ABSTRACT:
This paper introduces a novel algorithm that increases the efficiency of the current cloud-based smart-parking system and develops a network architecture based on the Internet-of-Things technology. This paper proposed a system that helps users automatically find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance and the total number of free places in each car park.
This cost will be used to offer a solution of finding an available parking space upon a request by the user and a solution of suggesting a new car park if the current car park is full. The simulation results show that the algorithm helps improve the probability of successful parking and minimizes the user waiting time. We also successfully implemented the proposed system in the real world.
PROPOSED ARCHITECTURE:
A. System Overview:
The system is derived from the idea of IoT. The system uses the WSN consisting of RFID technology to monitor car parks. An RFID reader counts the percentage of free parking spaces in each car park. The use of RFID facilitates implementation of a large-scale system at low cost. The system provides a mechanism to prevent disputes in the car park and helps minimize wasted time in looking for a parking space.
Architecture of the Proposed System.
B. System Architecture:
Elements in the system
- Cloud-Based Server: This is a Web entity that stores the resource information provided by local units located at each car park.
- Local Unit: This unit is located in each car park and stores the information of each parking space.
- Software Client: This is an application software system. Running on Android operating system, the users will install it on their smartphones and use it to reserve parking spaces.
C. Network Architecture:
In general, we will use the term ‘‘user’’ when referring to the driver or vehicle and the term ‘‘resources’’ when referring to the parking spaces.
Parking Network We use the car park network (CPN) architecture infrastructure/backbone. The architecture is, where the dashed lines indicate wireless link and the solid lines indicates wired link.
Parking Network.
Constructing the Neighbor Table of nodes We use a function named F(α,β) to calculate the cost between the nodes in the network. F(α,β) is a function that depends on the distance between two nodes and the number of free parking spaces in the destination node.
ALGORITHM AND MATHEMATICAL MODEL:
A. Algorithm:
We propose an algorithm to describe the operation of the system.
System Operations
When a user wants to find a parking slot, he must login to our system. After successful login, a request message is sent to search for a free parking slot. Then, the system will send back a response message containing the information, including the car park address and the directions to reach it.
Calculating the Total Free Parking Spaces and Updating the Neighbor Table
In our proposed system, we use RFID technology to calculate the percentage of total free parking spaces in each car park. In each car park, an RFID reader is installed at the entrance. We use a variable named ‘‘Count’’ to calculate the total number of vehicles in the car park.
B. Mathematical Models:
We build the mathematical models of our proposed system based on the results. We create a parking planning strategy. We let P denote the set of all vehicles with parking queries in the queue.
C. Queue Models:
We modeled the system into a service queue. It includes all users entering each car park. The entering process at each node is considered to be a first-in first out (FIFO) queue and a Markov process.
Service Queue.
SIMULATION:
A. Simulations:
Setup
To evaluate the performance of the processes, we simulated a network deployment, including the car park architecture mentioned above.
A five-node Network.
B. Results And Evaluation:
To evaluate the performance of the proposed system, we determined the parameter for system performance as the cost in terms of user time in the system. The cost to the user is the time that the user spends in the parking system for service.
IMPLEMENTATION:
A. Software System:
We designed a software client that runs on a smartphone based on the Android platform, which was built from the ground up to enable developers to create compelling mobile applications that take full advantage of all that a handset can offer.
B. Elements:
The implementation of the system elements, including RFID tags, the RFID reader, the RFID antenna, Arduino Uno R3, Arduino Ethernet Shield, Screen and Cloud-based Server system.
CONCLUSION:
This study has proposed a parking system that improves performance by reducing the number of users that fail to find a parking space and minimizes the costs of moving to the parking space. Our proposed architecture and system has been successfully simulated and implemented in a real situation.
The results show that our algorithm significantly reduces the average waiting time of users for parking. Our results closely agree with those of our proposed mathematical models. The simulation of our system achieved the optimal solution when most of the vehicles successfully found a free parking space.
The average waiting time of each car park for service becomes minimal, and the total time of each vehicle in each car park is reduced. In our future study, we will consider the security aspects of our system as well as implement our proposed system in large scales in the real world.
Source: Feng Chia University
Authors: Thanh Nam Pham | Ming-fong Tsai | Duc Binh Nguyen | Chyi-ren Dow | Der-jiunn Deng
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