15 November Machine Learning in Shopping Centers November 15, 2018 By Gina Wurms retail |WiFi|, |Machine Learning| 0 Applying machine learning to shopping centers allows a precise forecast of the number of visitors that can be expected. On that basis, advertising spaces can be priced accurately. At a glance Application of machine learning in shopping centers Correlation of weather data and number of visitors Automatic determination of prices for advertising spaces Problem Definition The number of visitors in shopping centers varies all the time. At times when there are a lot of visitors, advertisements, for example on advertising displays, are more likely to be successful as they are seen by more people. However, the operators of shopping centers are not able to predict the number of visitors very well. As a result, an adequate and fair pricing of advertising spaces can’t be achieved. Solution Implementing a machine learning tool solves this problem. Machine learning enables a reliable forecast of the number of visitors and thus appropriate pricing of advertising spaces. A factor that affects the number of visitors significantly is the weather. When the weather is bad and it’s raining, there are usually more people visiting the shopping center. However, with this information alone the human brain can forecast the number of visitors very roughly at best. Machine learning on the other hand recognizes complete and precise correlation between the weather and the number of visitors and can make very accurate forecasts on that basis. With the knowledge of current weather data, the system can predict the number of visitors at a certain time accurately. Subsequently, adequate prices for advertising spaces can be determined automatically. Technical Implementation The available data sets are essential for any machine learning system. The quality and quantity of data determines the accuracy of the machine learning results. In this use case, the number of visitors can be measured using indoor positioning with Wi-Fi while the weather-related data can be collected using infsoft Sensor Tags. The data sets are imported into the infsoft Machine Learning Tool and given to an algorithm. With the historic data, the system gains experience and is trained. The gathered experience enables the model to make precise forecasts of how many people will visit the shopping center when it is given input of current weather data. The predicted number of visitors is then provided to infsoft Analytics and the Automation Engine. It is previously defined in the Automation Engine, which price for advertising spaces should be set when the forecasted number of visitors is located in a certain range. It is then possible to send an automated e-mail containing the price for an advertising space to the responsible persons and the shop operators. Thanks to the increasing amount of weather and visitor data, machine learning can gather more experience and forecasts will get even more precise over time. Beside the weather other factors like school holidays or big events in the area may affect the number of visitors in a shopping center. Those data sets can also be defined in the system to obtain even better predictions. Use Case PDF for Download Get the white paper for free Great introduction to the topic of indoor positioning Download Related Articles Process Optimization of Cleaning Machines In this application, the position of cleaning machines is to be determined in real time. Read More Indoor Navigation and Persons Tracking in the Shopping Mall Visitors of a shopping centre can navigate to certain shops, restaurants etc. by Indoor Navigation and parents can locate their children with a bracelet so that they cannot get lost. Read More Management of Tugger Trains in Industrial Production Punctual production supply in production industries can be facilitated by tracking tugger trains and applying a machine learning system. Read More Investigation and Prevention of Criminal Offences at ATMs A tracking solution and machine learning can solve and prevent crimes at ATMs. Read More Utilization Analysis of Work Devices In industrial environments, a geobased logic engine makes a decisive contribution to ensuring efficient operating processes and the best possible utilization of workstations. Read More Mobile App and Indoor Navigation for Supermarkets An app for customers and an indoor navigation solution for supermarkets improve the shopping experience and increase customer engagement. Read More Comments are closed.