Along with the rapid development of technology today, electronic devices have become commonplace for generation z. One of the uses of the current pandemic era is for learning activities. This computer-based test Tryout application was developed as a student learning tool to face the real exam. Using the simulation method, students can do UTBK tryouts repeatedly until they reach the minimum target requirements. This application is expected to provide convenience for students to know their abilities and can improve their knowledge. So that students can be better prepared for the exam.

The Internet of Things (IoT) should be able to handle heterogeneous systems in a transparent and stable manner by providing open access to the selected data subset for the development of a large number of digital services. Building a common architecture for IoT is a very complex task, mainly because of the huge variety of devices, different technologies and services required. In this paper, we focus exclusively on large urban IoT systems. IoT's development is designed to support smart city’s vision to utilize the most advanced communications technologies to support value-added services for city administration and for citizens. The paper provides a comprehensive survey of technologies, protocols, and architectures that allow for urban IoT.

Object detection is one step in object recognition in the field of computer vision. The edges of the image characterize the boundaries that distinguish it from other objects and are therefore a very important problem in image processing. Accurate Image Edge Detection can significantly reduce the amount of data and filter out useless information while retaining important structural properties in the image. Since edge detection is at the forefront of image processing for object detection, it is very important to have a good understanding of edge detection algorithms. In this study, applying canny edge detection using python and OpenCV and also compared with other image processing methods. The result is that Canny edge detection has a better performance compared to other algorithms such as LoG (Laplacian of Gaussian), Robert, Prewitt and Sobel.