Title: Dynamic optimisation of elevators using biometric identification systems
Authors: Eugeniu Cozac; Dmitry Gura; Alexey Bityutskiy; Sergei Kiselev; Anastasia Repeva
Addresses: Technical University of Moldova, Chisinau 2004, Moldova; GAN, c.o. Memery Crystal Llp, London EC4A 2DY, UK ' Kuban State Technological University, Krasnodar 350072, Russian Federation; Kuban State Agrarian University, Krasnodar 350004, Russian Federation ' Invent Technology Laboratory, Almaty 050052, Kazakhstan ' Russian Technological University, Moscow 115583, Russian Federation ' Moscow State University of Civil Engineering (National Research University), Moscow 117403, Russian Federation
Abstract: The research focused on developing a real-time monitoring algorithm for elevators in residential towers. The study employed methods, models, and software tools to build intelligent real-time decision-making systems. A model for the elevator setting process was implemented through a Markov decision-making process. The theory of mass service was applied to describe the model of elevator operations. Passenger waiting time patterns at some levels of the towers have been established. A mathematical model for managing passenger flows through the elevators of a high-rise building in real-time using facial recognition identification technology has been developed. In test mode, a face-recognition elevator control system has been installed in four elevators. The scientific value of the work resides in the multi-purpose nature of the mathematical optimisation model, its simplicity and accuracy. The proposed model allows optimising numerous elevator systems with a constantly evolving control algorithm tailored to the customer's preferences.
Keywords: lifting facility; Markov process; mathematical model; traffic fluctuations; biometric data; SDG.
International Journal of Simulation and Process Modelling, 2022 Vol.18 No.1, pp.1 - 10
Received: 06 Aug 2021
Accepted: 13 Oct 2021
Published online: 22 Jun 2022 *