Control systems and methods for controlling an engine. The control system includes a computation module and an input/output (I/O) module attached to the engine. The computation module is located in an area of the engine, or off-engine, that provides a more benign environment than the environment that the I/O module is subject to during operation of the engine. The I/O module includes a first processor and a first network interface device. The computation module includes a second processor with higher processing power than the first processor, and a second network interface device. The control system also includes a sensor configured to provide sensor readings to the first processor. The first processor transmits data based on the sensor readings to the second processor. The control system also includes an actuator operably coupled to the I/O module and that is controlled by the first processor based on commands from the second processor.

This disclosure relates generally to a system and method to identify at least one conflict and for controlling both static and dynamic variables in one or more operations of at least one subsystem of a plurality of building automation sub-systems. It includes a supervisory control layer that orchestrates multiple underlying sub-systems like heating, ventilation, and air-conditioning (HVAC) sub-systems and at least one access control sub-system. A test case generation framework is used to verify static and dynamic variables of operations of the sub-systems. It identifies conflicts in the static and dynamic variables. Therefore, the system provides controls to the sub-systems using the identified and adjusted conflict of static and dynamic variables on operations.

This disclosure relates generally to a system and method to identify at least one conflict and for controlling both static and dynamic variables in one or more operations of at least one subsystem of a plurality of building automation sub-systems. It includes a supervisory control layer that orchestrates multiple underlying sub-systems like heating, ventilation, and air-conditioning (HVAC) sub-systems and at least one access control sub-system. A test case generation framework is used to verify static and dynamic variables of operations of the sub-systems. It identifies conflicts in the static and dynamic variables. Therefore, the system provides controls to the sub-systems using the identified and adjusted conflict of static and dynamic variables on operations.

A foot presence sensor system for an active article of footwear can include a sensor housing configured to be disposed at or in an insole of the article, and a controller circuit, disposed within the sensor housing, configured to trigger one or more automated functions of the footwear based on a foot presence indication. In an example, the sensor system includes a capacitive sensor, and the sensor is configured to sense changes in a foot proximity to the sensor in footwear. Information about the sensed proximity can be used to determine a foot velocity characteristic, which in turn can be used to update an automated footwear function, such as an automatic lacing function, or can be used to determine a step count, foot strike force, a rate of travel, or other information about a foot, about an activity, or about the footwear.

A foot presence sensor system for an active article of footwear can include a sensor housing configured to be disposed at or in an insole of the article, and a controller circuit, disposed within the sensor housing, configured to trigger one or more automated functions of the footwear based on a foot presence indication. In an example, the sensor system includes a capacitive sensor, and the sensor is configured to sense changes in a foot proximity to the sensor in footwear. Information about the sensed proximity can be used to determine a foot velocity characteristic, which in turn can be used to update an automated footwear function, such as an automatic lacing function, or can be used to determine a step count, foot strike force, a rate of travel, or other information about a foot, about an activity, or about the footwear.

A hyperconverged industrial process control architecture is disclosed for controlling an industrial process within a physical process environment using a software-defined distributed control system (DCS) environment. The software-defined DCS environment may be implemented by virtualizing the hardware components of a DCS architecture on a server group to enable both software-defined process controllers and back-end DCS applications to run within the server group. This software-defined DCS network architecture reduces the hardware requirements of the process control system and reduces configuration complexity by implementing control components and higher-level components within a common environment within the server group.

A hyperconverged industrial process control architecture is disclosed for controlling an industrial process within a physical process environment using a software-defined distributed control system (DCS) environment. The software-defined DCS environment may be implemented by virtualizing the hardware components of a DCS architecture on a server group to enable both software-defined process controllers and back-end DCS applications to run within the server group. This software-defined DCS network architecture reduces the hardware requirements of the process control system and reduces configuration complexity by implementing control components and higher-level components within a common environment within the server group.

A system for monitoring industrial processes using an evolving set of iso-functional smart nodes, for a distributed mesh network, each node comprising a Linux or Linux-compatible computer hardware architecture and a software stack. Each node receives an execute statement from a program hosted by another node in the mesh and, by execution on the computer hardware architecture of each node, said program is responsible for: two-way communication with other nodes or a central platform (Big Data Management), control of sensors or programmable automatons for monitoring a process or actuators, acquisition and logging of data from the latter, formatting of data and decentralized calculations, said central platform allowing the acquisition, management and storing of a data lake and comprising means for synchronous or asynchronous communication with the distributed mesh network.

A system for monitoring industrial processes using an evolving set of iso-functional smart nodes, for a distributed mesh network, each node comprising a Linux or Linux-compatible computer hardware architecture and a software stack. Each node receives an execute statement from a program hosted by another node in the mesh and, by execution on the computer hardware architecture of each node, said program is responsible for: two-way communication with other nodes or a central platform (Big Data Management), control of sensors or programmable automatons for monitoring a process or actuators, acquisition and logging of data from the latter, formatting of data and decentralized calculations, said central platform allowing the acquisition, management and storing of a data lake and comprising means for synchronous or asynchronous communication with the distributed mesh network.

A safety controller module for providing safety control comprises a non-volatile memory configured for storing a safety control program and one or more processing units configured to execute safety control functions associated with the safety control program to provide independent safety control. The safety controller module further comprises a connector configured to communicatively couple the safety controller module with a non-safety controller. The safety controller module is configured to communicate an input and/or an output signal of the safety controller module via the connector to the non-safety controller.