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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63880
Volume:
10 |
5 |
May 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Department of Computer Science and Engineering
Malnad College of Engineering
Department of Computer Science and Engineering
Malnad College of Engineering
Department of Computer Science and Engineering
Malnad College of Engineering
Department of Computer Science and Engineering
Malnad College of Engineering
Department of Computer Science and Engineering
Malnad College of Engineering
Modern elevator systems face challenges such as long waiting time, unnecessary movement, and high energy consumption. This project proposes EcoLift, an intelligent el- evator dispatching system that uses Genetic Algorithm (GA)- based optimization and sensor-based passenger verification to improve elevator efficiency. The system aims to reduce passen- ger waiting time, optimize journey time, and minimize energy consumption. The proposed solution combines software-based optimization with low-cost hardware components for practical implementation.
KEYWORDS
EcoLift is an intelligent elevator dispatching system de- veloped to improve energy efficiency and passenger comfort using Genetic Algorithm-based optimization and sensor-based passenger verification. The project provides a low-cost and practical solution suitable for smart building applications. Future enhancements may include: • Machine Learning-based traffic prediction • Multi-elevator coordination • IoT cloud monitoring • Mobile application integration
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Publication Date
5/24/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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