Big Data Based Points of Interest Analysis


Duration: 5 months
Industry: Marketing and Advertising
Location: USA


The client is an innovative advertising company delivering cutting-edge technology solutions for marketing and advertising in malls and supermarkets across the US


The customer created an alerting system for sellers which was based on the developed algorithm, and it functioned to inform that a potential client is approaching the store location. Aterise was to create an algorithm that detects users’ movement around the mall and recognizes typical routes and points of interest


The core task for Aterise team was to develop a neural network algorithm that would analyze the collected Big Data and transform it into human-readable actionable insights to increase the quality of customer service at hypermarkets and malls

From the user application standpoint, at this stage Aterise team was required to create a fully functioning MVP relying on the provided mockup by the customer. The prototype of the system contained 3 potential user roles: the administrator, the user, and the business user. Besides the opportunity to upload the examples of AI algorithms to the website, it was necessary to implement the data verification system of the algorithm


Aterise developed a functional frontend system with an opportunity for further backend integration based on the customer’s mockup. As a result, we delivered software that predicts people’s movements along the area with beacons placed around. The software uses data taken from the accelerometer and a user phone’s compass with the software set up on the phone

  • Aterise not only turned the customer’s idea into reality but also managed to cut down their expenses for front-end and back-end integration
  • We managed to train the algorithm on the basis of the data received from the user’s device (cell phone). That resulted in the ability to predict user movements with an accuracy of 3 meters
  • We optimized the data, trained the neural network algorithm, and achieved a prediction accuracy of up to 97%
  • Finally, Aterise conducted a test check of the solution beginning from the simplest neural network algorithms up to the most complex algorithms. Thus, we made the system operate accurately by creating an ideal algorithm

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