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done with the route planner algorithm running on Smart Park App. Refer to the following Fig. where the destination point is indicated via a green ball with a star symbol. The pink circles are nothing but available parking places near the destination point, and the blue arrows indicate the connecting roads
for these parking places. The route planner algorithm with Google maps generates the distance matrix to identify the nearest parking place from the destination. If you refer to the Fig., Parking Places C and E seem to be closer parking places from the destination. Although Parking Place C seems the nearest one, there is no direct route available to reach it from the destination. However, there is a direct road available to reach to Parking Place E and hence the Smart Park App recommends the nearest parking place to the user as Parking Place E. Now, the user may connect to Parking Place E server and enquire about parking availability at any given point and go there if the parking lot is available. If no parking is available at Parking Place E, then the user can go to the second nearest Parking Place C as per the availability of the parking.
Further, to ensure that the parking status information from all the parking place servers should be available at the central system through a dedicated dashboard for ease and convenience, another desktop machine running with Data Analytics software is connected with all the parking place servers in a network over the Internet. The Data Analytics software ensures the availability of the parking status information from all the parking place
Dr Dipak Gade || 71
servers at any given time and runs various analytics algorithms on the collected parking status data to find out the following:
• Average parking time, peak parking hours, least parking time and maximum parking time
• Seasonal variations in parking, busiest parking places and least utilized parking places
• Average parking availability at any given time, parking data trends, and parking data correlation with locations
The above-listed information gives enough insights with respect to parking-related requirements, parking capacity of specified geography location, need for additional parking places, underutilized parking places, etc.
To ensure having a cost-effective solution in place, I made use of open-source software technologies, tools and databases. For a hardware platform, the available desktop machines operating on the Windows Operating System were used. I used online available images of parking places as well as simulated parking data for testing the overall functionality of Smart Park App, Data Analytics software and parking place server software. The developed software application was verified with the stated research objectives, and I found that most of the functional requirements were easily getting fulfilled.
The prototype of Smart Park software is found highly successful during laboratory- level testing. I am now planning to implement a full-fledged smart parking solution based on the Smart Park software. I am sure that people travelling from one city to another can find a Smart Park solution highly useful to find out nearby parking places easily and conveniently.
Finally, I would like to end this story with a famous quote from James Baldwin “Not everything that is faced can be changed, but nothing can be changed until it is faced”.
    






















































































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