Abstract: Channel assignment for wireless access networks is directed toward improved overall communication capability of the networks. A network is formed of wireless access points (APs) coupled via wired (and/or wireless) links and enabled to communicate with clients via radio channels of each of the APs. Local information is collected at each of the APs and processed to determine channel assignments according to a Neighbor Impact Metric (NIM) that accounts for one-hop and two-hop neighbors as well as neighbors not part of the network. Optionally, the NIM accounts for traffic load on the APs. The channel assignments are determined either on a centralized resource (such as a server or one of the APs) or via a distributed scheme across the APs. The local information includes how busy a channel is and local operating conditions such as error rate and interference levels.

Abstract: Channel assignment for wireless access networks is directed toward improved overall communication capability of the networks. A network is formed of wireless access points (APs) coupled via wired (and/or wireless) links and enabled to communicate with clients via radio channels of each of the APs. Local information is collected at each of the APs and processed to determine channel assignments according to a Neighbor Impact Metric (NIM) that accounts for one-hop and two-hop neighbors as well as neighbors not part of the network. Optionally, the NIM accounts for traffic load on the APs. The channel assignments are determined either on a centralized resource (such as a server or one of the APs) or via a distributed scheme across the APs. The local information includes how busy a channel is and local operating conditions such as error rate and interference levels.

Abstract: The present disclosure relates to automated chatbot generation for different domains from available human-to-human chat logs. The systems and methods may be configured to cluster user utterances as well as agent utterances from the human chat logs. A data miner mines intents and entities from the user utterance clustering and mines actions from agent utterances. The intents, entities and actions mined are used to generate a set of stories or flows which are further used by a machine learning engine to train the chatbot. The stories or flows are also generated automatically by mapping the intents with the actions.

Abstract: Examples of employee concierge are provided. In an example, an issue may be determined for an employee. The issue may be determined based on a query shared by the employee or upon occurrence of an unusual event. The unusual event may be indicative of a deviation in behaviour and routine of the employee. A session may be initiated and the issue may be parsed to determine a context. A bot may be selected from multiple bots for the issue where each bot includes information relating to a solution to address the issue. Data associated with the issue may be collected from a central database and other bots. The data may then be analyzed to determine a solution. The solution comprises a response to the query and a suggestion to mitigate the unusual event.

Abstract: Channel assignment for wireless access networks is directed toward improved overall communication capability of the networks. A network is formed of wireless access points (APs) coupled via wired (and/or wireless) links and enabled to communicate with clients via radio channels of each of the APs. Local information is collected at each of the APs and processed to determine channel assignments according to a Neighbor Impact Metric (NIM) that accounts for one-hop and two-hop neighbors as well as neighbors not part of the network. Optionally, the NIM accounts for traffic load on the APs. The channel assignments are determined either on a centralized resource (such as a server or one of the APs) or via a distributed scheme across the APs. The local information includes how busy a channel is and local operating conditions such as error rate and interference levels.

Abstract: Channel assignment for wireless access networks is directed toward improved overall communication capability of the networks. A network is formed of wireless access points (APs) coupled via wired (and/or wireless) links and enabled to communicate with clients via radio channels of each of the APs. Local information is collected at each of the APs and processed to determine channel assignments according to a Neighbor Impact Metric (NIM) that accounts for one-hop and two-hop neighbors as well as neighbors not part of the network. Optionally, the NIM accounts for traffic load on the APs. The channel assignments are determined either on a centralized resource (such as a server or one of the APs) or via a distributed scheme across the APs. The local information includes how busy a channel is and local operating conditions such as error rate and interference levels.

Abstract: Examples of employee concierge are provided. In an example, an issue may be determined for an employee. The issue may be determined based on a query shared by the employee or upon occurrence of an unusual event. The unusual event may be indicative of a deviation in behaviour and routine of the employee. A session may be initiated and the issue may be parsed to determine a context. A bot may be selected from multiple bots for the issue where each bot includes information relating to a solution to address the issue. Data associated with the issue may be collected from a central database and other bots. The data may then be analyzed to determine a solution. The solution comprises a response to the query and a suggestion to mitigate the unusual event.

Abstract: Channel assignment for wireless access networks is directed toward improved overall communication capability of the networks. A network is formed of wireless access points (APs) coupled via wired (and/or wireless) links and enabled to communicate with clients via radio channels of each of the APs. Local information is collected at each of the APs and processed to determine channel assignments according to a Neighbor Impact Metric (NIM) that accounts for one-hop and two-hop neighbors as well as neighbors not part of the network. Optionally, the NIM accounts for traffic load on the APs. The channel assignments are determined either on a centralized resource (such as a server or one of the APs) or via a distributed scheme across the APs. The local information includes how busy a channel is and local operating conditions such as error rate and interference levels.

Abstract: Channel assignment for wireless access networks is directed toward improved overall communication capability of the networks. A network is formed of wireless access points (APs) coupled via wired (and/or wireless) links and enabled to communicate with clients via radio channels of each of the APs. Local information is collected at each of the APs and processed to determine channel assignments according to a Neighbor Impact Metric (NIM) that accounts for one-hop and two-hop neighbors as well as neighbors not part of the network. Optionally, the NIM accounts for traffic load on the APs. The channel assignments are determined either on a centralized resource (such as a server or one of the APs) or via a distributed scheme across the APs. The local information includes how busy a channel is and local operating conditions such as error rate and interference levels.

Abstract: A method includes separating a collection of devices configured for participation in a DR event into an On-to-Off DR device set (On-to-Off set) and an Off-to-On DR device set (Off-to-On set). The method includes portioning into transition groups devices of the On-to-Off set and/or devices of the Off-to-On set based at least partially on latency involved in command communication with one or more of the devices. The method includes scheduling state transitions of the transition groups such that an energy curtailment during the state transitions meets a curtailment margin of a total curtailment of the DR event. The method includes executing a micro DR event that includes the state transitions in which the devices in the transition groups are transitioned from a current state to an alternative state and the micro DR event curtails a portion of a total energy curtailment for the DR event.

Abstract: A method includes generating a duty cycle expression for heating, ventilation, air condition (HVAC) systems. The method includes estimating a baseline cycling percentage that maintains an indoor temperature at a particular setpoint based on the generated duty cycle expression and a curtailed cycling percentage that maintains the indoor temperature within a particular temperate interval of the particular setpoint. The method includes calculating a baseline-off-duration in which the HVAC system is in an off state during a normal operating cycle and a curtailed-on-duration implemented during a curtailment period. The method includes adjusting the curtailed-on-duration and the baseline-off-duration to satisfy a minimum-time-on and a minimum-time-off constraint of each HVAC system. The method includes identifying one or more HVAC systems to include in a micro DR event.

Abstract: A method includes separating a collection of devices configured for participation in a demand response (DR) event into an On-to-Off DR device set (On-to-Off set) and an Off-to-On DR device set (Off-to-On set). The method includes forming latency groups from devices of the Off-to-On set and the On-to-Off set based on a lower curtailment margin and an upper curtailment margin defined for a macro DR event. The method includes portioning one or more transition groups from the devices of the Off-to-On set and the On-to-Off set. The portioning is based on device curtailment capacities of the devices of the Off-to-On set and the On-to-Off set, a dynamic lower curtailment margin, and a dynamic upper curtailment margin. The method includes creating transition group pairs from the transition groups and executing a micro DR event such that an energy curtailment remains within the curtailment band.

Abstract: A method of forecasting a resource load for consumption at a site, e.g., an electrical load of a site. The method includes receiving historical load data and historical ambient condition data that are time series data pertaining to a site and generating additional data from the received data. The method includes building a best sub-model for each of multiple forecast intervals. The building includes clustering in parallel training portions of the historical load data and the additional data, training possible sub-models using the clustered training portions, verifying forecasted loads output from the possible sub-models against verification portions of the historical load data and the additional data, and determining a first subset of parameters for the best sub-model based upon accuracy of the forecasted loads. The method includes forecasting a resource load at the site for each of the forecast intervals using an ensemble of the best sub-models.

Abstract: A method includes generating a duty cycle expression for heating, ventilation, air condition (HVAC) systems. The method includes estimating a baseline cycling percentage that maintains an indoor temperature at a particular setpoint based on the generated duty cycle expression and a curtailed cycling percentage that maintains the indoor temperature within a particular temperate interval of the particular setpoint. The method includes calculating a baseline-off-duration in which the HVAC system is in an off state during a normal operating cycle and a curtailed-on-duration implemented during a curtailment period. The method includes adjusting the curtailed-on-duration and the baseline-off-duration to satisfy a minimum-time-on and a minimum-time-off constraint of each HVAC system. The method includes identifying one or more HVAC systems to include in a micro DR event.

Abstract: A method includes separating a collection of devices configured for participation in a demand response (DR) event into an On-to-Off DR device set (On-to-Off set) and an Off-to-On DR device set (Off-to-On set). The method includes forming latency groups from devices of the Off-to-On set and the On-to-Off set based on a lower curtailment margin and an upper curtailment margin defined for a macro DR event. The method includes portioning one or more transition groups from the devices of the Off-to-On set and the On-to-Off set. The portioning is based on device curtailment capacities of the devices of the Off-to-On set and the On-to-Off set, a dynamic lower curtailment margin, and a dynamic upper curtailment margin. The method includes creating transition group pairs from the transition groups and executing a micro DR event such that an energy curtailment remains within the curtailment band.

Abstract: A method includes separating a collection of devices configured for participation in a DR event into an On-to-Off DR device set (On-to-Off set) and an Off-to-On DR device set (Off-to-On set). The method includes portioning into transition groups devices of the On-to-Off set and/or devices of the Off-to-On set based at least partially on latency involved in command communication with one or more of the devices. The method includes scheduling state transitions of the transition groups such that an energy curtailment during the state transitions meets a curtailment margin of a total curtailment of the DR event. The method includes executing a micro DR event that includes the state transitions in which the devices in the transition groups are transitioned from a current state to an alternative state and the micro DR event curtails a portion of a total energy curtailment for the DR event.

Abstract: Channel assignment for wireless access networks is directed toward improved overall communication capability of the networks. A network is formed of wireless access points (APs) coupled via wired (and/or wireless) links and enabled to communicate with clients via radio channels of each of the APs. Local information is collected at each of the APs and processed to determine channel assignments according to a Neighbor Impact Metric (NIM) that accounts for one-hop and two-hop neighbors as well as neighbors not part of the network. Optionally, the NIM accounts for traffic load on the APs. The channel assignments are determined either on a centralized resource (such as a server or one of the APs) or via a distributed scheme across the APs. The local information includes how busy a channel is and local operating conditions such as error rate and interference levels.

Abstract: A method of forecasting a resource load for consumption at a site, e.g., an electrical load of a site. The method includes receiving historical load data and historical ambient condition data that are time series data pertaining to a site and generating additional data from the received data. The method includes building a best sub-model for each of multiple forecast intervals. The building includes clustering in parallel training portions of the historical load data and the additional data, training possible sub-models using the clustered training portions, verifying forecasted loads output from the possible sub-models against verification portions of the historical load data and the additional data, and determining a first subset of parameters for the best sub-model based upon accuracy of the forecasted loads. The method includes forecasting a resource load at the site for each of the forecast intervals using an ensemble of the best sub-models.

Abstract: Channel assignment for wireless access networks is directed toward improved overall communication capability of the networks. A network is formed of wireless access points (APs) coupled via wired (and/or wireless) links and enabled to communicate with clients via radio channels of each of the APs. Local information is collected at each of the APs and processed to determine channel assignments according to a Neighbor Impact Metric (NIM) that accounts for one-hop and two-hop neighbors as well as neighbors not part of the network. Optionally, the NIM accounts for traffic load on the APs. The channel assignments are determined either on a centralized resource (such as a server or one of the APs) or via a distributed scheme across the APs. The local information includes how busy a channel is and local operating conditions such as error rate and interference levels.

Abstract: Wireless mesh networks (or “meshes”) are enabled for arbitrary interconnection to each other and may provide varying levels of coverage and redundancy as desired. Interoperability between meshes having differing configurations, internal operations, or both, may be freely intermixed and inter-operated in unrestricted combination. Enhanced explicit inter-bridge control protocols operate using pre-existing control packets. Pre-existing broadcast packet floods are used to learn the best paths across interconnected meshes (termed a “multi-mesh”). Enhanced routing protocols operating within each mesh may optionally examine information limited to the respective mesh when forwarding traffic, thus enabling robust multi-mesh scaling with respect to memory and processing time required by the routing protocols. Communication scalability is improved by enabling frequency diversity across the multi-mesh by configuring meshes within interference range of each other for operation at a plurality of frequencies.