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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Sahour, Abdelhakim
Khenchela University
Computer Science & IT Electrical & Electronics Engineering

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The Efficiency of HEVC/H.265, AV1, and VVC/H.266 in Terms of Performance Compression and Video Content Boumehrez, Farouk; Sahour, Abdelhakim; Djellab, Hanane; Maamri, Fouzia
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i3.5336

Abstract

In recent times, there has been a significant focus on digital compression. The purpose of this study is to undertake a comparative evaluation and examination of the efficacy of the latest standards, namely HEVC, AVI, and its successor VVC. The determination of which standard to utilize relies heavily on factors such as the inherent characteristics of the video, its functionalities, quantization parameters, image quality, as well as the size and video content, this latter, is often classified by spatio-temporal complexity using spatial and temporal information (SI/TI). In reality, they are mostly used for original video sources. The efficiency of encoding original video sources is unknown. The results show that each standard has characteristics that sometimes make it superior to others. In addition, We observe that By understanding how SI and TI affect encoding efficiency, we will be able to better optimize the encoding process and reduce the amount of data that needs to be stored, transmitted, and processed. This could help to reduce the amount of time and energy required to encode video content, as well as reduce the amount of storage space needed to store it. Compared to H.265/HEVC, AV1 is more efficient at compressing HD and FHD video, and more efficient for SD video. In addition, experiments show that VVC/H.266 has higher compression efficiency.
Forest fire risk monitoring using fuzzy logic and IoT technology Sahour, Abdelhakim; Boumehrez, Farouk; Maamri, Fouzia; Djellab, Hanane; Abdelali, Bakhouche
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 2: June 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i2.5242

Abstract

Forest fire is one of the leading causes of ecological damage and environmental problems. This work aims to develop a forest fire risk monitoring system in which an artificial intelligence technique, fuzzy logic, has been used to determine the forest method risk (temperature, relative humidity, and wind speed). Fuzzy set theory implements categories or groupings of data whose boundaries are not clearly defined (i.e. fuzzy), consisting of rule bases, membership functions, and inference methods. We also use wireless sensor networks (WSN) and Internet of Things (IoT) technologies. In order to collect environmental information through WSN based environmental sensors, the collected information is transmitted to a database on a server through an Internet connection. Users can monitor the saved data using an internet browser in each whey. This provides the ability to analyze detailed data and then take the necessary precautions to protect threatened forests.
Co-Authors Abdelali, Bakhouche Boumehrez, Farouk Boumehrez, Farouk Djellab, Hanane Maamri, Fouzia