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

Kumaran, K. Manikanda; Chinnadurai, M.

doi:10.1007/s12652-020-01758-w

Cited by 9 publications

(1 citation statement)

References 19 publications

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“…In recent years, emerging technologies in the fields of cloud computing, robotic computing algorithms, wireless sensor networks and communication help the advance of cloud robotics in smart cities. Kumaran et al [45] developed a cloud robotic system using hybrid artificial intelligent algorithms. The proposed system was shown to perform the crowd control in smart cities satisfactorily.…”

Section: Supervised Machine Learningmentioning

confidence: 99%

Advances in Machine Learning for Sensing and Condition Monitoring

Ao¹,

Gelman²,

Karimi³

et al. 2022

Applied Sciences

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In order to overcome the complexities encountered in sensing devices with data collection, transmission, storage and analysis toward condition monitoring, estimation and control system purposes, machine learning algorithms have gained popularity to analyze and interpret big sensory data in modern industry. This paper put forward a comprehensive survey on the advances in the technology of machine learning algorithms and their most recent applications in the sensing and condition monitoring fields. Current case studies of developing tailor-made data mining and deep learning algorithms from practical aspects are carefully selected and discussed. The characteristics and contributions of these algorithms to the sensing and monitoring fields are elaborated.

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Section: Supervised Machine Learningmentioning

confidence: 99%