The overarching goal of this proposal is to develop an artificially intelligent alcohol sensor that is wearable, non- invasive, smart, and aesthetic.
The aim, in Phase I, is to design and develop the alcohol sensor based on metal (i.e., Cobalt) functionalized Titanium nanotubes (TiNT) to detect, monitor, and display blood alcohol levels in real-time using microcontrollers-based wrist-band like devices. At the core of our innovation, we have Cobalt- functionalized TiNT sensors which are capable of detecting alcohol exposure from the skin in 1ppm level that can be tuned down to 1ppb level as well (i.e., sensitivity of the sensor is tunable). The control unit of our system is reusable, sensors are replaceable, the microcontrollers are equipped with a micro-SD card for personal-data storage, and the proposed unit has a built-in wireless system for data transmission. This proposal also aims, in Phase II, to create an integrated artificially intelligent (AI) network that will have the capabilities of (a) translating the real-time data into a pre-cautious safety signals that will communicate with the personal vehicle safety features through a wireless signal (i.e., Bluetooth), and (c) adaptively taking unattended decisions-on-demand (DoD) through machine learning when the driver is heavily intoxicated. 1
Breath-analyzers within the law enforcement settings alone cannot tackle the problems associated with alcohol consumptions and abuse. Recently developed wearable alcohol sensor technologies mostly rely on wet-electrochemical environments around the skin. Therefore, we propose to develop wearable alcohol sensor using titania nanotube which will be dry, non- invasive, artificially intelligent, and aesthetic. We also aim to integrate these sensors through machine learning for taking unattended decisions on demand under influence.
