Abstract: An energy management system is disclosed for optimizing energy usage of HVAC equipment in a building complex. The energy management system is configured to be integrated into an existing Building Automation System (“BAS system”) in order to process the data points in a less time consuming and efficient manner relative to known systems that map one point at a time. The BAS system data points are “point mapped”, i.e., uploaded to a file in the “cloud”, and are updated continuously as a function of time and deposited in a “bucket” in which the data points are unfiltered. These data points can then be filtered by node path and equipment in order to bulk tag equipment and bulk tag points in each of the buildings. These bulk tagged points data points can then be linked to specific rules in an analytical rules library. The system automatically applies predetermined analytical rules to tagged HVAC data points without specific knowledge of the rule by the user.

Abstract: An energy management system is disclosed for optimizing energy usage of HVAC equipment in a building complex. The energy management system is configured to be integrated into an existing Building Automation System (“BAS system”) in order to process the data points in a less time consuming and efficient manner relative to known systems that map one point at a time. The BAS system data points are “point mapped”, i.e., uploaded to a file in the “cloud”, and are updated continuously as a function of time and deposited in a “bucket” in which the data points are unfiltered. These data points can then be filtered by node path and equipment in order to bulk tag equipment and bulk tag points in each of the buildings. These bulk tagged points data points can then be linked to specific rules in an analytical rules library. The system automatically applies predetermined analytical rules to tagged HVAC data points without specific knowledge of the rule by the user.

Abstract: An energy management system is disclosed for optimizing energy usage of HVAC equipment in a building complex. The energy management system is configured to be integrated into an existing Building Automation System (“BAS system”) in order to process the data points in a less time consuming and efficient manner relative to known systems that map one point at a time. The BAS system data points are “point mapped”, i.e., uploaded to a file in the “cloud”, and are updated continuously as a function of time and deposited in a “bucket” in which the data points are unfiltered. These data points can then be filtered by node path and equipment in order to bulk tag equipment and bulk tag points in each of the buildings. These bulk tagged points data points can then be linked to specific rules in an analytical rules library. The system automatically applies predetermined analytical rules to tagged HVAC data points without specific knowledge of the rule by the user.

Abstract: An energy management system is disclosed for optimizing energy usage of HVAC equipment in a building complex. The energy management system is configured to be integrated into an existing Building Automation System (“BAS system”) in order to process the data points in a less time consuming and efficient manner relative to known systems that map one point at a time. The BAS system data points are “point mapped”, i.e., uploaded to a file in the “cloud”, and are updated continuously as a function of time and deposited in a “bucket” in which the data points are unfiltered. These data points can then be filtered by node path and equipment in order to bulk tag equipment and bulk tag points in each of the buildings. These bulk tagged points data points can then be linked to specific rules in an analytical rules library. The system automatically applies predetermined analytical rules to tagged HVAC data points without specific knowledge of the rule by the user.