Wireless and Voice-Controlled Automated 2-Wheel Drive Forklift for Enhanced Industrial Warehouse Operations
The automation technology is expected to become integrated into two-wheel drive forklifts, which is one of the fascinating growths in the rapidly growing forklift automation field. Forklift automation technologies have enhanced the management of material handling and warehouse operations in modern societies. Research has indicated that it enhances efficiency, security and productivity of a facility where it is applied. With it the industrial sector could be revolutionized by the reduction of labor costs, the minimization of the risks of accidents and the optimization of the utilization of space. Robotics, automation, IoT, and artificial intelligence will all be utilized for the manufacture of fully automated two-wheel drive forklifts. This technology enables forklifts to lift and transport pallets, load and unload cargo or transport goods within a given area. Forklifts designed with automation technologies interlinked and running do run safer and with less manpower input. To make operations using the forklift easy to perform, research efforts will focus on enhancing the use of advanced wireless communication technologies, Mobile Computing, and Speech Recognition. One of the primary controls that helps the customers to drive the forklift using their smart devices by sending instructions is through the application developed for the purpose. It is hands-free as speech recognition capability is also provided. Future expansions of voice and mobile controlled industrial automation systems are enabled by this program.
Authors
- Muhammad Yasir Jamal (ORCID: https://orcid.org/0000-0002-7231-6413)
- Muhammad Shahid (ORCID: https://orcid.org/0000-0002-4039-8856)
- Muhammad Zia Ur Rahman
- Aashir Waleed (ORCID: https://orcid.org/0000-0002-6929-8373)
- Muhammad Sohaib (ORCID: https://orcid.org/0000-0003-2743-3706)
- Misbah Mehrab
Institutions
- University of Engineering and Technology Lahore (PK)
- University of Faisalabad (PK)
Publication Details
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1109/etecte63967.2024.10823715
- Citations
- 1
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.35