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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Syed Hasan Saeed
Integral University
Computer Science & IT Electrical & Electronics Engineering

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A Cooperative Cache Management Scheme for IEEE802.15.4 based Wireless Sensor Networks Piyush Charan; Tahsin Usmani; Rajeev Paulus; Syed Hasan Saeed
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (18.65 KB) | DOI: 10.11591/ijece.v8i3.pp1701-1710

Abstract

Wireless Sensor Networks (WSNs) based on the IEEE 802.15.4 MAC and PHY layer standards is a recent trend in the market. It has gained tremendous attention due to its low energy consumption characteristics and low data rates. However, for larger networks minimizing energy consumption is still an issue because of the dissemination of large overheads throughout the network. This consumption of energy can be reduced by incorporating a novel cooperative caching scheme to minimize overheads and to serve data with minimal latency and thereby reduce the energy consumption. This paper explores the possibilities to enhance the energy efficiency by incorporating a cooperative caching strategy.
Detection of harmful gases present in the environment Pratiksha Rai; Syed Hasan Saeed
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp70-80

Abstract

The electronic nose (e-nose) is demonstrated in this research for detecting and identifying several forms of hazardous gases. We describe an e-noses for detecting several gases, including butane, acetone, methane, and ethanol. For dimensionality reduction in 3D representation, data processing approaches are based on the partial least square (PLS) method. The suggested system can be utilised for sensor optimization since different sensors with varied operating temperatures can be tested in many devices to find the best array for a specific detection or application. The results reveal that, depending on the sensor array characteristics, varying success rates in classification can be attained when discriminating contaminants. The preceding criteria lead to a new search for a portable, dependable, low-cost, and most efficient gas sensor. The major purpose of this study is to create a gas sensor array that can detect and monitor toxic and poisonous gases in the environment, as well as warn against dangerous organic compounds. Our goal is to create a sensor system that can distinguish the most significant decontamination gases while also being highly responsive, precise, low-effort, and low-power demanding.
Harmful gases detection using artificial neural networks of the environment Pratiksha Rai; Syed Hasan Saeed; Shri Om Mishra
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1389-1398

Abstract

This work describes a small, low-cost electronic nose device which can detect harmful substances that can harm human health, such as flammable gas like acetone, ethanol, butane as well as methane, among others. An artificial olfactory instrument consists of a set of metal oxide semiconductor sensors as well as a computer-based communications channel for signal gathering, proceeding, and presentation. We used three sensors instead of six, and the results were plotted as a variance, score as well as loading plot with crossvalidation. For gas identification, we use artificial neural network (ANN) and compare them to parallel factor analysis. Electronic nose (e-nose) has provided numerous benefits in a variety of logical study disciplines. Our goal is to create a sensor exhibit framework that can discriminate the most exceedingly contaminated gases while also being extremely responsive, precise, and less power consuming. Thus, for gas detection, we employ an ANN as well as make a comparison of results with parallel factor analysis (PARAFAC).
Co-Authors Piyush Charan Pratiksha Rai Rajeev Paulus Shri Om Mishra Tahsin Usmani