Abstract: A system for automatically learning and adapting to the energy usage of an equipment installed at a facility or many pieces of equipment at a plurality of facilities, where the system is provided with an initial baseline energy usage signature for the equipment, which is modified by measured energy usage and by at least one peripheral sensor measurement data to create a modified energy usage signature. The system uses artificial intelligence to learn and adapt the baseline energy usage signature to learn the business operation and account for external variables such as temperature variance and increased business flow or an interaction between devices. The smart system can identify when a piece of equipment falls outside of “normal” operation and determines what automatic action is to be taken for that piece of equipment.

Abstract: A system for automatically learning and adapting to the energy usage of an equipment installed at a facility or many pieces of equipment at a plurality of facilities, where the system is provided with an initial baseline energy usage signature for the equipment, which is modified by measured energy usage and by at least one peripheral sensor measurement data to create a modified energy usage signature. The system uses artificial intelligence to learn and adapt the baseline energy usage signature to learn the business operation and account for external variables such as temperature variance and increased business flow or an interaction between devices. The smart system can identify when a piece of equipment falls outside of “normal” operation and determines what automatic action is to be taken for that piece of equipment.

Abstract: A system for automatically learning and adapting to the energy usage of an equipment installed at a facility or many pieces of equipment at a plurality of facilities, where the system is provided with an initial baseline energy usage signature for the equipment, which is modified by measured energy usage and by at least one peripheral sensor measurement data to create a modified energy usage signature. The system uses artificial intelligence to learn and adapt the baseline energy usage signature to learn the business operation and account for external variables such as temperature variance and increased business flow or an interaction between devices. The smart system can identify when a piece of equipment falls outside of “normal” operation and determines what automatic action is to be taken for that piece of equipment.

Abstract: Provided is a system for comparing telecommunications resources between a first company and a group of companies. A storage is accessible by a system computer, the computer having a network connection. An interface module allows the first company to access the system computer, and a comparison module receives a comparison request. The comparison request includes a group selection and a criteria selection that includes telecommunications services criteria associated with a telecommunication. The comparison module compares the telecommunications services criteria data related to the first company with telecommunications services criteria data related to the group. A telecommunications metric module generates a telecommunications metric related to the comparison of the telecommunications services criteria data of the first and second companies.