Design and Development of an Automated Forklift with IOT Weight System

This paper presents the design and development of an automated forklift system with integrated IoT-based weight monitoring and RFID-based pallet identification, aimed at enhancing efficiency and safety in industrial material handling. The forklift autonomously identifies, loads, and transports pallets using RFID technology, ensuring accurate pallet selection and handling. The IOT- based weight system, monitored via the Blynk app, enables real-time load tracking and overload alerts, safe operation. Path-following capabilities are achieved using IR sensors, while ultrasonic sensors provide effective obstacle detection, allowing precise navigation within medium scale industrial environments. By minimizing human intervention, the forklift system optimizes productivity, and offers a scalable solution for medium- scale industries. Results demonstrate the forklift’s effectiveness in automating complex tasks in industrial settings, contributing to improved workflow and operational reliability.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-05
DOI
https://doi.org/10.5281/zenodo.14287510
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
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article

Design and Development of an Automated Forklift with IOT Weight System

Zenodo (CERN European Organization for Nuclear Research)
Advanced Manufacturing and Logistics Optimization
article

Design and Development of an Automated Forklift with IOT Weight System

article en

Abstract

This paper presents the design and development of an automated forklift system with integrated IoT-based weight monitoring and RFID-based pallet identification, aimed at enhancing efficiency and safety in industrial material handling. The forklift autonomously identifies, loads, and transports pallets using RFID technology, ensuring accurate pallet selection and handling. The IOT- based weight system, monitored via the Blynk app, enables real-time load tracking and overload alerts, safe operation. Path-following capabilities are achieved using IR sensors, while ultrasonic sensors provide effective obstacle detection, allowing precise navigation within medium scale industrial environments. By minimizing human intervention, the forklift system optimizes productivity, and offers a scalable solution for medium- scale industries. Results demonstrate the forklift’s effectiveness in automating complex tasks in industrial settings, contributing to improved workflow and operational reliability.

Zenodo (CERN European Organization for Nuclear Research)
M S Ramaiah University of Applied Sciences (IN), Robotics Research (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 51%
Advanced Manufacturing and Logistics Optimization
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Design and Development of an Automated Forklift with IOT Weight System · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS