ABSTRACT
The need to sense and track in real time through sustainable and multifunctional labels is exacerbated by the COVID-19 pandemic, where the simultaneous measurement of body temperature and the fast tracking of people is required. One of the big challenges is to develop effective low-cost systems that can promote healthcare provision everywhere and for that, smarter and personalized Internet of things (IoT) devices are a pathway in large exploration, toward cost reduction and sustainability. Using the concept of color-multiplexed quick response (QR) codes, customized smart labels formed by two independent layers and smart location patterns provide simultaneous tracking and multiple synchronous temperature reading with maximum sensitivity values of 8.5% K-1 in the physiological temperature range, overwhelming the state-of-the-art optical sensor for healthcare services provided electronically via the internet (eHealth) and mobile sensors (mHealth).
ABSTRACT
Nowadays, the Internet of Things (IoT) has an astonishingly societal impact in which healthcare services stand out. Amplified by the COVID-19 pandemic scenario, challenges include the development of authenticatable smart IoT devices with the ability to simultaneously track people and sense in real-time human body temperature aiming to infer a health condition in a contactless and remote way through user-friendly equipment such as a smartphone. Univocal smart labels based on quick response (QR) codes were designed and printed on medical substrates (protective masks and adhesive) using flexible organic-inorganic luminescent inks. Luminescence thermometry and physically unclonable functions (PUFs) are simultaneously combined allowing non-contact temperature detection, identification, and connection with the IoT environment through a smartphone. This is an intriguing example where luminescent inks based on organic-inorganic hybrids modified by lanthanide ions are used to fabricate a smart label that can sense temperature with remarkable figures of merit, including maximum thermal sensitivity of Sr=1.46 %K-1 and temperature uncertainty of dT=0.2 K, and accuracy, precision, and recall of 96.2%, 98.9%, and 85.7%, respectively. The methodology proposed is feasibly applied for the univocal identification and mobile optical temperature monitoring of individuals, allowing the control of the access to restricted areas and the information transfer to medical entities for post medical evaluation towards a new generation of mobile-assisted eHealth (mHealth). Author