US 12,085,901 B2
Bot management framework for robotic process automation systems
Ramkumar Kothandaraman, Bangalore (IN); Koduvayur Vaidyanathan Ramesh, Bangalore (IN); Suman Sundaravaradan, Chennai (IN); Sunil Balugari, Bangalore (IN); and Puneet Kalra, Pune (IN)
Assigned to ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Feb. 1, 2018, as Appl. No. 15/886,341.
Claims priority of application No. 201711041688 (IN), filed on Nov. 21, 2017.
Prior Publication US 2019/0155225 A1, May 23, 2019
Int. Cl. G05B 13/02 (2006.01); G05B 13/04 (2006.01); G05B 19/042 (2006.01); G06F 11/34 (2006.01); G06N 3/006 (2023.01); G06N 20/00 (2019.01); H04L 41/16 (2022.01); H04L 41/5019 (2022.01)
CPC G05B 13/028 (2013.01) [G05B 13/041 (2013.01); G05B 19/042 (2013.01); G06F 11/3495 (2013.01); G06N 3/006 (2013.01); G06N 20/00 (2019.01); H04L 41/16 (2013.01); H04L 41/5019 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method executed by one or more processors, the method comprising:
receiving, by an adapter and from a robotic process automation (RPA) system connected to the adapter, information regarding a software bot deployed within the RPA system to perform an assigned task, the information including incident data from an anomaly in the RPA system occurring while the software bot performed the assigned task, the adapter being one of a plurality of adapters and specific to the RPA system, and being deployed to service the RPA system, the software bot being associated with a particular RPA tool, and the anomaly comprising one of an alert and an error raised by the software bot;
validating the incident data according to data validation rules assigned to the RPA system based on a delta data load validation of metadata included in the incident data;
determining, by the adapter, categorization and assignment of the anomaly based on a semantic analysis of the incident data to understand key word language and emotion of the incident data for insight discovery;
mapping, by the adapter, the received incident data according to a common data model based on the categorization and the assignment of the anomaly, the common data model being stored in a common data model repository connected to the adapter and providing a uniform schema by which to process incident data for multiple different RPA tools including the particular RPA tool;
determining, by the adapter, a resolution for the anomaly based on an analysis through a trained artificial intelligence (AI) model of the mapped incident data; and
executing the determined resolution by proactively bringing the software bot to a designated performance level.