نشریه پژوهش های نوین در شهر هوشمند
سال دوم شماره 2 (زمستان 1402)

Nowadays, with the increasing use of various discrete data acquisition methods such as drones and digital cameras, image processing has found wide application. However, video data alone cannot play a significant role in urban management decisions until they are transformed into statistical sequences. In this paper, a system for detecting the number of cars per unit length and time is presented. In this method, video data is converted into statistical sequences of traffic indicators. First, the images corresponding to each frame are modeled into background images based on the Gaussian mixture model, which are resistant to lighting changes. This operation is performed on a large number of frames to create a learned background image. In traditional traffic image processing methods, modeling the background image was not considered, and conversely, in the proposed method, this model is used to detect moving objects. Then, by comparing each input main frame with the learned background image, moving cars are detected. The information on the number of cars per unit length and time, which corresponds to the concepts of traffic volume and density, is used to estimate traffic flow. Based on the simulations performed and the comparison of the obtained results with other results from different studies, the high performance of the proposed method in car detection and accurate counting, considering proper background image training, is demonstrated. Moreover, this method can be used for processing low-quality images.

The world's population is growing at an unprecedented rate, and cities are at the forefront of this trend. Unfortunately, many cities, especially in developing countries, are facing significant crises. However, there is a solution that can transform urban life effectively and efficiently: smart cities. By providing residents with quick, easy, and affordable access to essential services, smart cities can improve the quality of life for millions of people. Governments around the world are already investing in this promising new approach to urban development, and you can join the movement towards a smarter, more sustainable future for our cities. Let's work together to create a better world for ourselves and future generations. The city of Karaj has experienced rapid growth in population and structure over the last few decades. As a result, it's crucial to understand the significance of smartening cities and providing high-quality services to citizens. The present research has identified the most important components that contribute to the smartness of cities, including technology, quality of environment and life, environment, transportation, economy, governance, social and human capital. The findings reveal that the city of Karaj has an average status for most of the smart city indicators. However, with better education, culture, and infrastructure, these indicators can be improved significantly. Therefore, it's essential to prioritize the development of these factors to make Karaj a smarter city that provides the best quality services to its citizens.

Advanced drug delivery systems designed on the basis of controlled drug release through oral polymeric films have demonstrated significant progress in the medical field. These systems operate in a way that the drug is placed within a polymeric matrix, and upon consumption, the polymeric film gradually swells due to solvent evaporation, subsequently leading to the controlled release of the drug under the influence of physical stimuli. The release rate of the drug can be controlled by adjusting the polymer structure and through formulation changes. Precise control of the swelling degree of polymeric films is of great importance as one of the key components for the effectiveness of delivery systems; insufficient swelling can cause incomplete drug release, while excessive swelling may lead to rapid degradation of the film structure and uncontrollable drug release in the patient's mouth. Therefore, engineering and controlling the swelling rate in the drug release process is considered a critical issue and is given special attention.

This paper explores the applications of augmented reality (AR) and virtual reality (VR) in the construction decoration industry. With advancements in virtual technologies, these tools have become powerful instruments for improving the processes of design, visualization, and execution of construction decoration projects. The article begins by examining the fundamental concepts and principles of augmented reality and virtual reality. It then presents various applications of these technologies in the field of construction decoration, including interior design, material and equipment selection, 3D modeling, and augmented reality visualization in physical environments. Furthermore, the advantages and challenges of utilizing these technologies in the construction decoration industry are discussed. Finally, suggestions are provided for optimizing the use of augmented reality and virtual reality in construction decoration to ensure they serve as effective and efficient tools in this industry. Drawing on research studies, case studies, and practical examples of construction decoration projects, this article introduces innovative and practical methods for leveraging augmented reality and virtual reality in the construction decoration industry. It is aimed at audiences interested in the latest advancements in technology and design in the construction decoration field and can serve as a suitable starting point for further research and implementation of practical projects in this area.

In this paper, we present a comprehensive plan for transforming Tehran into a smart city by leveraging machine learning techniques while prioritizing sustainable development, balanced development, and resilience. The plan outlines the key components, including data collection, machine learning algorithms, and initiatives for sustainable and equitable development. We discuss the hardware and software requirements for implementing machine learning algorithms in a smart city context, along with examples of input and output data for various applications. Additionally, we highlight the importance of monitoring, evaluation, and iteration to ensure the effectiveness of smart city initiatives. By following this plan, Tehran can harness the power of machine learning to address urban challenges, improve quality of life, and foster long-term prosperity for its residents.

This paper investigates the role of artificial intelligence technology and cognitive science in enhancing the accuracy and efficiency of physiotherapy. A cognitive science approach combined with artificial intelligence is utilized to identify and record movements of individuals with disabilities and improve the interactive environment. By improving the system's accuracy to 99% in identifying simple movements and 92% in complex movements, significant improvements in the physiotherapy process have been achieved. The precise coordination between camera and video projector modules enables the enhancement of a multidimensional movement experience and provides physiotherapists with accurate and up-to-date information regarding the movements of individuals with disabilities. The paper concludes with suggestions for further improvements in motion detection technology and educational insights for physiotherapists.