Abstract: The present invention leverages smart home technology to enhance energy efficiency generally and to provide an energy-efficient demand management solution. A Home System Configuration Manager, coupled with a Behavior Learning Engine and a User Goal Manager, iteratively modify Home System Configurations over time to address inherent conflicts among (and continuously refine) stated user goals. The present invention further comprises a novel Virtual Facilities Manager architecture that optimizes home health by combining multiple prediction engines, fed by continuously monitored and processed sensor-based and environmental data (historical as well as current), with an integrated Homecare Network of homeowners and service and other providers. This enables a continuous feedback process which detects and addresses abnormal conditions by issuing contextual alerts with associated actions (related alert-action pairs) in an iterative manner over time.

Abstract: The present invention comprises a novel Virtual Facilities Manager architecture that optimizes home health by combining multiple prediction engines, fed by continuously monitored and processed sensor-based and environmental data (historical as well as current), with an integrated Homecare Network of homeowners and service and other providers. This enables a continuous feedback process in which abnormal conditions (symptoms of an underlying problem, including suboptimal performance, as well as systemic scores exceeding predefined thresholds) are detected and addressed by issuing contextual alerts with associated actions (related alert-action pairs) in an iterative manner over time. By maintaining a Home Health Record including Scores (e.g., reliability and energy efficiency) representing the systemic state of one or more homes, the present invention enables connected providers to offer personalized provider services to targeted subsets of existing and prospective customers.

Abstract: The present invention comprises a novel Virtual Facilities Manager architecture that optimizes home health by combining multiple prediction engines, fed by continuously monitored and processed sensor-based and environmental data (historical as well as current), with an integrated Homecare Network of homeowners and service and other providers. This enables a continuous feedback process in which abnormal conditions (symptoms of an underlying problem, including suboptimal performance) are detected and addressed by issuing contextual alerts with associated actions (related alert-action pairs) in an iterative manner over time. By maintaining a Home Health Record including Scores (e.g., reliability and energy efficiency) representing the systemic state of one or more homes, the present invention detects not only maintenance issues, but also suboptimal performance “problems,” and addresses them with the same iterative troubleshooting approach until such scores return to an acceptable level.

Abstract: The present invention comprises a novel Virtual Facilities Manager architecture that optimizes home health by combining multiple prediction engines, fed by continuously monitored and processed sensor-based and environmental data (historical as well as current), with an integrated Homecare Network of homeowners and service and other providers. This enables a continuous feedback process in which abnormal conditions (symptoms of an underlying problem, including suboptimal performance) are detected and addressed by issuing contextual alerts with associated actions (related alert-action pairs) in an iterative manner over time. By maintaining a Home Health Record including Scores (e.g., reliability and energy efficiency) representing the systemic state of one or more homes, the present invention detects not only maintenance issues, but also suboptimal performance “problems,” and addresses them with the same iterative troubleshooting approach until such scores return to an acceptable level.