A safety module having a plurality of microcontrollers receives an analog input and determines a value of the analog input. The microcontrollers each determine a respective ternary state of the device by identifying, from three candidate ranges of values, a range of values in which the value falls, wherein at least two of the plurality of microcontrollers uses different candidate ranges of values, determining, based on the identified range, a ternary state corresponding to the range, and assigning the determined ternary state as the respective ternary state. The safety module determines whether the ternary states from the two microcontrollers map to a fault state, and, where they do, cause a command a command to be output to the device to enter a safe state.

Embodiments of the present disclosure provide a system for continuous and real-time management and monitoring of robotic process automation bots. In particular, the architecture of the system may comprise a centralized hub which provides various features and functions for bot management and monitoring, such as real-time health status updates, granular logging and notification functions, failure detection and reporting for debugging, bot inventory systems, or the like. Through the use of the components and/or features as described herein, the system may provide an efficient way to manage and monitor robotic process automation bots within a computing environment.

An environment control system includes: a control unit; a serial communication bus including a main communication line having a first end connected to the control unit and first to Nth (N: an integer of 2 or more) sub communication lines branched off from a second end of the main communication line; devices connected to the first to Nth sub communication lines; and switching units disposed on all the first to Nth sub communication lines and configured to connect and disconnect the devices to and from the control unit. Each of the first to Nth sub communication lines is connected to one or more of the devices.

A modular energy system for use in a surgical environment includes a plurality of functional modules including at least an initial module, a functional module, and a terminal module. Each of the plurality of modules has a module control circuit, and a local data bus. An internal data bus is composed of a serial array of the local data busses of the modules. The local data bus may includes a communication switch, a first switch data path between the communication switch and the module control circuit, a second switch data path in communication with the communication switch, and a third switch data path in communication with the communication switch. The third switch data path of a module N is in communication with a second switch data path of a module N+1. The system further includes a termination unit in communication with the third data path of the terminal module.

In an ultrasound system and a control method of the ultrasound system, in a case where occurrence of an error is detected, first operation information as at least one piece of operation information with the highest priority among a plurality of pieces of operation information corresponding to a type of the error that has occurred is displayed, and in a case where the number of times of the operation corresponding to the first operation information, which is performed by the user, has reached a predetermined number within a predetermined period after the first operation information is displayed, second operation information as at least one piece of operation information with the highest priority next to the first operation information is displayed.

A method of verifying execution sequence integrity of an execution flow includes receiving, by a local monitor of an automated device monitoring system from one or more sensors of an automated device, a unique identifier for each function in a subset of an execution flow for which the local monitor is responsible for monitoring. The method includes combining the received unique identifiers to generate a combination value, applying a hashing algorithm to the combination value to generate a temporary hash value, retrieving, from a data store, a true hash value, determining whether the temporary hash value matches the true hash value, and in response to the temporary hash value not matching the true hash value, generating a fault notification. The true hash value represents a result of applying the hashing algorithm to a combination of actual unique identifiers associated with each function in the subset.

A system and method for detecting and fixing robotic process automation failures, including collecting tasks from at least one client computerized device, processing the tasks via robotic process automation, collecting tasks that failed to complete per task type, recording successful execution steps per each of the failed tasks, evaluating the recorded successful execution steps with respect to the failed task types, and providing selected execution steps that best fix the failed tasks, thereby fixing the robotic process automation failures.

Anomaly detection and self-healing for robotic process automation (RPA) via artificial intelligence (AI)/machine learning (ML) is disclosed. RPA robots that utilize AI/ML models and computer vision (CV) may interpret and/or interact with most encountered graphical elements via normal learned interactions. However, such RPA robots may occasionally encounter new, unhandled anomalies where graphical elements cannot be identified and/or normal interactions will not work. Such anomalies may be processed by an anomaly handler. The RPA robots may have self-healing functionality that seeks to automatically find information that addresses anomalies.

A monitoring apparatus includes: an input unit that accepts equipment identifying information for identifying monitoring object equipment and an analysis purpose; and an output unit that, when analysis item data corresponding to the analysis purpose among operation data indicating an operating status of the identified monitoring object equipment is a value within a specified range on the basis of the equipment identifying information and the analysis purpose which have been input, outputs a tendency of the analysis item data compared with predetermined comparison item data. According to the above-described configuration, the status of the monitoring object equipment can be diagnosed and visualized for the sake of the condition based maintenance to perform maintenance in accordance with the status of each equipment.

Out-of-bounds recovery circuits configured to detect an out-of-bounds violation in an electronic device, and cause the electronic device to transition to a predetermined safe state when an out-of-bounds violation is detected. The out-of-bounds recovery circuits include detection logic configured to detect that an out-of-bounds violation has occurred when a processing element of the electronic device has fetched an instruction from an unallowable memory address range for the current operating state of the electronic device; and transition logic configured to cause the electronic device to transition to a predetermined safe state when an out-of-bounds violation has been detected by the detection logic.