scholarly journals An Improved Machine Learning-Based Short Message Service Spam Detection System

2019 ◽  
Vol 11 (12) ◽  
pp. 40-48
Author(s):  
Odukoya Oluwatoyin ◽  
◽  
Akinyemi Bodunde ◽  
Gooding Titus ◽  
Aderounmu Ganiyu
Keyword(s):  
Machine Learning ◽  
Short Message Service ◽  
Detection System ◽  
Spam Detection ◽  
Short Message ◽  
Message Service

Robotic Monitoring of Human and Animal-Real Time and Automated

2020 ◽  
Vol 17 (2) ◽  
pp. 803-813
Author(s):  
Emy Haryatmi ◽  
Aris Tito Sugihharto ◽  
Maulana Mujahidin
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Short Message Service ◽  
Detection System ◽  
Ultrasonic Sensor ◽  
Short Message ◽  
Message Service ◽  
Sms Notification

Autonomous robotic monitoring of human and animal used to secure the house or the flat. This robot can move freely from one side to another side of the house or the flat. Accordingly, this robot is sending the vision to android smartphone in real time. Therefore, the owner of the house or the flat can see inside the house while they were not around. The objective of this research is to develop autonomous robotic to be able to monitor the area from the existing of human and animal and send the vision to android smartphone in real time. This research used four leg robotic as an autonomous robotic monitoring. Four leg robotic is equipped with camera which connected to router based on wireless connection, PIR and ultrasonic sensor and GSM module to send short message service (SMS) notification if PIR sensor detect some movement. The experiment used cat as an animal object. Experiment showed that this robot can follow the object, either a human or an animal, within range of 10–45 cm from robot in 12 seconds and send the vision to android smartphone in real-time. The SMS is received in 5 seconds after camera capture the object. This robotic cannot determine who is the object on the camera because it is not equipped with object detection system.

Gas Leakage Detection System (GLDS)

2013 ◽  
Vol 34 (1) ◽  
pp. 36-43
Author(s):  
Daudi S. Simbeye
Keyword(s):  
Short Message Service ◽  
Detection System ◽  
Liquid Crystal Display ◽  
Cost Effective ◽  
Short Message ◽  
Leakage Detection ◽  
Wireless Technology ◽  
Liquefied Petroleum Gas ◽  
Gas Leakage ◽  
Message Service

This paper mainly focuses on the detection of gas leakage and providing security when the user is around or away from home. The system is Short Message Service (SMS) based and uses wireless technology for providing security against gas leakage to users hence cost effective and more adaptable. The system comprises of sensors for detecting gas leakinterfaced to microcontroller that will give an alert to user whenever there is a gas leakage, display warning information by using Liquid Crystal Display (LCD), sending SMS to the user for notification wherever he/she might be and turning off electric power with the help of magnetic relay. This will enable the user to take precaution of explosion disaster whichmay result on Liquefied Petroleum Gas (LPG) cookers like loss of properties, injury or even death. GLDS provides ideal solution to gas leakage problems faced by home owners in daily life.

A Novel Approach to Detect Spam and Smishing SMS using Machine Learning Techniques

2020 ◽  
Vol 12 (1) ◽  
pp. 21-38 ◽  
Author(s):  
Ankit Kumar Jain ◽  
Sumit Kumar Yadav ◽  
Neelam Choudhary
Keyword(s):  
Machine Learning ◽  
Short Message Service ◽  
Machine Learning Techniques ◽  
Second Phase ◽  
Short Message ◽  
Novel Approach ◽  
Learning Techniques ◽  
Message Service ◽  
Novel Method ◽  
Two Phases

Smishing attack is generally performed by sending a fake short message service (SMS) that contains a link of the malicious webpage or application. Smishing messages are the subclass of spam SMS and these are more harmful compared to spam messages. There are various solutions available to detect the spam messages. However, no existing solution, filters the smishing message from the spam message. Therefore, this article presents a novel method to filter smishing message from spam message. The proposed approach is divided into two phases. The first phase filters the spam messages and ham messages. The second phase filters smishing messages from spam messages. The performance of the proposed method is evaluated on various machine learning classifiers using the dataset of ham and spam messages. The simulation results indicate that the proposed approach can detect spam messages with the accuracy of 94.9% and it can filter smishing messages with the accuracy of 96% on neural network classifier.

scholarly journals Design and Implementation of Electricity Fault Detection System Using Microcontroller Arduino UNO

2021 ◽  
Vol 3 (1) ◽  
pp. 76
Author(s):  
Chandra Adrian ◽  
Mia Galina
Keyword(s):  
Fault Detection ◽  
Short Message Service ◽  
Detection System ◽  
Warning System ◽  
Simulation Method ◽  
Short Message ◽  
High Pitch ◽  
Message Service ◽  
Arduino Uno ◽  
Electrical Installation

This paper concentrates of creating a fault detection system that detect both emergency fault and fault that need of maintenance with prototype of electrical installation that is done through manual simulation method. The prototype consists of the lamp as the load integrated with Arduino UNO as the microcontroller with GSM module and buzzer. The microcontroller will detect and deduce the type of the fault happened in the installation and will send the data of the fault through the GSM module. GSM module then transmits the data to the mobile phone and let the user aware of the fault. Also, there will be buzzer as the warning system by producing high pitch sound that signalizes the fault that need immediate handling or emergency. The data of both faults will be sent as Short Message Service (SMS) to the user. The SMS will give the user the type of fault either emergency or need of maintenance, happened in the installation.

(Un/Semi-)supervised SMS text message SPAM detection

2014 ◽  
Vol 21 (4) ◽  
pp. 553-567 ◽  
Author(s):  
CHRIS R. GIANNELLA ◽  
RANSOM WINDER ◽  
BRANDON WILSON
Keyword(s):  
Short Message Service ◽  
Text Message ◽  
Support Vector ◽  
Model Parameters ◽  
Spam Detection ◽  
Short Message ◽  
Classification Approach ◽  
Message Service ◽  
The Uk ◽  
Probabilistic Generative Model

AbstractWe address the problem of unsupervised and semi-supervised SMS (Short Message Service) text message SPAM detection. We develop a content-based Bayesian classification approach which is a modest extension of the technique discussed by Resnik and Hardisty in 2010. The approach assumes that the bodies of the SMS messages arise from a probabilistic generative model and estimates the model parameters by Gibbs sampling using an unlabeled, or partially labeled, SMS training message corpus. The approach classifies new SMS messages as SPAM or HAM (non-SPAM) by zero-thresholding their logit estimates. We tested the approach on a publicly available SMS corpora collected from the UK. Used in semi-supervised fashion, the approach clearly outperformed a competing algorithm, Semi-Boost. Used in unsupervised fashion, the approach outperformed a fully supervised classifier, an SVM (Support Vector Machine), when the number of training messages used by the SVM was small and performed comparably otherwise. We believe the approach works well and is a useful tool for SMS SPAM detection.

scholarly journals Real Time Sticky Bomb Detection System Based on Compass Device and Arduino Board

2017 ◽  
Vol 13 (1) ◽  
pp. 46-52
Author(s):  
Sameer Majeed ◽  
Noor Jumaa ◽  
Auday Mohamad
Keyword(s):  
Short Message Service ◽  
Detection System ◽  
Threshold Value ◽  
Short Message ◽  
Alarm Signal ◽  
The Earth ◽  
The People ◽  
Message Service ◽  
New Strategy ◽  
The Magnetic Field

This paper presents a new strategy of sticky bomb detection. The detection strategy is based on measuring the magnetic field around the targeted car using compass device. A compass measure the earth gravitation of the car as (x,y,z) coordination , a threshold value of magnetic fields around the targeted car are recorded. If a difference is detected with any (x,y,z) coordination, an alert SMS message is sent to the car's owner. The detection system presented in this paper has been implemented based on Arduino board. The alarm signal is a Short Message Service (SMS) through Global System for Mobile Communication (GSM) module. The proposed method can gives the people of unstable countries a chance to discover whether their cars have been trapped with an IED bomb or their car still safe.

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