Power Monitoring and Passenger Classification on Logistics Elevator

Isa Hafidz, Institut Teknologi Telkom Surabaya, Indonesia
Aldhitiansyah Putra, Institut Teknologi Telkom Surabaya, Indonesia
Billy Montolalu, Institut Teknologi Telkom Surabaya, Indonesia
Dimas Adiputra, Institut Teknologi Telkom Surabaya, Indonesia
Rifky Dwi Putranto, Institut Teknologi Telkom Surabaya, Indonesia
Rafly Daffaldi, Institut Teknologi Telkom Surabaya, Indonesia
Dinda Karisma Ulfa, Institut Teknologi Telkom Surabaya, Indonesia


The elevator has an important role in assisting transportation and logistics activities in a building. However, if the elevator is not used wisely, then the power consumption will be inefficient. A policy of elevator usage is necessary to ensure the effectiveness of elevator power consumption. Therefore, in this study, elevator power consumption monitoring is proposed. The power consumption behavior can be learned so a suitable policy can be made accordingly. Two elevators in Telkom Campus Surabaya are monitored to understand the daily electrical energy usage. Internet of Things (IoT) based real-time power monitoring system is used to monitor the electrical energy usage of the elevator. A raspberry pi is used to collect the data of electrical usage via a current and power sensor. The data is sent to the cloud, which later is displayed through a dashboard website. The result shows that the elevator usage on weekdays and weekends is different. The peak power on weekdays is obtained from 15.00 to 16.00, meanwhile, on weekends, the peak occurs from 9:00 to 10:00. On weekdays, the total power consumed by the elevator is 51.74kW, while on weekends, it is 11.94kW. Restrictions on the use of lifts are applied to periods when the lift has few passengers and has a short distance. From the results obtained, the total power consumed can decrease by an average of 37%. It is expected that the suggested policies can reduce elevator power consumption and the monthly cost of electrical energy.


Internet of Things, Logistics Lift, Real-Time Power Monitoring

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DOI: https://doi.org/10.21831/elinvo.v6i2.43689


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