ShopMate

Eman Wasfy Ishtawi; Toqa Omar AbdAlDayem

ShopMate

dc.contributor.author	Eman Wasfy Ishtawi
dc.contributor.author	Toqa Omar AbdAlDayem
dc.date.accessioned	2026-08-19T10:12:44Z
dc.date.issued	2026-01-27
dc.description	--
dc.description.abstract	This project aims to enhance the shopping experience by helping customers easily locate items without prior knowledge of the supermarket layout. It saves time, reduces confusion, and supports individuals such as elderly people or first-time visitors. The system introduces automation and smart navigation into everyday retail environments, promoting the concept of intelligent shopping. The project focuses on several key aspects, including accurate indoor navigation to ensure autonomous and safe movement, collision avoidance using LiDAR, ultrasonic, accelerometer, gyroscope, and speed sensors, item scanning to allow users to view product prices and track their total cost, user-friendly interaction for entering shopping lists, and efficient path planning to minimize walking distance. The main objectives are to design and implement an autonomous cart that guides users to desired items, ensures smooth and safe movement through multi-sensor integration, and simplifies the shopping process by providing real-time product information. The methodology involves defining hardware and software components, using LiDAR for real-time mapping and localization, developing path-planning and obstacle-avoidance algorithms, integrating data from multiple sensors for stability, and building a simple user interface for inputting lists and scanning products. While some experimental smart carts exist globally, this project has not been developed before at our university, particularly not in this integrated form combining autonomous navigation with real-time LiDAR mapping and product price scanning.
dc.description.sponsorship	--
dc.description.statementofresponsibility	The significance of this project lies in its relevance to current market demands for smart retail solutions that improve efficiency, security, and accessibility. Retailers face increasing losses due to theft, rising labour costs, and customer dissatisfaction caused by long checkout times. The proposed smart shopping cart addresses these challenges by integrating automated item verification, theft prevention mechanisms, and autonomous navigation. From a customer perspective, the system offers a more convenient and guided shopping experience. The cart assists users in locating items efficiently, particularly benefiting customers who are unfamiliar with a store layout or shopping in a foreign country. Additionally, the system provides meaningful support for elderly users and individuals with mobility or control difficulties by reducing the need for manual cart handling. From a technical and commercial standpoint, this project demonstrates how low-cost, widely available hardware components such as Arduino, Raspberry Pi, LiDAR sensors, and standard communication modules can be combined to create a sophisticated intelligent system. The inclusion of boycott item detection also introduces an ethical and user-aware feature that enhances informed purchasing decisions. From an academic perspective, this work provides hands-on experience in robotics, embedded systems, and system integration within a real-world application. It aligns with current trends in autonomous systems and smart retail technologies.
dc.description.tableofcontents	The primary purpose of this project is to design and develop an intelligent smart shopping cart that enhances the shopping experience through autonomous assistance, secure item verification, integrated payment, and user-focused safety mechanisms. The system is intended to function as a reliable “shopping companion” that supports users throughout the shopping process while addressing common issues such as navigation difficulty, accidental or intentional item misplacement, and theft. The main objectives of this work are to: • Develop a smart shopping cart capable of operating in two distinct modes: manual mode and automatic mode. • Implement a manual control system that allows users to directly command the cart to move forward, turn left or right, and stop. • Design an automatic navigation system in which the cart autonomously navigates to items in the user’s shopping list based on proximity, rather than the order in which items were added, thereby optimising travel distance and time. • Perform accurate localisation and autonomous navigation in an indoor retail environment using LiDAR sensing, supported by rotational data from an MPU sensor to improve localisation accuracy. • Use three ultrasonic sensors positioned to monitor the front, left, and right sides of the cart, providing proximity-based safety by automatically halting motion when obstacles are detected during forward movement or turning operations. • Enable item scanning functionality that operates only when the cart is in a safe stop state, regardless of whether it is in manual or automatic mode. • Implement an item verification mechanism that checks whether a scanned item exists in the user’s cart list before allowing placement. • Handle accidental scanning events by prompting the user to confirm whether they wish to add an unlisted item to their cart. • Integrate a weight verification system that compares the measured weight of an item placed in the cart with its expected weight stored in a database. • Prevent theft by activating an audible warning if a weight mismatch is detected and requiring RFID-based employee authorisation to resolve the alert. • Detect and warn users when boycotted items are scanned to prevent unintentional purchases. • Continuously monitor Bluetooth connectivity and immediately stop all cart functions if the connection to the user is lost, preventing unintended cart movement. • Use a Raspberry Pi as a bridge between the Arduino-based control system and the LiDAR sensor, while also hosting a screen-based application for user interaction. • Provide audio feedback through a speaker to support users who prefer or require voice- based interaction. • Integrate a secure digital payment process using Stripe, allowing users to complete payment directly from the cart interface. • Design the system to assist users who are unfamiliar with the store layout or local language, as well as elderly users or individuals with difficulty controlling a conventional shopping cart.
dc.format.medium	Hardware
dc.identifier.citation	--
dc.identifier.other	12113093
dc.identifier.uri	https://hdl.handle.net/20.500.11888/21280
dc.language.iso	en
dc.publisher	Dr. Ashraf Armoush
dc.relation.ispartofseries	--
dc.subject.classification	Information Technology
dc.supervisor	Dr. Ashraf Armoush
dc.title	ShopMate
dc.title.alternative	--
dc.type	Graduation Project
person.telephone	+972592542676