Browsing Department of Computer Science and Engineering (CSE) by Subject "Raspberry Pi"
Now showing items 1-6 of 6
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Development of electronic voting machine with the inclusion of near field communication ID cards, biometric fingerprint sensor and POS printer
(BRAC University, 12/28/2014)The basis of this project is to create an electronic voting machine that will help to eradicate defrauding of the manual voting systems and prior versions of electronic voting. The thesis looks into and proposes a system ... -
Espionage: a voice guided surveillance robot with DTMF control and web based control
(© 2015 Institute of Electrical and Electronics Engineers Inc., 2015-06)This paper proposes a research that was taken up in the wake of increasing awareness of security crisis all over the world. An effort has been made to briefly demonstrate the proof of concept of using a mobile surveillance ... -
Intelligent intrusion prevention system for households based on system-on-chip computer
(© 2016 IEEE, 2016-05)Over the course of the last few decades, security systems have undergone radical overhauls and have transitioned into such sophisticated devices that some even completely shun any form of human interventions. In spite of ... -
An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning
(Brac University, 2021-06)In late 2019, a novel Coronavirus broke out from China, which has dispersed all over the globe and has taken away countless lives. Despite the fact that every person is at risk of getting infected with the virus, older ... -
Online smart security with remote monitoring facilities
(BRAC University, 4/18/2017)Where home security problem has integrated to daily life, there technology has already become an efficient solution for this issue, and this project has come up with all possible technical solution to home security issue. ... -
Predicting brain age from EEG signals using machine learning and neural network
(Brac University, 2022-05)The objective of this study was to develop a technique for calculating the ages of people’s brains by analyzing EEG data signals and using machine learning algorithms on a Raspberry Pi. We employed many machine learning ...