Investigating an AI-Based Parking Management System in Urban Areas of Developing Countries

Abstract: While it is true that parking systems constitute a basis of movement for people and goods, a number of challenges accrue thereof, such as congestion. Traffic congestion remains one of the critical challenges to urban mobility, resulting in implications for environmental pollution, the economy, and quality life for millions of people worldwide. In developing countries, city traffic is growing at an unprecedented rate. Because of the quick rate of urbanization, the exponential increase in vehicles is leading to congestion, pollution, and an increased rate of accidents.

Rajsahi, which is located in the northern part of Bangladesh, faces severe congestion in traffic flow similar to other cities in Bangladesh. Primarily, it is caused by on-street parking, which acts as the reason for continuous parking problems in this city since decades, particularly in the commercial areas. Thus, this dire situation requires continuous improvement in the existing parking system by incorporating technological solutions that reduce vehicular congestion, pollution, and parking problems within the city.

The paper brings into discussion the prevailing difficulties in parking that occur today in Rajshahi and signals the demand for a newer, friendlier system that regulates and optimizes the use of parking space. In this regard, a system is proposed which will offer a holistic solution for finding the most suitable parking space, considering spatial and temporal availability of parking spots, and the connectivity between parking areas and destinations. The development of an appropriate parking space allocation system based on OpenCV is called for by the conditions at hand. While investments in advanced management systems of parking are widely supported, there are various opinions regarding the adoption of different strategies aimed at improving the quality of transport systems, especially due to the lack of appropriate hardware settings.