ARCHIVES

Original Article

Driver Hiring System: A Web-Based Solution Using PHP

Prajwal Angalwar1Minal Patle2Bhagyashree Kumbhare3Yamini B. Laxane4

¹²Students, Department of MCA, Smt. Radhikatai Pandav College of Engineering, Nagpur, Maharashtra, India. ³Professor&HOD, Department of MCA, Smt. Radhikatai Pandav College of Engineering, Nagpur, Maharashtra, India. ⁴Professor, Department of MCA, Smt. Radhikatai Pandav College of Engineering, Nagpur, Maharashtra, India.

Published Online: May-August 2025

Pages: 144-147

Abstract

The rise of digital platforms has transformed various service industries, including transportation. One of the persistent issues in urban and semi-urban areas is the difficulty in hiring reliable and professional drivers. The traditional systems lack scalability, transparency, and operational efficiency. This paper presents the design and implementation of a dynamic, web-based Driver Hiring System developed using PHP, MySQL, and XAMPP. The system is intended to act as a middle layer between drivers and customers, offering a secure, user-friendly, and automated solution for managing driver hiring requests, registrations, and feedback. It also introduces an administrative interface for effective monitoring and management of the service. The system architecture, functionality, database design, security protocols, and testing mechanisms are comprehensively described to present a complete deployment-ready application

Related Articles

2025

Transforming Cyber-Physical Systems: Machine Learning for Secure and Efficient Solutions

2025

Exploring AI Techniques for Quantum Threat Detection and Prevention

2025

Maturity Models for Business Intelligence: An Overview

2025

INSPIRO: An AI Driven Institution Auditor

2025

Adaptive AI Framework for Anomaly Detection and DDoS Mitigation in Distributed Systems

2025

Predictive Modeling for College Admission Using Machine Learning and Statistical Methods

2025

Restaurant Table Reservation with Food Ordering

2025

A IoT-Driven Smart Commerce: Redefining Consumer Experience and Operational Efficiency in E-Commerce Platforms

2025

Agricultural Products: CVF Yield Prediction Using Ensemble Methods and Machine Learning Models

2025

Identifying and Forecasting Wastewater Pollutions Wring IOT & NLP