Browsing by Author "Khater, Ankit"

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A Comparative Analysis of SMS Spam Detection employing Machine Learning Methods
(Daffodil International University, 2022-04-13) Aliza, Humaira Yasmin; Nagary, Kazi Aahala; Ahmed, Eshtiak; Puspita, Kazi Mumtahina; Rimi, Khadiza Akter; Khater, Ankit; Faisal, Fahad
In recent times, the increment of mobile phone usage has resulted in a huge number of spam messages. Spammers continuously apply more and more new tricks that cause managing or preventing spam messages a challenging task. The aim of this study is to detect spam message to prevent different cybercrimes as spam messages have become a security threat nowadays. In this paper, studies on SMS spam problems to perform a better accuracy using several different techniques such as Support Vector Machine, K-Nearest Neighbor, Naïve Bayes, Random Forest, Logistic Regression and some more are performed. The result indicated that Support Vector Machine achieved the highest accuracy of 99%, indicating it might be useful as an effective machine learning system for future research.
A Promising Prediction of Diabetes Using a Deep Learning Approach
(Daffodil International University, 2022-01-06) Shakil, Rashiduzzaman; Akter, Bonna; Faisal, Fahad; Chowdhury, Tahmid Rashik; Roy, Tonmoy; Khater, Ankit
Diabetes is a collection of metabolic illnesses caused by a persistently high blood sugar level. If a reliable estimation is achievable, diabetes risk factors and severity can be reduced. In diabetes datasets, consistent and effective diabetes prediction is challenging because of the limited amount of labeled data and the abundance of outliers (or missing values).Alongside, the incidence rates of diabetes are rising alarmingly every year. Consequently, an early diagnosis of diabetes would be the most crucial step for receiving proper treatment. Hence, a deep learning-based reorganization system has gained popularity regarding disease identification. In this work, we used an updated Convolution Neural Network (CNN) model, modifying different hyperparameters and layer topologies on the UCI 130 USA Hospitals diabetes dataset. Additionally, five different types of optimizer, namely adaptive moment estimation (ADAM), ADAMAX, A more sustainable deal has been made using the Root Mean Square Propagation algorithm (RMSprop), stochastic gradient descent (SGD), and Nesterov accelerated adaptive moment (NADAM). Furthermore, improved accuracy of 99.98% was received by the ADAMAX optimizer.
An Automated Smart Embedded System on Fire Detection and Prevention for Ensuring Safety
(Scopus, 2021) Shamrat, F.M. Javed Mehedi; Khan, Aliza Ahmed; Sultana, Zakia; Imran, M. M.; Abdulla, Abdulla; Khater, Ankit
One of the biggest issues for architects, planners, and landowners is house combustion. Singular sensors have been used in the case of a fire for a long time, but they cannot quantify the volume of fire to warn emergency service units. To resolve this problem, this research aims to develop an intelligent smart fire warning system that detects fires utilizing connected sensors and alerts property owners, emergency services. The current model is divided into three modules: Smoke Detection Module (SDM), which is responsible for detecting smoke to prevent unwanted incidents; Notification Send Module (NSM), which is responsible for creating an alert service to alert the closest support center and user; and Emergency Alarm Module (EAM), which is responsible for handling the emergency alarm schedule when a fire arises. The results prove that the device worked well, and it should be remembered that our proposal can be integrated into any kind of setting, such as a house, workplace, ship, or industry.
Implementing E-Commerce Mobile and Web Application for Agricultural Products
(Daffodil International University, 2022-06-04) Chakraborty, Sovon; Shamrat, F. M. Javed Mehedi; Islam, Md Saidul; Kabir, Foysal; Khan, Ali Newaz; Khater, Ankit
In Bangladesh, the increased number of brokers has resulted in a price increase in the agricultural goods market. They acquire items from farmers at a discount and resell them to consumers at a premium. This deprives farmers, while customers pay an unreasonable price for basic essentials. This study aims to develop an e-commerce mobile and web application called 'e- Farmers' Hut' to facilitate direct producer-to-customer engagement. The application goal to maximize the advantages to producers and customers by eliminating middlemen's control. Both applications operate sequentially on the same database. Farmers and customers each have their profile to which they may submit the relevant information. Additionally, to optimize facilities use, also introduced an electronic payment method. Customers may see lists of available items that verified farmers have posted. The application has passed the testing process with expected outcomes. The technology has the ability to considerably simplify direct sales and purchases of items between farmers and consumers.
IoT Based Smart Automated Agriculture and Real Time Monitoring System
(Scopus, 2021) Shamrat, F. M. Javed Mehedi; Hossain, Alamin; Roy, Tonmoy; Khan, Md Ahasanul Adeeb; Khater, Ankit; Rahman, Md Tareq
In Bangladesh, agriculture is the primary source of income. It has a significant impact on the country's economy. However, agriculture is being hampered these days due to citizens shifting from rural to urban areas. Monitoring environmental factors is not a natural remedy for increasing crop production. Several causes have a significant impact on efficiency. Consequently, to address these issues, agriculture must incorporate automation. A farmer can save time, cost, resources, and energy by using an automated irrigation device. Traditional agricultural irrigation methods necessitate human interference. Human interference can be reduced with automated irrigation technology. This research work has designed and developed a reliable smart farming system (IoT) to reduce farmers' time costs and resources. Our proposed system can detect temperature, detect the moisture level and water level of the agricultural land, and remotely monitor the land crops. The proposed model sort out into four modules: Water Le vel Detection Module (WLDM) always detect the water level to avoid drops destruction; Soil Moisture Detection Module (SMDM) calculate the soil moisture level from the land, if the level goes down its start the water pump; Temperature Detection Module (TDM) is always counting the temperature and humidity of the air if its high then it will start the fan; Cloud and Notification Module (CNM) is handled the user notification through message and remotely monitoring the data of first three modules to take the necessary steps. The result shows the system successfully performed and it can be noted that our proposed can be implemented with any type of environment and agricultural land.
Sensor based Smart Automated Gas Leakage Detection and Prevention System
(Daffodil International University, 2022-05-02) Tasnim, Zarrin; Das, Saikat; Islam, Rakibul; Biswas, Jahanur; Shamrat, F. M. Javed Mehedi; Khater, Ankit
Liquefied petroleum gas (LPG) is commonly used for heating, cooking, automotive power, and various other uses worldwide. LPG is a particularly flammable gas, and LPG leaks cause significant incidents. The cause may arise from improper installation to the use of faulty gas cylinders. Since LPG is an extremely volatile and flammable gas, a reliable safety system has been designed and developed using IoT (Internet of Things) capable of detecting gas leakage, turning on the emergency alarm, tracking the location, and sending alerts messages to users and nearest helpline number. The proposed model sort out into four modules, such as Gas Detection Module (GDM) always detect the gas leakage to avoid unexpected incidents; Location Detection Module (LDM) track the gas leakage location and pass the value to NM; Notification Module (NM) is responsible for generating the message service to notify the nearest help center and user; In the case of a gas leak, the Alarm Module (AM) is responsible for activating an emergency alarm. The result shows the system successfully performed. It can be noted that the proposed can be embedded with any environment, including home, office, ship, industry, etc.