An apparatus comprises an electronic equipment chassis comprising a housing and at least one lid, the housing comprising a control panel with a first set of one or more status indicators. The apparatus also comprises at least one latch configured for securing the at least one lid to the housing, the at least one latch comprising a second set of one or more status indicators. The apparatus further comprises a processing device configured to determine status information for electronic equipment housed in the electronic equipment chassis, the status information characterizing whether at least one of opening and removing the at least one lid is safe to perform at a given time, and controlling, based at least in part on the determined status information, at least one of the first set of indicators and at least one of the second set of indicators.

Aspects of the disclosure relate to computing platforms that utilize improved techniques for dynamic event verification. A computing platform may receive first source data comprising driving data associated with a vehicle over a time period. Based on the first source data, the computing device may determine that the vehicle experienced an event, resulting in an event output. In response to determining the event output, the computing device may generate a request for second source data associated with the vehicle over the time period. The computing device may receive, from a sensor device, the second source data. Based on a comparison of the first source data to the second source data, the computing platform may determine an event comparison output. The computing platform may determine that the event comparison output exceeds a predetermined comparison threshold, and may send an indication of an event in response.

A power system monitoring control system and method that retains a control table and, when a failure occurs, controls a target according to a type of the failure according to the control table in which the method includes: estimating a contingency point which is an occurrence point of the failure that is assumed in the power system based on prescribed disaster information; estimating an assumed disaster content which is a content of a disaster at each contingency point based on the disaster information and an estimation result of the contingency point; changing contingency data based on an estimation result of the assumed disaster content at each contingency point, contingency data including an occurrence site and an aspect of each of the failures that are assumed to occur, and a contingency change rule including a contingency data change rule; and updating the control table based on changed contingency data.

A system optimal control technique with accuracy guarantee that enables high-speed calculations is provided. One aspect of the present invention is related to a system optimal control device including a graph converting unit configured to convert, based on an upper bound of an probability of arrival from an initial state to a final state of a stochastic game representing system information, the stochastic game into a flow analysis graph, a path selecting unit configured to select a path having a maximum width among paths from each state node to a final state node in the converted flow analysis graph, a width of each of the paths being defined as a minimum weight of edges forming the path, and a convergence determining unit configured to determine convergence of the upper bound and a lower bound of the probability of arrival of the stochastic game based on information about the selected path.

A method for diagnosing a vehicle electrical system of a vehicle including a plurality of intercommunicating arithmetic logic units. A diagnostic application is executed on one arithmetic logic unit of the plurality of arithmetic logic units. The diagnostic application receives a diagnostic inquiry from an external diagnostic unit. The diagnostic inquiry is analyzed by the diagnostic application. Based on the content of the diagnostic inquiry, the diagnostic application sends data to at least one arithmetic logic unit and/or sends a diagnostic response to the external diagnostic unit.

A wireless and cellular vibration monitoring device (2) comprising a connection structure (6) suitable for attaching the monitoring device (2) to equipment to be monitored is disclosed. The monitoring device (2) comprises a temperature sensor (8) and a vibration sensor (10) configured to remotely monitor vibration and temperature transferred to the monitoring device (2) via the connection structure (6). The device comprises an integrated satellite-based radio-navigation system for location detection. The monitoring device (2) comprises a metal base (4) comprising a body portion (56) comprising a threaded portion (6) constituting the connection structure (6). The threaded portion (6) comprises male threads and protrudes from the body portion (56) of the base (4). The temperature sensor (8) is thermally connected to the body portion (56) of the base (4).

Implementations of systems for monitoring industrial equipment may include: a processor coupled with one or more sensors. The systems may include one or more input/outputs coupled with the sensors. The one or more input/outputs may be configured to couple with one or more peripheral devices. The processor may be configured to electrically couple with a remote server. The remote server may be configured to process data received from the one or more sensors and instruct, through the processor, the one or more peripheral devices to make an adjustment.

A hybrid data collection and analysis infrastructure combines edge-level and cloud-level computing to perform high-level monitoring and control of industrial systems and processes. Edge devices located on-premise at one or more plant facilities can collect data from multiple industrial devices on the plant floor and perform local edge-level analytics on the collected data. In addition, the edge devices maintain a communication channel to a cloud platform executing cloud-level data collection and analytic services. As necessary, the edge devices can pass selected sets of data to the cloud platform, where the cloud-level analytic services perform higher level analytics on the industrial data. The hybrid architecture operates in a bi-directional manner, allowing the cloud-level and edge-level analytics to send control instructions to industrial devices based on results of the edge-level and cloud-level analytics.

A method of remotely configuring one or more building system components at a building site uses a cloud-based server remote from the building site. The cloud-based server receives information from an intelligent gateway at the building site that identifies each of one or more building system components at the building site. The cloud-based server is used to create a site configuration that is based at least in part on the identified information for each of the one or more building system components. The site configuration is then downloaded from the cloud-based server to the intelligent gateway such that the intelligent gateway is able to pass configuration information to one or more local controllers that control operation of the one or more building system components.

A method of remotely configuring one or more building system components at a building site uses a cloud-based server remote from the building site. The cloud-based server receives information from an intelligent gateway at the building site that identifies each of one or more building system components at the building site. The cloud-based server is used to create a site configuration that is based at least in part on the identified information for each of the one or more building system components. The site configuration is then downloaded from the cloud-based server to the intelligent gateway such that the intelligent gateway is able to pass configuration information to one or more local controllers that control operation of the one or more building system components.