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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67817
Volume:
10 |
10 |
Oct 2026
Pages:
1-7
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.

Electronics & Telecommunication Engineering
JSPM's Bhivrabai Sawant Polytechnic, Wagholi

Electronics & Telecommunication Engineering
JSPM's Bhivrabai Sawant Polytechnic, Wagholi

Electronics & Telecommunication Engineering
JSPM's Bhivrabai Sawant Polytechnic, Wagholi

Electronics & Telecommunication Engineering
JSPM's Bhivrabai Sawant Polytechnic, Wagholi

Electronics & Telecommunication Engineering
JSPM's Bhivrabai Sawant Polytechnic, Wagholi
Industrial material handling is an essential activity in manufacturing and storage environments, but conventional transportation methods generally depend on continuous human effort and may require considerable time. This paper presents the design of an AI Smart Industrial Material Transport Robot intended to provide an intelligent and automated approach to internal material movement. The proposed system combines Artificial Intelligence with an ESP32 controller, RFID module, load cell, ultrasonic sensor, camera module, motor driver, DC motors and IoT/Wi-Fi connectivity. RFID is used for material identification, while the load cell provides weight-related information and the ultrasonic sensor supports obstacle detection. Camera information is considered for image processing and AIbased decision making. The ESP32 coordinates the control process and operates the motors through the L298N motor driver. The proposed architecture is aimed at reducing manual handling, improving workplace safety, reducing transportation time and supporting efficient industrial operations. Experimental performance results are not included at this stage because the prototype is under development.
KEYWORDS
The Al Smart Industrial Material Transport Robot presents an integrated approach automated material movement in industrial environments. The proposed architecture combines RFID-based material identification, load-cell weight sensing, ultrasonic obstacle detection, camera-based visual information, Al processing, ESP32 control, L298N motor driving, DC motors and IoT/Wi-Fi monitoring. The combination intended to reduce manual handling, support safer movement and improve the efficiency of repetitive internal transportation. The project is currently at the prototype-development stage; therefore, final experimental measurements are not included. Practical testing will be required to establish load capacity, navigation performance, obstacle response, battery endurance and
[1] K. Ellithy et al., “AGV and Industry 4.0 in Warehouses,” International Journal of Advanced Manufacturing Technology, 2024. [2] T. Lackner et al., “Autonomous Mobile Robots in Intralogistics,” Procedia CIRP, 2024. [3] W. X. Oh et al., “Autonomous Mobile Robot for Transporting Goods,” 2024. [4] N. P. Panta et al., “Autonomous Mobile Robot for Material Handling,” 2024. [5] “Autonomous Industrial Mobile Warehouse,” Applied Sciences, 2024. [6] Y. Gong and R. B. M. de Koster, “Autonomous Mobile Robot Systems,” Transportation Science, 2024. [7] “Digital Twin-Based Reinforcement Learning for AMR,” International Journal of Computer Integrated Manufacturing, 2024. [8] N. Demir et al., “Autonomous Mobile Robot Using ROS,” International Journal of 3D Printing Technologies, 2024. [9] D. Selvaraj et al., “AGV for Material Handling Using RFID,” 2024. [10] “IoT-Based Robotic Arm for Product Sorting,” Electronics, 2025.
Publication Date
10/12/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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