Devices, methods, and systems for data-driven acceleration of deployed services

A system for data-driven acceleration of deployed services, comprising:

• a database configured to store a plurality of previously calculated model solutions represented as a plurality of case pairs, wherein each of the plurality of case pairs comprises a first value and a second value, the first value representative of the number of actual building features and an efficiency associated with the number of building features for a first building, wherein the first value efficiency is a predicted quantity of resources for a particular time required to maintain a particular temperature within the first building based on the number of building features, wherein the second value representative of deployed heating, ventilation, and air conditioning (HVAC) resources based on a combination of the number of building features and environmental features of the first building, and wherein the second value is representative of a model predictive control (MPC) value that was utilized to deploy resources to the first building at the particular time;
• a ranking engine configured to rank the plurality of corresponding case pairs based on performance results of the case pairs;
• and
• a deployment engine configured to:
• receive a number of actual building feature values for a second building;
• determining a building value for the second building;
• compare the building value for the second building to the first value of the previously calculated model solutions;
• identify a first value from a particular previously calculated model solution that corresponds to the building value for the second building based on the comparison;
• and
• apply the MPC value of the previously calculated model solution to the second building to;
• and
• deploy HVAC resources to the second building based on the previously calculated model solution.

A method for data-driven acceleration of deployed services, comprising:

• ranking a plurality of case pairs based on performance results of the case pairs, wherein the plurality of case pairs each include a first value and a second value, the first value representative of a number of actual building features and an efficiency associated with the number of building features of a first building, wherein the first value efficiency is a predicted quantity of resources for a particular time required to maintain a particular temperature within the first building based on the number of building features, wherein the second value is representative of deployed heating, ventilation, and air conditioning (HVAC) resources based on a combination of the number of building features and environmental features of the first building, wherein the second value is representative of a model predictive control (MPC) value that was utilized to deploy resources to first building at the particular time;
• receiving a number of actual building feature values for a second building;
• determining a building value for the second building;
• comparing the building value for the second building to the first value of the previously calculated model solutions
• identifying a first value from a particular case pair that corresponds to the building value for the second building based on the comparison;
• applying the MPC value of the particular case pair to the second building;
• and
• deploying, HVAC resources to the second building utilizing the MPC value of the particular case pair.