@inproceedings{8b92041ea3294ac7921e7155fa8e2807,
title = "Application Specific Instrumentation (ASIN): A Bio-inspired Paradigm to Instrumentation by fusing sensors and AI (SensAI)",
abstract = "Nature has, consistently, been an inspiration for scientists and engineers. In this paper, I present a novel paradigm to instrumentation where we co-develop the sensor and machine learning algorithms to bolster the sensor. This is what happens in most species of animals through generations of coevolution. Such sensor and AI (SensAI) empowered instruments are expected to be inexpensive as well as more efficient (in the applications for which they have been developed). In addition to presenting the modus operandi of this application specific instrumentation (ASIN) paradigm this paper shall also, briefly, discuss some of the successful demonstrations of the ASIN paradigm.",
keywords = "Artificial Intelligence, Bio-inspired, Bio-inspired Architecture, Instrumentation, Machine Learning, Sensors",
author = "Mishra, {Amit Kumar}",
note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 1st International Conference on Data Science, Machine Learning and Artificial Intelligence, DSMLAI 2021 ; Conference date: 09-08-2021 Through 12-08-2021",
year = "2022",
month = jan,
day = "13",
doi = "10.1145/3484824.3484921",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "1--6",
editor = "Jat, {Dharm Singh} and Colin Stanley and Jose Quenum and Nilanjan Dey and Arpit Jain",
booktitle = "DSMLAI '21",
address = "United States of America",
}