Browsing by Author "Shahnewaz Siddique"

Now showing 1 - 7 of 7
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    Open Access
    An Approach in Travel Demand Management Employing Crowd Sourced Data on a Social Networking Interface
    (North South University, 2019) Rabita Saleh; Syed Mohammad Dawood Yaseen; Mehbuba Zabyn; Shahnewaz Siddique; 1530649042; 1530669042; 1611968642
    According to research unveiled by the Accident Research Institute (ARI) of the Bangladesh University of Engineering and Technology (BUET) in 2018, traffic congestion in Dhaka costs the Bangladeshi economy approximately five million work hours and Tk. 37, 000 crore, annually. Amidst various other causes, the unpredictable nature of traffic in Dhaka creates prolonged traffic congestions. A significant part of these statistics can be attributed to a lack of information about traffic and no reliable central source of information to consult regarding the advisability of conducting a journey at any particular time. The only moderately reliable approach to gathering information regarding traffic is consulting Google Maps. However, the estimated time of arrival provided therein often fails to be satisfactorily accurate. In this paper we propose an online web application that combines the nature of a social media interface with crowd sourced data- a tool of our times the potential of which we are only beginning to grasp now- in order to provide the users with a central source of reliable information with the purpose of increasing traffic awareness, and thereby, discouraging congestion using concepts of travel demand management (TDM), particularly intelligent transportation technologies.
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    Assistive App for Visually Impaired People
    (North South University, 2023) Arham Chowdhury; Tasnuva Nawar; Saifuzzaman; Sumiya Sultana; Shahnewaz Siddique; 1931861642; 1931816642; 1931406042; 1931277642
    Monetary transactions are an indispensable part of our day to day activities. In case of a large amount of cash transaction, human error is a matter of concern. Thus the need for an efficient automated system for currency recognition has become significant these days. The challenge of currency recognition and object detection remains a significant obstacle for individuals with visual impairments. This issue is particularly pronounced in developing nations, where robust currency recognition systems are scarce. Recent research efforts have sought to address this issue, focusing on the complexities posed by the gradual degradation of currency notes over time. Recognizing currency notes has become increasingly complex due to wear and tear. Notably, the development of currency recognition systems adjust to the needs of visually impaired individuals in Asian countries has been relatively limited. To address this challenge, research has been conducted, leading to the forthcoming implementation of a practical application featuring two core components: an Image Classification Module and a Text-toSpeech Module. The primary hurdle in both modules is to enhance accuracy by using deep learning techniques. This initiative represents a crucial step in improving accessibility for visually impaired individuals, especially in regions with limited resources. The trained deep learning model achieved a remarkable 91% accuracy, indicating the convergence of the model during the validation process. This outcome signifies a significant advancement in providing accurate and reliable currency recognition and object detection for visually impaired users
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    Open Access
    Centralized Blood Bank Management System
    (North South University, 2020) Fahmidur Rahman; Sakif Hasan; Shahnewaz Siddique; 1410965642; 1420602042
    Blood transfusion and it’s related institutions like hospitals and blood banks are a common place in our modern lives, but still today people face shortage of blood during emergencies and sometimes even loose their loved ones in the process. In many cases it is mostly due to shortage of voluntary donors but sometimes it is due to lack of communication or no communication between the medical institutions. This evident problem is unacceptable in a age of internet and digitalization because with a proper platform, the issue can not only be solved but can save lives that should not be lost. Our project creates such a platform, where users, blood banks and hospitals can communicate with everyone and be aware of the need and shortcomings of blood anywhere else. If one blood bank has a certain type of blood and one does not, then they should be able to communicate, know the shortcomings and solve through the system we named “Centralized Blood Bank Management System”. This system will allow them to notify others of their own shortage and make requests to make up for that shortage. Besides, user asin public can also make their requests through this platform in times of emergencies. Our platform has a Web app and an Android app, which makes verified transactions between all the entities and has an easy accessibility to all.
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    FitTrack: Fitness and Health Tracking System for the People of Dhaka City
    (North South University, 2023) Asif Ahmed; Md. Fazayel Murshid; Tasmim Hassan; Shahnewaz Siddique; 1712426042; 1722152042; 1822157642
    The Fittrack app is a mobile application developed to address the health and fitness needs of the people living in Dhaka City. With this initiative's help, users can track their physical activity, keep tabs on key health indicators, and access customized workout programs. The Fittrack app offers a user-friendly design and a variety of features catered to Dhaka city people's separate lives and needs by utilizing the power of mobile technology. The Fittrack app's design, development, and evaluation, along with some of its main features and technical details, are covered in this paper. The app's sophisticated algorithms for goal-setting, data analysis, and activity tracking enable users to make educated decisions about their fitness and health. Through a user-centric approach and integration with popular fitness wearables, the Fittrack app aims to promote a healthier lifestyle and contribute to the overall well-being of the people of Dhaka city. The Fittrack app seeks to encourage a healthy lifestyle and improve the general well-being of the people of Dhaka city through a user-centric approach and integration with well-known fitness wearables.
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    IoT Enabled Smart Farm
    (North South University, 2023) Musfiqur Rahman; Syed Shadman Ahmed; Shahnewaz Siddique; 1931546642; 1811352642
    Now a days, livestock farming has become a concerning issues in our country because of population growth and demand. We need more urgency in this sector to produce more in numbers that too by maintaining a safe environment for the livestock animals. The intention of our work is to establish a platform on livestock monitoring and management. The IoT framework provides IoT solution in a wide range of domains and applications in livestock farming. The technology stack is based on the Internet of Things with relevant sensors available to determine the monitoring system to be placed on the animal. To bring better output from this sector, we intend to build an IOT device that will take care the livestock animal health and their welfare, the situation in which they live and their reproduction. It will provide a safe and healthy environment through continuous surveillance.
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    PHOENIX: Drone Aided Disaster Management System
    (North South University, 2019) Arnob Barua; Hasan-Ul Islam; Shihab Bin Sarwar Chowdhury; Shahnewaz Siddique; 1530418343; 1511167043; 1511974643
    There are traditional ways that we have used to control and deal with the after math of fire hazards and natural calamities like earthquakes and cyclone. But as the technology has developed in recent years we have come up with a more innovative method to tackle this problem which we believe can save more lives. Our solution is PHOENIX. It is a pair of drones that are designed for surveillance and survival package delivery in the case of a disaster management. The reason why we chose to work with drones is because one of the major aspect of a drone is that it can reach where a person cannot. In many disastrous situations that is a major factor in saving lives. Traditional methods has to work from a distance and is inaccessible in tight places. Our drones can provide an overview of the whole effected area and show exactly where to send rescuers and resources to save maximum lives and goods. In case of disasters these drones can be used for surveillance and also for deployment of fire extinguishing agents and emergence survival kits. These small changes can cause a major difference in a life and death situation. We believe that in the right hand our project can save a lot of lives in disaster situations.
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    Real Time Safety Measurement Protocol System for Construction Sites Using Machine Learning in Bangladesh
    (North South University, 2022) Tanjila Islam; Tanzila Islam; Sourav Biswas; Md. Abir Ahmed; Shuvo Bhowmick; Shahnewaz Siddique; 1811017042; 1811027042; 1721288642; 1722322042; 1632409042
    Safety in the construction industry is one of the main concerns in Bangladesh. It is one of the most unpredictable and danger-filled industry sectors. Most developed countries endeavor to reduce the tragic damages and losses resulting from construction accidents by preventing, eliminating, and bypassing the probable occurrences. Unfortunately, Bangladesh is one of the countries most at risk of construction accidents because they lack a robust safety system. Both authorities and employees do not have a clear understanding of construction safety. Safety negligence tends to cause most accidents. Thousands of Bangladeshi workers are injured or die from accidents on construction sites every year. Lack of training and knowledge about the equipment are the top five causes of these misfortunes, followed by lack of personal protective equipment, lack of safety eliminating/avoiding design, unfit equipment, and a lack of knowledge about the equipment. [1] The last decade has seen numerous studies conducted to introduce effective protection systems within the construction industry using machine learning and computer vision. To achieve this goal, in this study we proposed a model to actively monitoring the proper wearing of Safety Equipment (hard-hat, gloves, face masks, vests, harnesses and boots) of the construction workers in real-time. Based on the results of experimental tests, the model proved to have 86.93% mean average precision, which was effective for identifying safety equipment correctly. In combination with YOLOv4 and Darknet, these pieces of equipment can be registered and classified simultaneously. In future, we want to develop a system that monitors the wear of safety equipment to determine if workers are wearing it properly based on our model. Workers will not be able to access certain construction areas if one of these pieces of equipment is missing