Smoke Recognition in Smart Environment Through IoT Air Quality Sensor Data and Multivariate Logistic Regression

Author:- S. M. Mohidul Islam and Kamrul Hasan Talukder
Category:- Conference; Year:- 2023
Discipline:- Chemistry Discipline
School:- Science, Engineering & Technology School

Abstract

Automatic classification and monitoring the human activity using sensors is a decisive technology for Ambient Assisted Living (AAL). Early recognition approaches involved in manually outlining expert guidelines for the sensor values. Recently, machine learning-based human activity recognition methodologies have fascinated a lot of attention. Some human activities produce smoke in the environment which is danger in most situations. The objective of the proposed work is to detect the smoke making activities that are taken out inside any smart environment based on the data assimilated by a set of environmental sensors inspecting the constituents of the air. We have used lower and upper bound based capping technique to handle the outliers and then we have standardized the contents of the features using standard scaling. These preprocessing makes the sensor data more apposite for selected logistic regression algorithm. The outcome of the proposed method shows better result than many state-of-the-art methods.

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