Empirical Evaluation of IoT-Based Smart Load Delivery Robot for Real-Time Payload Performance Monitoring and Analysis System
Keywords:
IoT, Arduino Nano, Smart Load Delivery Robot, Real-Time, Load-Carrying PerformanceAbstract
Introduction/Main Objectives:The aim of the study was to evaluate the performance of an IoT-based smart delivery robot utilizing the Arduino Nano microcontroller and to analyze the delivery speed achieved by the smart delivery robot compared to the manual delivery method.
Background Problems: Existing low-cost transport robots typically suffer from unquantified performance degradation under varying loads and lack synchronous monitoring frameworks to support physics-based performance benchmarking.
Novelty: This work presents a controlled empirical study of an IoT-integrated smart load delivery robot supported by a local microcontroller-based IoT network. The architecture transforms real-time telemetry into actionable insights, empowering smarter robotic control optimization and introduces a scalable benchmarking blueprint for delivery robots built for space-limited environments.
Research Methods:The system was built around an embedded Arduino Nano unit responsible for motion control and deterministic local data streaming.Three operator-involved trials were conducted across a 30m delivery track.The trials used standardized payload increments of 2kg and 3kg.
Finding/Results:The results show a time saving range between 14.65% and 19.76% for a 2kg load over 30 meters. For a 3kg load, the results show time savings of 13.33% to 14.19%.The research shows that the robot has a stable design for carrying loads, which is very good.
Conclusion: The research demonstrates that the Smart Load Delivery Robot saves delivery time. Its design is stable for carrying loads. The architecture provides a foundation for smarter robotic control optimization and a scalable benchmarking blueprint.
References
Craig, J. J. (2018). Introduction to Robotics: Mechanics and Control (4th ed.). Pearson.
Beginning Robotics with Raspberry Pi and ArduinoAlciatore, D. G., & Ok, H. (2020). Beginning Robotics with Raspberry Pi and Arduino. Apress.
Priya, S., & Holm, J. (2025). IoT-enabled small robot benchmarking under conditioned payload variability for indoor logistics environments. Journal of Autonomous and Indoor Robotics Systems, 8(1), 42–59.
Li, X., Wang, Y., & Zhao, Q. (2020). Design and development of a Bluetooth- controlled indoor service robot. International Journal of Advanced Robotic Systems, 17(5), 1–12. https://doi.org/10.1177/1729881420961234
Monk, S. (2019). Programming Arduino: Getting Started with Sketches (3rd ed.). McGraw-Hill Education.12-200
Robotics Trends. (2022). Omni-wheel mobile robots for indoor delivery. Retrieved from https://www.roboticstrends.com
Sharma, R., & Singh, A. (2021). Smart service robots for indoor delivery: A review. Journal of
Robotics and Autonomous Systems, 142, 103751.
https://doi.org/10.1016/j.robot.2021.103751
Siciliano, B., & Khatib, O. (2016). Springer Handbook of Robotics (2nd ed.). Springer
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