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p-Index From 2021 - 2026
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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Indonesian Journal of Electrical Engineering and Computer Science
Plabon kumar Saha
American International University-Bangladesh
Computer Science & IT

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A review on notification sending methods to the recipients in different technology-based women safety solutions A. Z. M. Tahmidul Kabir; Al Mamun Mizan; Plabon kumar Saha; Nirmal Debnath; Tasnuva Tasneem
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp57-64

Abstract

Women have progressed a lot in terms of social empowerment and economics. They are going for higher education, jobs, and many other similar endeavors, but harassment cases have also been on the rise. So, women’s safety is a big concern nowadays, especially in developing countries. Many previous studies and attempts were made to create a feasible safety solution for women. Out of various features to ensure women’s safety in critical situations, location tracking is a very common and key feature in most previously proposed solutions. This study found mechanisms of sending the location to different types of recipients in various women safety solutions. In addition, the advantages and drawbacks of location sending methods in women's safety solutions were analyzed.
An intelligent wind turbine with yaw mechanism using machine learning to reduce high-cost sensors quantity Subrotho Bhandari Abhi; Plabon Kumar Saha; A. Z. M. Tahmidul Kabir; Al Mamun Mizan; Mohammad Minhazur Rahman; Afrina Talukder Mimi; Md. Mainul Ahsan; Arpita Hoque; Humyra Nusrat
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp10-21

Abstract

In this paper, with the assistance of some tools and a machine learning model, a smart wind turbine was formed that eliminates some expensive sensors and reduces sensor complexity. Squirrel cage induction generator (SCIG) and six rotor blades make up the proposed design, and depending on the wind's direction, the turbine itself can rotate the rotor hub to produce energy more effectively. Additionally, two stepper motors are coupled to the yaw mechanism with the aid of the rotor hub, and the entire controlling procedure will depend on the direction of the wind. The rotor hub must continuously revolve in the same direction as the wind to maximize wind energy utilization. Additionally, to correctly predict wind degrees, a machine learning model was deployed. Random forest regression was used to train and predict the wind direction. The model is deployed in Raspberry Pi, where the incoming sensor values are being stored. Using the generated data, machine learning model was trained and it can be concluded that the model can potentially replace some of the expensive sensors to reduce cost. The model can be used for similar weather conditions only based on machine learning model and fewer sensors.
Co-Authors A. Z. M. Tahmidul Kabir Afrina Talukder Mimi Al Mamun Mizan Arpita Hoque Humyra Nusrat Md. Mainul Ahsan Mohammad Minhazur Rahman Nirmal Debnath Subrotho Bhandari Abhi Tasnuva Tasneem