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All Journal Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics International Journal of Engineering, Science and Information Technology
Haider Hadi Abbas
Al-Mansour University College
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Practical application of IOT and its implications on the existing software Israa Sadu; Zahraa A. Jaaz; Haider Hadi Abbas; Haider Abdulshaheed
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2069

Abstract

The data management from end-to-end level is done by cloud-assisted IOT for its users and they keep a goal in increasing their number of users with the course of time. From saving the infiltration of data from both internal and external threats to the system, IOT is the best-proposed method used for securing the database. Connecting objects/individuals with the Internet via safe interaction is the main objective of IOT. It can assemble all the hardware devices that are designed to store data for an individual or an organization. The associated applications and the way in which it can be deployed in the present organization in order to optimize the current working system. This paper focuses on providing an overall systematic secured data sharing portal that is devoid of threats from internal as well as external entities. By using CIBPRE data encryption a major security reform is introduced by IOT in storing and sharing of data on a regular basis.
Integrating security and privacy in mmWave communications Ghadah M. Faisal; Hasanain Abdalridha Abed Alshadoodee; Haider Hadi Abbas; Hassan Muwafaq Gheni; Israa Al-Barazanchi
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.4314

Abstract

The aim of this paper is to integrate security and privacy in mmWave communications. MmWave communication mechanism access three major key components of secure communication (SC) operations. proposed design for mmWave communication facilitates the detection of the primary signal in physical (PHY) layer to find the spectrum throughput for primary user (PU) and secondary user (SU). The throughput of SC for PU with maximum throughput being recorded at 0.7934 while maximum throughput for SU is recorded at 0.7679. So, we will design a mmWave communication mechanism for solving this problem. The probability for sensing where the probability of detection (PD) is predicted at a defined range of 690 km with an estimated accuracy of 83.56% while the probability of false alarm (PFA) is predicted at a defined range of 230 km with an estimated accuracy of 81.39%. This conflicting but interrelated issue is investigated over three stages for the purpose of solving with a cross-layer model with MAC and PHY layers for a secure communication network (SCN) while reducing the collision effect concurrently with a 92.76% for both cross-layers. MATLAB 2019b would be forwarded in use as the increasing demand for augmenting the bandwidth in secure communications has actuated the evolutionary technology.
Design of Ethical AI Frameworks for Sustainable and Adaptive Energy Management Systems Mustafa Humadi; Haider Hadi Abbas; Hassan Waryoush Hilou; Nahlah. M. A. D. Najm; Ammar Abdulkhaleq Ali; M. Batumalay
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1288

Abstract

The integration of Artificial Intelligence (AI) in Energy Management Systems changed completely how sustainable infrastructure operates?and is guarded. But the growing independence of AI decision-making presents some serious ethical questions about?fairness, transparency, and accountability. The article introduces a new framework with Ethical AI for Sustainable and Adaptive Energy Management Systems (EAI-SEM) that is designed to combine functional (re)configuration for operational control and ethical governance in centralized: smart buildings and?decentralized: nano-grid settings. The approach incorporates deep reinforcement learning for adaptive control, federated learning for privacy-preserving model updates, and an?integrated Ethics Verification Module for a dynamic assessment of privacy-conformance levels. In experimental simulations over 30-day operation of the smart building and 10-rounds of federated training of the nano-grid, unjust fairness deviation and explainability of the system experienced enhancements, which also indicated?the reduction of carbon dioxide emissions. The?study demonstrated that ethical protocols can be included without impacting on computational efficiency and system responsiveness. Additionally, the federated structure facilitated decentralized ethical responsibility across different actors and thus allowed for the scalable?implementation. The authors verify the possibility of integrating ethics into the computational core of?intelligent energy systems, near from auditing static policies, towards dynamic ethical choices. In the future the process innovation work could be applied to deployments in other infrastructure systems like water?systems and mobility systems, and it provides a reproducible model for the embedding of normative reasoning into AI for infrastructure.
Co-Authors Ammar Abdulkhaleq Ali Ghadah M. Faisal Haider Abdulshaheed Hasanain Abdalridha Abed Alshadoodee Hassan Muwafaq Gheni Hassan Waryoush Hilou Israa Al-Barazanchi Israa Sadu M. Batumalay Mustafa Humadi Nahlah. M. A. D. Najm Zahraa A. Jaaz