Cloud Based Point of Sale System with Face Recognition

A Point of Sale (POS) is an electronic banking outlet that enables customers to complete the basic financial transactions using debit or credit cards without the aid of bank representative or teller. It is an electronic banking outlet that enables customers to complete the basic financial transactions using debit or credit cards without the aid of bank representative or teller. The Traditional POS system runs on closed networks and the user data is stored on local servers. They need to be updated manually on-site. POS systems generally accept credit and debit cards to process bills. It is found that there is increase in levels of fraud among the users of credit and debit card. So there is a requirement to build a system that can store the data securely and also do the transactions without giving scope to any fraudulent activities. For the effective and efficient operations of security systems, accurate and automatic recognition of persons is becoming increasingly important. As a solution our proposed system ‘Cloud Based POS System with Face Recognition and Password with Cloud implementation’ is proposed as a method of payment making POS systems both card less and cashless. FaceNet which was proposed by Google Researchers was used for implementing face verification and recognition, along with password verification as a two-step authentication. We use FaceNet and Multi-Task Cascaded Convolutional Neural Network, for detection and identification of faces. This POS system will do more, than just accepting payments. Here we also try to Integrate Cloud Computing (CC) with the system which makes it more secure. The combination of POS system with Cloud Computing will make our new system more reliable and faster. It is studied that this technique is not very expensive and it gives us an accuracy rate of about 96.75%