An attempt on OOH analytics

Last year we have started this project. We didn't make to market. We have coded so much and put our effort on it. Thought of sharing this with the tech world. Most of these things can be done by any tech company. Someone looking a similar product and would like to play around and understand it, it's open to use. I moved everything to my personal account.

URL : https://54.70.173.122

Please bear with speed as its hosted on smaller AWS EC2 instance.

I can share source code after understanding your usage. Please feel free to contact me

Here is brief document about the hoarding oohlive application

• “ A web-based analytical application to measure the Billboards and popularity of the area with traffic density”.
• We tried building product to disrupt the Indian OOH advertising industry by bringing technology and real-time analytics hand to hand. We have successfully built our prototype using the real-time field data from selected places in Bengaluru, India. We used industry standard analytics and image process algorithms ( Google Analytics, Map and road APIs) to address real-time industry issues.

We successfully implemented logic to rank area popularity based on the number of google reviews stores( clothing, restaurants and big brands). We were able to categorize area type like educational, religions, resident, commercial based on google place data. We used our custom algorithms to rank the area considering traffic density .

This app helps to identify and rank the locality anywhere in the world. You can use this for any purpose for tagging the area. We wanted to use this for advertising industry especially outdoor hoarding boards.

Product demo URL : https://54.70.173.122

Please bear with speed as its hosted on a smaller AWS EC2 instance.

• I can share code after understanding your usage. Please feel free to contact me on LinkedIn
• Key Features
• Proof of concept for pricing each hoarding depending on the locality, traffic density and hoarding peak viewer-ship and physical dimensions.
• Identify current brand on the hoardings.
• Given brand listing all the hoarding with beautiful stats.
• Given area listing all active and current running campaigns.
• Competitions analysis.
• Monitoring the continuity and integrity of the billboard add on hoarding.
• Add analysis on the hoarding based on historic data on the hoarding over a period of time
• Connecting digital marketing with OOH adds ( Push notifications to the mobile devices based on profile, locality and the billboard ads around the device)
• Registered the major hoardings ( 300+) in Bangalore with built in house android application.

Technology Stack : Java, Angular 4, Spring Boot, MongoDB, Ionic, Google Maps’ Roads,

• Matrix , Direction, Road,& Geolocation APIs’, MongoDB.

Billboarded Register App

• Built using ionic 3 android application to capture the image of a billboard of hoarding and near the road connecting to it.
• Using this app we have registered more than 300+ billboards across major areas of Bangalore. It also captures lat and long of device, camera direction, area locality and sends data to the server to process so to identify the current brand, text on the image and traffic density with surrounding landmarks.
• Technology stack : Ionic 3, google angular library (AGM) Spring Boot, Java & J2EE , MongoDB
• API: Google road API, Place API, Image API, distance API

Instead of scrapping project, I thinking to share with someone who can take it further. These things can be easily implemented by a tech company. This is mainly for those who planning POC or just want to see if things can be done in this way.

I would be glad to help you walk you through code and application.

Thanks.