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Contribution to Book
AI thermometer for temperature screening: Demo abstract
SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems
  • Tomasz Lewicki, San Jose State University
  • Kaikai Liu, San Jose State University
Publication Date
11-16-2020
Document Type
Conference Proceeding
DOI
10.1145/3384419.3430433
Abstract

Thermal imaging provides a way of measuring the temperature of the subject in a contactless manner and is capable of taking the temperature of multiple subjects at a time. Due to COVID-19, there is a high demand for massive temperature screening for the crowded public in high traffic areas to detect any individual with a fever immediately. In this project, we propose to design an open-source AI thermometer for massive fever screening combining edge-based object detection solution and multi-modal sensor fusion. Different from many recent products that target commercialization and still not accessible for small business owners due to manufacturing delay and high cost, our open source solution can help developers build and assemble the AI thermometer like Lego blocks with off-the-shelf open computing board and components. We hope our solution can help small business owners to quickly utilize our AI technology at the lowest cost without long waiting.

Citation Information
Tomasz Lewicki and Kaikai Liu. "AI thermometer for temperature screening: Demo abstract" SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems (2020) p. 597 - 598
Available at: http://works.bepress.com/kaikai-liu/35/