Shiffters

Abstract

The relocation of residential properties in Pakistan presents significant challenges for consumers. Traditional moving services frequently employ opaque pricing struc tures, resulting in unexpected additional charges that were not communicated during initial consultations. Furthermore, customers regularly experience damaged or miss ing belongings, with limited accountability from service providers. These persistent issues within the industry necessitated the development of an innovative solution. This paper presents Shiffters, a comprehensive mobile and web application designed to connect users with verified moving companies while ensuring transparency and accountability throughout the relocation process. The platform was developed us ing Flutter for cross-platform compatibility, Firebase for authentication and real time data management, and YOLO (You Only Look Once) for artificial intelligence powered object recognition and real-time inventory management capabilities. The development methodology followed a systematic approach encompassing user consul tation, system architecture design, implementation, and rigorous testing protocols. A distinguishing feature of the application is its AI-powered camera functionality, which enables automatic recognition and cataloging of furniture and boxes through computer vision. This eliminates the traditional manual inventory process conducted by moving personnel, which is prone to errors and omissions. The platform provides users with real-time truck tracking capabilities, transparent cost estimation, and comprehensive digital documentation, thereby eliminating paper-based processes. Empirical validation conducted with actual users demonstrated measurable improve ments across multiple metrics: significant reduction in lost items, decreased comple tion time for relocation services, and substantially lower stress levels reported by customers throughout the moving experience.