Before the COVID-19 pandemic, major disruptions to the fast food industry hailed from the development of new technologies and the implementation of smarter systems. Post-pandemic, the physical dimension of human/computer interactions was elevated for the first time. In this smart solution, Wavicle’s team developed a novel method to improve the proximity required in human/computer interactions by developing a personalized smart application with gesture recognition through audio-video stream analytics.
Wavicle built an end-to-end data science embedded solution using data from all audio and video systems that leverage machine learning and advanced analytics capabilities to convert gestures to speech. This artificial intelligence (AI) powered solution is deployment-ready with American Sign Language detection. It can also customize gestures to speech recognition.
The platform relies on custom AI algorithms to identify gestures and is built on the perceptual computing user interface. A custom portal allows the recognized gestures to generate text and then generate audio output from the text model. Customer responses are captured, analyzed, and used to refine the AI model continuously, and reinforcement calibrations are under development.
Bringing together all customer gesture data in one platform with already available standard gestures for American Sign Language has allowed Wavicle’s team to develop personalization in the video analytics space. In turn, this drives customer engagement and safety during pandemics and increases physical dimensionality for customers.
Previously challenged by customer adaptations and technology latency due to the amount of analyzable data, companies were reluctant to explore the path of customized smart systems. The COVID-19 pandemic has forced businesses to adapt to newer technologies with consideration of the physical dimension. With AI-based smart tools, companies have new ways to engage customers in safer environments.
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