Browsing by Author "Hanif Ali, Mohammad"

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    IOT Based Street Lighting Using Dual Axis Solar Tracker and Effective Traffic Management System Using Deep Learning
    (11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020. IEEE, 2020-10) Saifuzzaman, Mohd.; Shetu, Syeda Farjana; Moon, Nazmun Nessa; Nur, Fernaz Narin; Hanif Ali, Mohammad
    With the rapid increase of population, nonrenewable energy loss has become one of the prior concerns worldwide in recent years. Researchers are working on the proper utilization of renewable energy to save the rest of the non-renewable energy sources for future generations. One of the purposes of this research is to develop an intelligent automation system that can decide luminous control operation based on light intensity. Here, LDR sensor is installed in such a way that it can be able to identify Night and Day mode using a certain intensity value, and as well as IR sensors take over the control of street light. The solar cell will be used for power supply here and DC current will work as a secondary backup. The article also involves automatic monitoring of traffic controls through a video system. The camera incorporates automatic text retrieval from video data utilizing lip reading by decoding facial expression utilizing deep learning methods. The proposed solution includes a test data collection, an interpretation of the picture frame, and a text production of the specified words. The test data collection will be structured in the proposed methodology by integrating all potential facial expressions of different words.
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    IOT-NFC Controlled Remote Access Security and an Exploration through Machine Learning
    (2020 18th International Conference on ICT and Knowledge Engineering (ICT&KE), IEEE, 2020-12-25) Khan, Md. Abbas Ali; Hanif Ali, Mohammad; Haque, A.K.M Fazlul; Sharmin, Farah; Jabiullah, Md. Ismail
    Internet of Things (IOT) is a system that allows to connect the computing devices without the help of human-to-human or human-to-computer interaction. This paper proposes an app-based remote access control door lock security system (RACDLS) along with a short-range wireless communication naming Near Field Communication (NFC). The RACDLS system generates two sides' authentication systems rather than one side authentication like conventional systems. In the conventional system, users which are registered, can enter the premises only. In the proposed RACDLS system, users require permission from the room owner either they are registered or unregistered. Moreover, for maintaining the integrity and the confidentiality of data, a cryptographic technique (e.g.) we consider computational 512 bits hash function. In contrast, apply AES-192 for encrypting the hashed data. In addition, machine learning (ML) shows the performance of the employee activities including prediction with model accuracy. A definitive objective of this paper is to ensure the security of remote access control as well as allow notification of both ends, accessibility, usability, and permissibility of a personnel to enter the premises.