LIDAR) and artificial intelligence (AI). In some embodiments, a system: receives LIDAR data generated from a LIDAR camera; measures a plurality of dimensions of a landscape based upon processor analysis of the LIDAR data; builds a 3D model of the landscape based upon the measured plurality of dimensions, the 3D model including: (i) a structure, and (ii) a vegetation; and displays a representation of the 3D model.

Abstract: A computer system including sensor and alternative power technologies for enhancing waste disposal and energy efficiency using is provided. The computer system may be configured to receive waste data and recycling data from at least one sensor located proximate to a waste bin, and determine a level of waste in the waste bin based upon the received waste data, and a level of contamination of the waste bin based upon the received recycling data. The computer system may be also configured to determine whether collection of waste in the waste bin or decontamination of the waste bin is required. The computer system may be further configured to generate an alert including information corresponding collection or decontamination of the waste bin, and transmit the alert to one or more client devices associated with at least one user.

Abstract: The following relates generally to light detection and ranging (LIDAR) and artificial intelligence (AI). In some embodiments, a system: receives light detection and ranging (LIDAR) data generated from a LIDAR camera; receives preexisting utility line data; and determines a location of the utility line based upon: (i) the received LIDAR data, and (ii) the received preexisting utility line data.

Abstract: A computer system including sensor technology for detecting environmental pollution levels in a water source and alerting users in real-time of the environmental pollution levels within the water source is provided. The computer system may be configured to receive pollution data from at least one sensor, analyze the received pollution data, and determine a level of environmental pollution in the water source based upon the analysis. The computer system may be also configured to determine, based upon the analysis of the pollution data, whether the water source is polluted, and generate an alert including information of the polluted water source. The computer system is further configured to generate a user list including at least one user of the water source, and transmit the alert to one or more client devices associated with the at least one user to notify the at least one user that the water source is polluted.

Abstract: The following relates generally to light detection and ranging (LIDAR) and artificial intelligence (AI). In some embodiments, a system: receives light detection and ranging (LIDAR) data generated from a LIDAR camera; receives preexisting utility line data; and determines a location of the utility line based upon: (i) the received LIDAR data, and (ii) the received preexisting utility line data.

Abstract: The following relates generally to light detection and ranging (LIDAR). In some embodiments, an inventory list of personal belongings is generated based upon data received from a LIDAR camera. For instance, in some embodiments a system: receives LIDAR data generated from one or more LIDAR cameras; analyzes the LIDAR data to determine or identify one or more personal articles or insurable assets; and generates an electronic inventory list of personal belongings based upon the one or more personal articles or insurable assets determined or identified from the LIDAR data.

Abstract: Systems and methods are described for evaluating and analyzing home data to generate a home score. The method may include: (1) retrieving home data for a property; (2) determining, based upon the home data for the property, one or more home score factors, wherein the determining may include: (i) analyzing, using a trained machine learning data evaluation model, the home data for the property to determine home characteristic data for the property, (ii) analyzing, using the trained machine learning data evaluation model, the home data for the property to determine a likelihood of loss associated with the property, and (iii) determining, based upon the home characteristic data for the property and the likelihood of loss associated with the property; and (3) generating, based upon the one or more home score factors, a home score for the property.

Abstract: Systems and methods are described for evaluating and analyzing home data to generate a home score. The method may include: (1) retrieving home data for a property; (2) determining, based upon the home data for the property, one or more home score factors, wherein the determining may include: (i) analyzing, using a trained machine learning data evaluation model, the home data for the property to determine home characteristic data for the property, (ii) analyzing, using the trained machine learning data evaluation model, the home data for the property to determine a likelihood of loss associated with the property, and (iii) determining, based upon the home characteristic data for the property and the likelihood of loss associated with the property; and (3) generating, based upon the one or more home score factors, a home score for the property.

Abstract: Systems and methods are described for evaluating and analyzing home data to generate a home score. The method may include: (1) retrieving at least one of home data for a property or user data for a user; (2) determining, using a trained machine learning evaluation model, one or more home score factors based upon at least one of the home data or the user data; (3) receiving, from the user, a home modification indication; (4) modifying, based upon the home modification indication, at least one of the one or more home score factors to create one or more modified home score factors; and (5) generating, based upon the one or more modified home score factors, a home score for the property.

Abstract: Systems and methods are described for evaluating and analyzing home data to generate a home score. The method may include: (1) retrieving at least one of home data for a property or user data for a user; (2) determining, using a trained machine learning evaluation model, one or more home score factors based upon at least one of the home data or the user data; (3) receiving, from the user, a home modification indication; (4) modifying, based upon the home modification indication, at least one of the one or more home score factors to create one or more modified home score factors; and (5) generating, based upon the one or more modified home score factors, a home score for the property.

Abstract: A computer system including sensor technology for detecting environmental pollution levels in a water source and alerting users in real-time of the environmental pollution levels within the water source is provided. The computer system may be configured to receive pollution data from at least one sensor, analyze the received pollution data, and determine a level of environmental pollution in the water source based upon the analysis. The computer system may be also configured to determine, based upon the analysis of the pollution data, whether the water source is polluted, and generate an alert including information of the polluted water source. The computer system is further configured to generate a user list including at least one user of the water source, and transmit the alert to one or more client devices associated with the at least one user to notify the at least one user that the water source is polluted.

Abstract: The following relates generally to light detection and ranging (LIDAR). In some embodiments, an inventory list of personal belongings is generated based upon data received from a LIDAR camera. For instance, in some embodiments a system: receives LIDAR data generated from one or more LIDAR cameras; analyzes the LIDAR data to determine or identify one or more personal articles or insurable assets; and generates an electronic inventory list of personal belongings based upon the one or more personal articles or insurable assets determined or identified from the LIDAR data.

Abstract: A computer system including sensor and alternative power technologies for enhancing waste disposal and energy efficiency using is provided. The computer system may be configured to receive waste data and recycling data from at least one sensor located proximate to a waste bin, and determine a level of waste in the waste bin based upon the received waste data, and a level of contamination of the waste bin based upon the received recycling data. The computer system may be also configured to determine whether collection of waste in the waste bin or decontamination of the waste bin is required. The computer system may be further configured to generate an alert including information corresponding collection or decontamination of the waste bin, and transmit the alert to one or more client devices associated with at least one user.

Abstract: The following relates generally to light detection and ranging (LIDAR). In some embodiments, a homeowners insurance quote is produced based upon data received from a LIDAR camera. For instance, in some embodiments, a system: receives light detection and ranging (LIDAR) data generated from one or more LIDAR cameras; analyzes the LIDAR data to determine or identify one or more features or characteristics of a home; and generates an electronic homeowners insurance quote based upon, at least in part, the one or more features or characteristics of the home determined or identified from the LIDAR data.

Abstract: The following relates generally to light detection and ranging (LIDAR). In some embodiments, a homeowners insurance quote is produced based upon data received from a LIDAR camera. For instance, in some embodiments, a system: receives light detection and ranging (LIDAR) data generated from one or more LIDAR cameras; analyzes the LIDAR data to determine or identify one or more features or characteristics of a home; and generates an electronic homeowners insurance quote based upon, at least in part, the one or more features or characteristics of the home determined or identified from the LIDAR data.

Abstract: The following relates generally to light detection and ranging (LIDAR) and artificial intelligence (AI). In some embodiments, a system: receives LIDAR data generated from a LIDAR camera; measures plurality of dimensions of the home based upon processor analysis of the LIDAR data; builds a 3D model of the home based upon the measured plurality of dimensions; and displays a representation of the 3D model by visually navigating through the 3D model.

Abstract: The following relates generally to light detection and ranging (LIDAR) and artificial intelligence (AI). In some embodiments, a system: receives sensor data via wireless communication; updates an electronic inventory of goods within a store based upon the received sensor data associated with the item movement or purchase; receives an electronic order of goods from a customer mobile device via wireless communication or data transmission over one or more radio frequency links; determines if the goods in the electronic order received from the customer are still available; generates a LIDAR-based virtual map of the store; determines a location of the goods in the electronic order that are still available; overlays the determined location of the goods onto the LIDAR-based virtual map of the store; and displays an updated LIDAR-based virtual map of the store displaying aisles of the store and the determined location of the goods within the store.