A Field-Oriented Test-Simulation of Embedded Lift Information System for High Rise Buildings

higherThe higher the contrsuction site, the longer the vertical length of movements of construction lifts carrying workers or material. At skyscraper high-rise construction, an experienced supervisor manages the lift operation for vertical moving of material. Therefore, there are needs for computational tools to assist managers on site to make a decision how to control and monitor numerous lifts by integrated network systems. Vertical transportation management of materials and labors is closely related to productivity of high rise construction, and the importance of vertical transportation grows as the buildings become higher. The objective of this study is to verify the efficiency and suitability of embedded lift information systems (Intelligent monitoring & control using distributed sensor swarms) through a test-bed for a high-rise building construction site in Korea. Embedded Lift Information System (ELIS) consists of 6 types of sensor devices selected by site-oriented demand survey. The sensor modules consist of a Double Senor type Encoder, Limit Switch, Separating type Current Transformer, Proximity Sensor, Load Cell. The lift sends real-time data of speed, direction and present load to the control server, at a rate of 5Hz. Based on the acquired data, the optimum lift is selected. The algorithm used in ELIS predicts movement of lifts based on collected sensor data since lifting cycle-estimation becomes a vital part for an arithmetic computation based on vertical zoning algorithm which levels operation ratio and reduces queuing times. The sensor data provides a basis for the algorithm to select optimum construction hoist when the next lift call is given. To select the optimum lift, a primary consideration is the present load capacity; if the capacity is already full, the hoist is instantly excluded. The lift direction and the direction to the destination floor are considered in terms of minimizing the overall required movement. Third, travel time is calculated for the remaining hoists to select the optimum construction hoist that minimizes queuing times of materials and labor. The result of lift movement patterns were compared with non-ELIS equipped systems, and was found that a decision making algorithm can be connected with real-site construction plan.