Cloud-based robotic system for crowd control in smart cities using hybrid intelligent generic algorithm

• Published in: Journal of ambient intelligence and humanized computing Vol. 11; no. 12; pp. 6293 - 6306
• Main Authors: Manikanda Kumaran, K., Chinnadurai, M.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2020; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Cities; Cloud computing; Communication; Computation offloading; Computational Intelligence; Control systems; Crowd control; Crowdsourcing; Data collection; Energy consumption; Energy storage; Engineering; Genetic algorithms; Internet of Things; Internet resources; Neural networks; Original Research; Quality of service; Remote computing; Robotics; Robotics and Automation; Robots; Sensors; Smart cities; Ubiquitous computing; User Interfaces and Human Computer Interaction; Wireless communications; Wireless sensor networks; Cloud computing; Storage; Energy; Smart city; Robotics
• ISSN: 1868-5137; 1868-5145
• DOI: 10.1007/s12652-020-01758-w

In recent years, cloud robotics in smart cities emerged with the technology of cloud computing and robotic enabled services such as ubiquitous computing based on internet resources, wireless sensor network, communication technologies, and large scale storage system for smart systems. The Internet of things is a complement to generate an enhanced system where robots offload the pervasive cloud to ensure the quality of the service from the data-intensive computation. In general the robots offloading is a crucial issue because of their skill learning, decision-making capabilities, a unique feature of mobility, and data collection. In this paper, a cloud-based robotic system for the crowd control system in smart cities using the hybrid intelligent generic algorithm has been proposed for smart crowd management. The cloud enhanced robots are employed to execute the essential task while taking into consideration of different complexity in a smart city. Furthermore, the integrated framework has been introduced to handling the task offloading and task completion through the robotics movement with minimum time and energy. The experimental results shows that the proposed system achieves powerful computation, storage, energy-efficient and reduce the cost with the help of cloud computing for smart city management.