Abstract

Abstract – The project titled PARKING AREA DETECTION using IoT aims to alleviate traffic congestion on roads, in multi-story buildings, and at malls caused by a lack of available parking spaces. It provides users with information about the nearest empty parking slot based on their location. Our goal is to optimize the use of parking facilities by tracking vacant slots and assigning them to users. This smart parking system can lead to a reliable, secure, and efficient management solution. Recently, the concept of smart cities has gained significant traction, and with the advancement of the Internet of Things, the vision of a smart city is becoming more attainable. Ongoing efforts in the IoT sector are focused on enhancing the productivity and reliability of urban infrastructure. Issues like traffic congestion, insufficient parking options, and road safety are being tackled through IoT solutions. The proposed Smart Parking system includes an on-site IoT module that monitors and indicates the availability of each parking space. Additionally, a mobile application is available for users to check parking availability and reserve a slot. The paper also outlines a high-level overview of the system architecture and concludes with a use case that demonstrates the effectiveness of the proposed model. This survey paper details the development of an advanced machine learning-based attendance system integrated with a MySQL database. The proposed system leverages facial recognition technology to facilitate efficient user registration and attendance management, specifically within educational settings. By employing Convolutional Neural Networks (CNN) and Multi-task Cascaded Convolutional Networks (MTCNN) integrated through the Keras deep learning framework, the system aims to significantly improve accuracy, scalability, and real-time operability. The paper discusses the motivation, design architecture, implementation, and potential impacts of the system, alongside an evaluation of traditional attendance methods and their limitations.