Abstract: Data associated with a flight, including a flight plan, a vehicle, and/or a pilot is processed via a risk assessment platform to obtain one of more numerical risk values, for example a ground risk value and an air risk value. Based on the processed data, a matrix of risk assessment decisions is generated containing risk related information (such as risk remediation information). Accordingly, based on a consistent set of risk relation information, a predictable and repeatable flight decision (such as a decision whether to fly, or an adjustment to a flight route) can be made. In some instances, the data to be processed is quantitative data collected from one or more third party systems, such as sensor data or geospatial data. The risk assessment platform includes toolkits or services to be used in the processing and transformation of this data to reach a risk assessment decision.

Abstract: A platform for unmanned traffic management (UTM) may include a compute system and infrastructure that standardizes and controls aviation data transmitted between service providers, where each service is abstracted from the platform through a service wrapper that enforces the preset data standards. The service wrappers enforce restrictions on the performance and configuration of data from the service provider. The service wrappers are customized to respective services (such as tracking, terrain, or weather), but provide a standard point of interface, security, and trust between the platform and any services directed to provide a similar function. Upon the request of a user or service providers to obtain aviation data, the UTM platform selects a service providing that aviation data, and provides connection data to the user while protecting the security and integrity of the data.

Abstract: A platform for unmanned traffic management (UTM) may include a compute system and infrastructure that standardizes and controls aviation data transmitted between service providers, where each service is abstracted from the platform through a service wrapper that enforces the preset data standards. The service wrappers enforce restrictions on the performance and configuration of data from the service provider. The service wrappers are customized to respective services (such as tracking, terrain, or weather), but provide a standard point of interface, security, and trust between the platform and any services directed to provide a similar function. Upon the request of a user or service providers to obtain aviation data, the UTM platform selects a service providing that aviation data, and provides connection data to the user while protecting the security and integrity of the data.

Abstract: Data associated with a flight, including a flight plan, a vehicle, and/or a pilot is processed via a risk assessment platform to obtain one of more numerical risk values, for example a ground risk value and an air risk value. Based on the processed data, a matrix of risk assessment decisions is generated containing risk related information (such as risk remediation information). Accordingly, based on a consistent set of risk relation information, a predictable and repeatable flight decision (such as a decision whether to fly, or an adjustment to a flight route) can be made. In some instances, the data to be processed is quantitative data collected from one or more third party systems, such as sensor data or geospatial data. The risk assessment platform includes toolkits or services to be used in the processing and transformation of this data to reach a risk assessment decision.

Abstract: A system (and a method) are disclosed for reliably disseminating a state of a node in a large network consisting of nodes with constrained resources. The system comprises a process embodied by a state machine comprised of an advertise state, a request state, and a share state. The system processes input events, mutates its internal state, and outputs side effects. The outputs from one node in the network may become inputs events to one or more other nodes in the network. Viral dissemination is an emergent behavior across the nodes in a network that all independently and continuously perform these input processings, state mutations, and output side effects.

Abstract: A system and a method are disclosed for determining the electrical values of assets in a facility. The system receives a power tree configuration for a facility. The system generates a mathematical model of the power tree configuration. The mathematical model includes nodes that represent assets of the power tree configuration. The system receives electrical values for an asset and associates the values with a node. The system receives electrical values for another asset and associates the values with another node. The system then determines the electrical values for a different node based on the electrical values associated with the first two nodes.

Abstract: A pervasive computing system comprises a set of client devices and a network of small computing units, referred to as nodes. The client devices and nodes run programs that communicate with each other to solve a given problem, but the client devices and the nodes use different software execution environments and protocols. A host server acts as an intermediary between the client devices and the nodes, bridging the gap between the different software execution environments and protocols of the client devices and the nodes.

Abstract: A system (and a method) are disclosed for reliably disseminating a state of a node in a large network consisting of nodes with constrained resources. The system comprises a process embodied by a state machine comprised of an advertise state, a request state, and a share state. The system processes input events, mutates its internal state, and outputs side effects. The outputs from one node in the network may become inputs events to one or more other nodes in the network. Viral dissemination is an emergent behavior across the nodes in a network that all independently and continuously perform these input processings, state mutations, and output side effects.

Abstract: A pervasive computing system comprises a set of client devices and a network of small computing units, referred to as nodes. The client devices and nodes run programs that communicate with each other to solve a given problem, but the client devices and the nodes use different software execution environments and protocols. A host server acts as an intermediary between the client devices and the nodes, bridging the gap between the different software execution environments and protocols of the client devices and the nodes.

Abstract: A mobile computer establishes a wireless communication session with a wireless access point of a computer network. The location of each wireless access point is known and obtainable either from a database on the network or from the access points themselves. The strengths of wireless signals passing between the mobile computer and multiple wireless access points of the network, including the access point with which the mobile computer has established the session are measured at multiple time intervals. The measurements may be taken at the mobile computer itself or at the wireless access points. The measured strength values are then weighted according to such factors as whether the mobile computer has already established a communication session with the access point from which the sample was taken, and how old the sample is. For each location, the weighted strength values obtained for access points in that location are summed.

Abstract: A mobile computer establishes a wireless communication session with a wireless access point of a computer network. The location of each wireless access point is known and obtainable either from a database on the network or from the access points themselves. The strengths of wireless signals passing between the mobile computer and multiple wireless access points of the network, including the access point with which the mobile computer has established the session are measured at multiple time intervals. The measurements may be taken at the mobile computer itself or at the wireless access points. The measured strength values are then weighted according to such factors as whether the mobile computer has already established a communication session with the access point from which the sample was taken, and how old the sample is. For each location, the weighted strength values obtained for access points in that location are summed.