Occupancy Detection in Room Using Sensor Data

With the advent of Internet of Thing (IoT), and ubiquitous data collected every moment by either portable (smart phone) or fixed (sensor) devices, it is important to gain insights and meaningful information from the sensor data in context-aware computing environments. Many researches have been implemented by scientists in different fields, to analyze such data for the purpose of security, energy efficiency, building reliability and smart environments. One study, that many researchers are interested in, is to utilize Machine Learning techniques for occupancy detection where the aforementioned sensors gather information about the environment. This paper provides a solution to detect occupancy using sensor data by using and testing several variables. Additionally we show the analysis performed over the gathered data using Machine Learning and pattern recognition mechanisms is possible to determine the occupancy of indoor environments. Seven famous algorithms in Machine Learning, namely as Decision Tree, Random Forest, Gradient Boosting Machine, Logistic Regression, Naive Bayes, Kernelized SVM and K-Nearest Neighbors are tested and compared in this study.

READ FULL TEXT
research
06/18/2021

Performance Evaluation of Classification Models for Household Income, Consumption and Expenditure Data Set

Food security is more prominent on the policy agenda today than it has b...
research
07/27/2022

Blockchain associated machine learning and IoT based hypoglycemia detection system with auto-injection feature

Hypoglycemia is an unpleasant phenomenon caused by low blood glucose. Th...
research
10/27/2020

Decision Tree and Random Forest Implementations for Fast Filtering of Sensor Data

With increasing capabilities of energy efficient systems, computational ...
research
10/22/2019

A Context-aware Framework for Detecting Sensor-based Threats on Smart Devices

Sensors (e.g., light, gyroscope, accelerometer) and sensing-enabled appl...
research
06/09/2022

Human Activity Recognition from Knee Angle Using Machine Learning Techniques

Human Activity Recognition (HAR) is a crucial technology for many applic...
research
04/10/2022

Optimization of IoT-Enabled Physical Location Monitoring Using DT and VAR

This study shows an enhancement of IoT that gets sensor data and perform...
research
06/24/2019

Hybrid-Learning approach toward situation recognition and handling

The success of smart environments largely depends on their smartness of ...

Please sign up or login with your details

Forgot password? Click here to reset