Finding a parking space in university is very difficult. Its even worse when you are in a hurry to attend a lecture. Wouldn't it be cool to know if a parking spot is free or not by just looking at your mobile app? this is how we landed on this idea. Finding a parking place is tiresome not just in universities but at any location(especially during holiday season). So by installing such a system in the parking lot, the user can view any available parking spaces in the mobile app.

What it does

Finds the parking spaces available in a particular parking Area. The sensors are located at every parking lot in the parking area and this information is sent to local. From local server the data is sent to IBM Cloudant(NOSQL Database) which is then redirected to the mobile app. Mobile app displays a list of available parking slots.

How we built it

  1. We are currently using different kind of sensors to know if car is parked or not - using arduino (which is a RF transmitter) and the local server has a RF receiver which receives all this data.
  2. We are running a python script on local server to send the data related to parking space to a NOSQL Cloudant Bluemix database.
  3. Public APIs are used to retrive this information from cloudant to the android mobile app.

Challenges we ran into

There were couple of challenges we faced:

  1. Finding appropriate Hardware was a challenge.
  2. The Bluemix platform was new to us, so we had to explore a lot. Especially working on Kinetise on IBM Bluemix and IBM cloudant was a great challenge and we finally had to consider an alternate plan.

Accomplishments that we're proud of

  1. End-to-End working model of the project.
  2. We were successfully able to communicate the sensor information to local Server.
  3. Integration of the IBM cloudant platform with the local server was one of the crucial achievements for our project.

What we learned

During the process of building the project, we learnt a lot about:

  1. Making different kinds of sensors work.
  2. Integrating multiple embedded devices to work concurrently.
  3. Using various devices like Rasberry Pi, arduino and Intel edison.
  4. IBM Bluemix platform - specific modules like Internet Of Things, IBM Cloudant, Kinetise for developing mobile application.

What's next for Park it Easy

  1. We want to make the project scalable.
  2. We want to improvise on the mobile application to display proper parking area design resemling the physical parking space for ease of use.
  3. Also we want to extend the functionality by including new devices like Alexa to make the experience more personalized for the user.
  4. We would also like to experiment and find a combination of sensors which can robustly identify the presence of a vehicle in the parking lot.
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