Wireless Communication for Robotic Process Automation Using Machine Learning Technique

Abstract

Machine intelligence is what has been generated by programming computers with certain aspects of human intellect, like training, solving problems, and priority setting. A machine can solve a number of complicated issues using these capabilities. In major industries, such as customer support and manufacturing, machine intelligence is now being employed. The growth and quick development of digital technology and artificial intelligence (AI) technologies are becoming more and more difficult. At now, sophisticated manufacturing, the world of invention, and broad acceptance are undergoing a fast transition. Robotics is much more vital as it may now be related to the human brain by the connection between machine and brain, as AI develops. The world’s economy faces substantial difficulties by increasing productivity in the manufacturing industry. This study examines the present progress of robotic communication styles of artificial intelligence (AI). In many specific applications, communication between members of a robotic group or even people becomes vital. The paper solves the problem of implementation of an independent industry mobile robot in all fields in the major business, live interactive, planning, mobile robot technologies, and intending. In order to identify the best solution to this issue, a mixed integer robotic model has been developed.

Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things

“…[ [9][10][11][12][13][14][15][16] Cloud computing technologies assist IoRT systems and virtual machines in terms of connectivity and scalability. IoRT devices leverage connected sensors, cloud computing and wireless technologies, and machine learning algorithms for real-time data collection as regards device control and diagnostics.…”

“…IoRT leverages computer vision and data processing algorithms, image acquisition devices, and distributed intelligence tools [9][10][11][12] for object recognition, manipulation, and control. Machine intelligence and mobile robot technologies optimize image recognition accuracy and thus cloud-based production processes and tasks can be performed effectively.…”

“…Cognitive artificial intelligence, wireless sensor and actuator networks, and remote big data management tools [5][6][7][8] and recognition across remote and synthetic simulation environments. Autonomous cognitive systems enable process monitoring and diagnosis of production line management in intelligent connectivity infrastructures [9][10][11][12], considerably improving productivity. Cloud computing technologies, image recognition and ambient intelligence tools, and context awareness algorithms [13][14][15][16] can configure trajectory paths and detect events by continuous process monitoring and data collection.…”