A Performance Evaluation Study of a smart lawn Mower for Improving Cutting Efficiency and Optimising Operation Time
Keywords:
Smart lawn mower, operational efficiency, automation, time saving, landscape maintenanceAbstract
Introduction/Main Objectives: This study aimed to assess the performance of a smart lawn mower designed to boost the efficiency of operational activities and optimize the landscape maintenance period in an educational campus environment.
Background Problems: Manual grass-cutting activities, which are still common in educational institutions in Malaysia, are time-consuming, require significant manpower, and result in an inconsistent cutting style.
Novelty: This study presents an automated, smart lawn mower that uses an electric driving system with central control to increase operational productivity and decrease reliance on human labor.
Research Methods: The study uses a quantitative experimental comparison approach between the smart lawn mower and the manual method on a 2,000 square feet test site. The evaluated parameters are operational time (minutes) and cutting rate (area cut/time). The savings and effectiveness were analyzed using a percentage increase method.
Finding/Results: The results showed that the smart lawn mower reduced operational time by 50% (from 40 minutes to 20 minutes) and increased the cutting rate by 100% compared to the manual method.
Conclusion: The automated system significantly enhances time efficiency and productivity. It also supports green campus initiatives through efficient technology and user-friendly maintenance. This research demonstrates the potential of integrating automated technology into landscape maintenance as a modern, sustainable solution and lays the groundwork for future IoT-based smart lawn mower systems.
References
Aboagye, S., Mensah, K., & Boateng, P. (2024). Smart campus transformation: Integrating IoT and data analytics in higher education facilities. Journal of Smart Environments, 15(3), 221–235.
Chen, L., & Luo, X. (2024). Performance assessment of autonomous robotic lawnmowers under variable terrain conditions. Robotics and Autonomous Systems, 175, 104756.
Hossain, R., Alam, M., & Islam, K. (2022). Efficiency optimization of high-speed DC motors in automated cutting applications. Measurement: Sensors, 24, 100482.
Nordin, M., Halim, N., & Yusof, A. (2021). Influence of blade speed uniformity on grass cutting performance. Applied Mechanics and Materials, 920, 85–91.
Zhang, J., Wang, R., & Lee, S. (2023). Comparative analysis of robotic and manual lawn mowing systems: A time-efficiency perspective. Sustainable Engineering Innovations, 12(4), 317–326.
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