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SenseSafe - Crowd Sensing & Advertising Response - Use Case

Asia Pacific’s largest network of in-vehicle screens wanted a platform that would enable different brands to connect with commuters whether they were using public transportation, taxis or ride-sharing cars.


  • The company needed to understand commuters’ preferences so that it could respond accordingly.
  • It was important to measure and understand passengers’ reactions to various media as well as assess responses to advertising and marketing.
  • It needed to sense the mood of large crowds using public transportation in order to detect any malicious intent and to improve on the commuter experience


  • SenseSafe’s algorithm is designed to accurately measure crowd emotions. Responses to the content of entertainment, advertising and campaigns are continuously tested inside the vehicle. This enables marketers to determine which advertisements are most effective and optimize content for maximum impact on consumers.
  • The platform is extremely effective when it comes to measuring the engagement of commuters with interactive displays that both “push” information and gather data on customer preferences and satisfaction.
  • The platform is non-intrusive and anonymous, which makes it an ideal touchpoint for surveying and analyzing commuter messaging and omni-channel onboarding data. This provides analytics as well as insights for advertisers. Emotion analysis increases survey feedback efficiency at least three-fold by reducing survey time from 10 minutes to 3 minutes.
  • The system’s emotion sensing AI data offers deep insights into consumer behavior by enabling access to unfiltered and unbiased viewer responses. It identifies the key emotional moments that have the most intense engagement and provides reliable data for analytics covering topics such as brand recall, purchase intent and sales lift.


  • Our emotion analytics increase the relevance to passengers of targeted content which enhances their ride experience while increasing the impact of campaigns by brand owners. At the same time, it provides insights into campaign effectiveness and consumer preferences.
  • The system is able to identify those key segments within an advertisement that are most effective in appealing to an audience, as well as which campaign engages the audiences the most.
  • The system provides private drivers-for-hire with a new source of revenue by offering credible evidence of passenger engagement with interactive content on screens attached to passenger seats.
  • The system also identifies commuter preferences reflected by emotions such as frustrations or delight. This is critical in understanding commuter trends as well as the effects that changes in location, time of day and day of the week have on commuter emotions. The system can also be trained to detect potential malicious intent.
  • We have been able to leverage our experience working with one of the world’s largest consumer goods companies, by comparing the accuracy of our emotion data analysis with the consumer engagement tested during their major advertising campaigns.