Online shopping isasasas buying products or services via the internet using a computer or mobile platform. It provides a different policy and environment to both consumers and suppliers for having business activities in a digital environment than a traditional way. Some countries are highly adopted and utilizing online shopping for their day to day operations. There are some differences among countries in consumers’ buying behavior toward online shopping, which may be the reason for comfortability and reliability about the procedure and policies of digital environments. Online shopping is one of the convenient and best solutions for the busy life of today’s world. This study aims to identify those options for why users select online shopping rather than traditional shopping. The research model explained and predicted the behavioral intention and attitude towards online shopping. The convenient sampling method was used to select the sample units, and the Snowball sampling method was used to identify online shopping users. The questionnaire consists of two main sections. The first section analyzes the demographic factors related to online shopping. The second section included TAM variables. among the participants, 35(56%) were males, and 27(44%) females. The majority of 31(50%) of the online shopping users were between 25 to 30 years, and the rest (6%) were above 40 years. As expected, the experience of online shopping almost 34% of the respondents have less than ten years. Whereas the rest differ in their online shopping experience, those who used online shopping for 1-3 years stood at 31%. Moreover, 24% of the respondents have 3-5 years’ experience. Only a few respondents have more than five years’ experience. It stood for 11%. This study revealed that users comprehensively supported online shopping behavior except for four hypotheses. Thus, it could be concluded that people prefer online shopping because of their knowledge, usefulness, and attitude towards online shopping. The relation between attitude and behavioral intention is strongly positive and significant.

The time and attendance systems help to monitor the employers and students working and attending time. Educational systems are struggling with the traditional system. It affects the pedagogical activities considerably. The traditional system is encountering many problems, and there is a need for a robust technological solution. This study focuses on building a two-factor prototype with RFID, IoT, and machine learning techniques. A microcontroller, GSM module, RFID tag, an RFID reader are used for first step verification. A camera with Multitask Cascaded Convolutional Network (MTCNN) model is used for a second verification. When both are okay, students will get the attendance. If it fails, parents will get a notification about the student’s attendance. When the prototype is developed as a complete system, the educational system will be getting higher advantages.

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