In this paper we introduce the core results of the project on visualisation and analysis of data collected from the vertical transport facilities. The aim of the project was to provide better user experience as well as to help building maintenance staff to increase productivity of their work. We elaborated a web-based system for vertical transportation, to cover the needs of (1) staff working on building maintenance, (2) people who are regularly using the facilities in the corresponding buildings.
 The round trip time is the basis for designing elevator systems. There are a number of different methods for calculating the round trip time, whether analytical or numerical. As the building and the conditions of the traffic become more complicated, analytical methods become intractable. Numerical methods offer an attractive alternative for calculating the round trip time. Monte Carlo simulation has been used to find the value of the round trip time. The use of the Markov chain Monte Carlo method is a viable alternative. This paper derives the formulae necessary to build the transition probability matrix for the elevator during a round trip under incoming traffic conditions and multiple entrances. A numerical example is then solved by finding the round trip time using the Markov chain Monte Carlo method and then cross verified by the use of Monte Carlo simulation and the analytical equation based method. Excellent agreement has been found between the three methods, with differences smaller than 0.01 . Efficient elevator group control is an important issue for vertical transportation in high-rise buildings. From the engineering design perspective, regulation of average waiting time and journey time while considering energy consumption is an optimization problem. Alternatively to the conventional algorithms for scheduling and dispatching cars to hall calls, intelligent systems based methods have drawn much attention in the last years. This study aims to improve the elevator group control system's performance by applying genetic algorithm based optimization algorithms considering two systems. Firstly, average passenger waiting time is optimized in the conventional elevator systems in which a hall call is submitted by indicating the travel direction. Secondly, a recent development in elevator industry is considered and it is assumed that instead of direction indicators there are destination button panels at floors that allow passengers to specify their destinations. In this case optimization of average waiting time, journey time and car trip time is investigated. Two proposed algorithms have been applied considering preload conditions in a building with 20 floors and 4 cars. The simulation results have been compared with a previous study and conventional duplex algorithm.