| Titre : | Swaply Peer-to-Peer Delivery Platform Powered by AI |
| Auteurs : | FARHI Abderrahmane Tayeb, Auteur ; FARHANE Mohammed El Amin, Auteur ; RAHMANI Mohamed Elhadi, Directeur de thèse ; Bouarara Hadj Ahmed, Directeur de thèse |
| Type de document : | texte manuscrit |
| Editeur : | Université de Saïda – Dr. Moulay Tahar – Faculté des Mathématiques, de l’Informatique et des Télécommunications, 2025/2026 |
| Format : | 72ض |
| Accompagnement : | CD |
| Langues: | Anglais |
| Index. décimale : | BUC-M 008534 |
| Catégories : | |
| Résumé : |
ملخص
Résumé يقدممشروع"Swaply"، وهو منصة لوجستية رقمية تشاركية تهدف إلى ربط العمالء بسائقينمستقلين لتسهيل عمليات نقل البضائع والطرود بكفاءة وموثوقية عالية. يعتمد النظام على بنية معماريةمتكاملة توفر واجهات مخصصة لكل من العميل، السائق، واإلدارة، مما يضمن تنظيم سير العمل بشكل آمن وسلس. تقدم المنصة ميزات متقدمة تشمل التتبع اللحظي للرحالت، التسعيرالديناميكي، والتواصل المباشر. وتبرز قوة المشروع في اعتماده المعمق على تقنيات الذكاء االصطناعي لحل التحديات األمنية والتشغيلية؛حيث يشتمل على نظام أمني ذكي للتحقق من هويات السائقين ومطابقتها، وخوارزمية دقيقة لتصفية التقييماتالوهمية لضمان شفافية المنصة، باإل ًضافة إلى مساعد افتراضي مدمج لدعم المستخدمين آلياً. ختاما، يجسد هذا المشروع حال ً برمجيا ً متطورا ً يخلق بيئة نقل لوجستية آمنة، ذكية، وعالية الموثوقية. This project presents "Swaply", a collaborative digital logistics platform aimed at connecting customers with independent drivers to facilitate the transport of goods and parcels with high efficiency and reliability. The system relies on an integrated architecture that provides dedicated interfaces for the customer, the driver, and the administration, ensuring a secure and seamless workflow. The platform offers advanced features, including real-time trip tracking, dynamic pricing, and direct communication. The core strength of the project lies in its deep integration of Artificial Intelligence (AI) to address security and operational challenges; it encompasses a smart security system for driver identity verification and matching, a precise algorithm for filtering fake reviews to ensure platform transparency, and a built-in virtual assistant for automated user support. Ultimately, this project embodies a sophisticated software solution that establishes a secure, intelligent, and highly reliable logistics environment. Ce projet présente "Swaply", une plateforme logistique numérique collaborative conçue pour connecter les clients à des chauffeurs indépendants afin de faciliter le transport de marchandises et de colis avec une efficacité et une fiabilité élevées. Le système repose sur une architecture intégrée offrant des interfaces dédiées pour le client, le chauffeur et l'administration, garantissant ainsi un flux de travail sécurisé et fluide. La plateforme propose des fonctionnalités avancées comprenant le suivi des trajets en temps réel, la tarification dynamique et la communication directe. La force principale du projet réside dans sa profonde intégration des technologies d'Intelligence Artificielle (IA) pour relever les défis sécuritaires et opérationnels ; il intègre un système de sécurité intelligent pour la vérification et la correspondance des identités des chauffeurs, un algorithme précis de filtrage des faux avis pour assurer la transparence de la plateforme, ainsi qu'un assistant virtuel intégré pour le support automatisé des utilisateurs. En conclusion, ce projet incarne une solution logicielle sophistiquée qui crée un environnement de transport logistique sécurisé, intelligent et hautement fiable. |
| Note de contenu : |
Contents
GENERAL INTRODUCTION........................................................................................ 1 CHAPTER 1: PROJECT CONTEXT AND PROBLEM STATEMENT ....................... 2 1.1 Introduction ............................................................................................................ 2 1.2 Problem Statement ................................................................................................. 2 1.3 Existing Limitations ............................................................................................... 3 1.4 Project Objectives .................................................................................................. 3 1.5 Conclusion ............................................................................................................. 3 Chapter 2: State of the Art ............................................................................................... 4 2.1 Introduction ............................................................................................................ 4 2.2 Peer-to-Peer Delivery Platforms ............................................................................ 4 2.2.1 Overview and Evolution .................................................................................. 4 2.2.2 Uber Connect ................................................................................................... 5 2.2.3 Yassir Delivery ................................................................................................ 5 2.2.4 Glovo ............................................................................................................... 5 2.3 Identity Verification and Facial Recognition Technologies .................................. 6 2.3.1 The Role of Identity Verification in P2P Platforms ........................................ 6 2.3.2 Using Convolutional Neural Networks for Face Verification ......................... 6 2.4 Conversational AI and LLM-Based Customer Support ......................................... 7 2.4.1 From Rule-Based Dialog Systems to LLMs ................................................... 7 2.4.2 Groq API and Inference Acceleration ............................................................. 7 2.5 Fake Review Detection .......................................................................................... 7 2.5.1 Review Manipulation Problem ........................................................................ 7 2.5.2 Machine Learning Approach ........................................................................... 8 2.6 Comparative Analysis and Research Gaps ......................................................... 9 2.7 Conclusion ........................................................................................................... 10 CHAPTER 3: SYSTEM REQUIREMENTS AND ANALYSIS .................................. 11 3.1 Introduction .......................................................................................................... 11 3.2 System Actors ...................................................................................................... 11 IV 3.3 Functional Requirements ..................................................................................... 11 3.3.1 Global Layout & Access Control .................................................................. 11 3.3.2 Passenger Hub (Client Operations) ............................................................... 12 3.3.3 Driver Workspace (Driver Operations) ......................................................... 12 3.3.4 Admin Panel (Operations Room) .................................................................. 12 3.3.5 Integrated AI Systems ................................................................................... 13 3.4 Non-Functional Requirements ............................................................................. 13 3.5 Use Case Overview .............................................................................................. 14 3.6 Conclusion ........................................................................................................... 14 CHAPTER 4: SYSTEM ARCHITECTURE ................................................................. 15 4.1 Introduction .......................................................................................................... 15 4.2 Architectural Overview ........................................................................................ 15 4.3 Frontend Structure (Client-Side) .......................................................................... 15 4.4 Backend Structure (Server-Side).......................................................................... 16 4.5 Data Model ........................................................................................................... 18 4.6 Technology Stack ................................................................................................. 18 4.7 System Dynamics (Sequence Diagrams) ............................................................. 19 4.8 Conclusion ........................................................................................................... 24 CHAPTER 5: IMPLEMENTED MODULES ............................................................... 25 5.1 Introduction .......................................................................................................... 25 5.2 Authentication and Smart Routing ....................................................................... 25 5.3 Delivery Management Module (Passenger Side) ................................................. 26 5.4 Trip Management Module (Driver Side) ............................................................. 27 5.5 Real-Time Trip Lifecycle and State Management ............................................... 27 5.6 Driver Onboarding and Verification Gateway ..................................................... 28 5.7 Admin Dashboard & Verification Control Room ................................................ 29 5.8 Virtual Assistant Interface (AI Chatbot) .............................................................. 30 5.9 Trust, Rating, and AI Review Filtering ................................................................ 31 5.10 Conclusion .......................................................................................................... 32 Chapter 6: AI Systems — Integration and Evaluation .................................................. 33 6.1 Introduction .......................................................................................................... 33 V 6.2 AI System 1 — Face Verification Module .......................................................... 34 6.2.1 Overview and Purpose ................................................................................... 34 6.2.2 Technical Architecture and Verification Pipeline ......................................... 34 6.2.3 System Components ...................................................................................... 36 6.2.4 Integration with the Swaply Platform............................................................ 36 6.2.5 Evaluation and Model Justification ............................................................... 37 6.3 AI System 2 — Fake Review Detector ................................................................ 37 6.3.1 Overview and Purpose ................................................................................... 37 6.3.2 Dataset Description ....................................................................................... 37 6.3.3 Feature Engineering....................................................................................... 38 6.3.4 Model Selection and Architecture ................................................................. 38 6.3.5 Training Procedure ........................................................................................ 38 6.3.6 Feature Groups .............................................................................................. 39 5.3.7 Evaluation Results ......................................................................................... 41 6.3.8 Analysis of Results ........................................................................................ 45 6.3.9 Platform Integration....................................................................................... 46 6.4 AI System 3 — Customer Support Chatbot ......................................................... 47 6.4.1 Overview and Purpose ................................................................................... 47 6.4.2 Technology Selection — Groq API and Large Language Models................ 47 6.4.3 System Architecture and Integration ............................................................. 48 6.4.4 Prompt Engineering and Domain Configuration ........................................... 50 6.4.5 Types of Queries Handled ............................................................................. 51 6.4.6 Conclusion ..................................................................................................... 52 CHAPTER 7: SECURITY, PRIVACY, AND ETHICAL CONSIDERATIONS......... 53 7.1 Introduction .......................................................................................................... 53 7.2 Privacy Considerations ........................................................................................ 53 7.3 Security Considerations ....................................................................................... 53 7.3.1 Stateless Authentication via JSON Web Tokens (JWT ................................ 54 7.3.2 Cryptographic Password Hashing ................................................................. 54 7.3.3 Role-Based Access Control (RBAC) Enforcement ....................................... 54 7.3.4 Securing Real-Time WebSockets .................................................................. 54 VI 7.3.5 Input Validation and Injection Prevention .................................................... 54 7.4 Ethical Considerations ......................................................................................... 55 7.5 Conclusion ........................................................................................................... 55 CHAPTER 8: EVALUATION AND TESTING ........................................................... 56 8.1 Introduction .......................................................................................................... 56 8.2 Evaluation Dimensions ........................................................................................ 56 8.3 Testing Approach ................................................................................................. 56 8.4 Results .................................................................................................................. 57 8.5 Conclusion ........................................................................................................... 58 CHAPTER 9: LIMITATIONS AND FUTURE WORK ............................................... 59 9.1 Introduction .......................................................................................................... 59 9.2 Current Limitations .............................................................................................. 59 9.3 Future Work ......................................................................................................... 59 9.4 Conclusion ........................................................................................................... 60 GENERAL CONCLUSION .......................................................................................... 61 |
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