Smart Parking System Using Internet of Things
davanizadeh, mahmood (2024)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024060219705
https://urn.fi/URN:NBN:fi:amk-2024060219705
Tiivistelmä
This thesis develops a comprehensive software system for smart parking management aimed at effectively assigning parking spaces and providing intelligent directions to users. The system was designed to integrate various software technologies, including backend, frontend, and DevOps, to facilitate real-time data gathering and user-friendly interfaces, thereby creating an all-encompassing parking management solution. Through the deployment of sensors and IoT devices in parking lots, the system collected crucial information on parking spot availability, vehicle occupancy, and traffic movement, ensuring an up-to-date and accurate overview of parking conditions.
The success of the implementation is apparent in several significant areas. Firstly, the software significantly reduces the time drivers spend searching for parking spots. This reduction in search time will directly translate to decreased traffic congestion and lower carbon emissions, contributing to environmental sustainability and improved urban mobility. Secondly, by streamlining the reservation process, the system enhances user convenience and satisfaction, offering a seamless and efficient parking experience.
Moreover, the system's capability to adapt to changing parking demands ensures optimal use of available resources. This adaptability not only maximizes the efficiency of parking space utilization but also boosts revenue generation for parking operators by dynamically adjusting to varying occupancy levels and user preferences. Additionally, the extensive data collected by the software provides valuable insights into parking patterns and consumer behavior. Such data-driven insights are instrumental for city planners and policymakers, enabling them to make well-informed decisions regarding urban development, traffic management, and infrastructure investments.
The success of the implementation is apparent in several significant areas. Firstly, the software significantly reduces the time drivers spend searching for parking spots. This reduction in search time will directly translate to decreased traffic congestion and lower carbon emissions, contributing to environmental sustainability and improved urban mobility. Secondly, by streamlining the reservation process, the system enhances user convenience and satisfaction, offering a seamless and efficient parking experience.
Moreover, the system's capability to adapt to changing parking demands ensures optimal use of available resources. This adaptability not only maximizes the efficiency of parking space utilization but also boosts revenue generation for parking operators by dynamically adjusting to varying occupancy levels and user preferences. Additionally, the extensive data collected by the software provides valuable insights into parking patterns and consumer behavior. Such data-driven insights are instrumental for city planners and policymakers, enabling them to make well-informed decisions regarding urban development, traffic management, and infrastructure investments.