DevMesh

Smart Kart

Dev Aryan Khanna

Dev Aryan Khanna

Delhi

4 1

Smart Kart uses IoT to reduce queues in malls with a smart cart. Products are automatically scanned and added to the bill when placed in the cart. No manual scanning, faster checkout. IoT enhances the shopping experience, minimizing queues, and satisfying customers. ...learn more

Project status: Under Development

Mobile, Robotics, Networking, Internet of Things, Artificial Intelligence, Graphics and Media, PC Skills, Cloud

Intel Technologies
DevCloud, Other, Intel CPU

Code Samples [1]

Overview / Usage

Smart Kart is an IoT-based project that addresses the common problem of long queues in shopping malls. By introducing a smart shopping cart system, Smart Kart streamlines the checkout process. When a user places a product in the cart, it is automatically scanned and added to their bill. This eliminates the need for manual scanning, saving time for both shoppers and retailers.

The project utilizes IoT technology to enable seamless communication between the smart cart and a central system. The cart's sensors and connectivity allow for real-time product recognition and billing. By leveraging this technology, Smart Kart significantly reduces waiting times, creating a more efficient and satisfying shopping experience.

The research and development of Smart Kart involve designing and implementing advanced computer vision algorithms and machine learning models. These technologies enable accurate and fast product scanning, ensuring reliable billing and inventory management. The project also requires integrating secure payment gateways and building a robust backend system for processing transactions.

In production, Smart Kart can be experienced as an IoT-based solution available in shopping malls. Shoppers can simply place products in the cart, knowing that their purchases will be automatically scanned and added to their bill. This technology not only eliminates the hassle of manual scanning but also reduces the overall time spent in queues, improving customer satisfaction and optimizing store operations.

Overall, Smart Kart represents an innovative application of IoT and AI technologies in the retail industry. By addressing the problem of long queues in shopping malls, the project enhances the shopping experience, improves efficiency, and offers a glimpse into the future of automated and seamless retail transactions.

Methodology / Approach

Methodology used in this project are :-

  1. IoT Integration: The project involves integrating IoT technology into shopping carts, enabling communication between the carts and a central system. This integration can be achieved using wireless connectivity protocols such as Wi-Fi or Bluetooth, allowing for real-time data transmission between the cart and the backend system.
  2. Computer Vision and Machine Learning: Smart Kart utilizes computer vision algorithms and machine learning models for product recognition. These technologies enable the automatic scanning and identification of products placed in the cart. Advanced image processing techniques and deep learning frameworks like TensorFlow or PyTorch can be employed to train models on extensive product databases.
  3. Data Security: To ensure secure transactions, the project must implement robust data encryption techniques and adhere to industry-standard security protocols. Secure communication channels, encryption algorithms, and user authentication mechanisms are essential to protect sensitive customer data.
  4. Payment Integration: Smart Kart needs to integrate with various payment gateways to facilitate automated billing. This involves implementing secure payment APIs and protocols to securely process transactions and deduct amounts from users' chosen payment methods, such as bank accounts or digital wallets.
  5. Backend Processing: A scalable and efficient backend system is required to handle the real-time processing of scanned products, generate bills, and manage inventory. This may involve leveraging cloud computing services, database management systems, and scalable server architectures.
  6. User Experience: The project should prioritize a user-friendly interface for shoppers. This includes designing intuitive scanning mechanisms, providing real-time feedback on scanned items, and delivering personalized recommendations based on user preferences and shopping history.

Technologies Used

Technologies:

  1. Internet of Things (IoT) - for enabling communication and connectivity between the smart shopping carts and the backend system.
  2. Computer Vision - for product recognition and scanning using image processing algorithms and machine learning models.
  3. Machine Learning - for training models to recognize and identify products accurately.
  4. Cloud Computing - for scalable storage, processing, and hosting of the backend system.
  5. Payment Gateway Integration - for secure and automated billing processes.
  6. Mobile Development - for creating mobile applications to interface with the smart carts and provide real-time information to users.

Libraries and Tools:

  1. TensorFlow or PyTorch - popular deep learning frameworks for training computer vision models.
  2. OpenCV - a computer vision library for image processing tasks.
  3. MQTT or HTTP - communication protocols for transmitting data between the smart carts and the backend system.
  4. RESTful APIs - for integrating with external services, such as payment gateways.
  5. Database Management Systems - for efficient data storage and retrieval, such as MySQL or MongoDB.
  6. Agile Methodologies - Scrum or Kanban for iterative and collaborative development.

Software:

  1. Backend System - a custom-built software system for processing scanned products, generating bills, and managing inventory.
  2. Mobile Application - for users to interact with the smart carts, view real-time product information, and make payments.

Hardware:

  1. Smart Shopping Carts - equipped with IoT sensors, barcode scanners, and wireless connectivity for automatic product scanning.
  2. Mobile Devices - smartphones or tablets used by shoppers to interact with the smart carts.

Intel Technologies: Intel offers a range of technologies that could be utilized in the development of the Smart Kart project, including:

  1. Intel IoT Development Kits - for building IoT-enabled devices and connecting them to the Intel IoT Platform.
  2. Intel Processors - for efficient data processing and computation in the backend system.
  3. Intel RealSense Cameras - for advanced computer vision capabilities, such as depth sensing and object recognition. (To Be Added

Repository

https://github.com/divyansh383/Smart-Cart

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