Towards Contactless Elevators with TinyML using CNN-based Person Detection and Keyword Spotting
It addresses the need for cost-effective, safe, and efficient elevator systems to reduce physical contact, particularly relevant for public health in multi-floor buildings, though it is incremental as it builds on existing tinyML and CNN methods.
This study tackled the problem of contactless elevator operation by developing a tinyML-based system using CNN-based person detection and keyword spotting, achieving 83.34% detection accuracy, 80.5% keyword spotting efficacy, and under 5 seconds latency.
This study presents a proof of concept for a contactless elevator operation system aimed at minimizing human intervention while enhancing safety, intelligence, and efficiency. A microcontroller-based edge device executing tiny Machine Learning (tinyML) inferences is developed for elevator operation. Using person detection and keyword spotting algorithms, the system offers cost-effective and robust units requiring minimal infrastructural changes. The design incorporates preprocessing steps and quantized convolutional neural networks in a multitenant framework to optimize accuracy and response time. Results show a person detection accuracy of 83.34% and keyword spotting efficacy of 80.5%, with an overall latency under 5 seconds, indicating effectiveness in real-world scenarios. Unlike current high-cost and inconsistent contactless technologies, this system leverages tinyML to provide a cost-effective, reliable, and scalable solution, enhancing user safety and operational efficiency without significant infrastructural changes. The study highlights promising results, though further exploration is needed for scalability and integration with existing systems. The demonstrated energy efficiency, simplicity, and safety benefits suggest that tinyML adoption could revolutionize elevator systems, serving as a model for future technological advancements. This technology could significantly impact public health and convenience in multi-floor buildings by reducing physical contact and improving operational efficiency, particularly relevant in the context of pandemics or hygiene concerns.