Browsing by Author "Omotayo Oshiga"

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    Human Detection For Crowd Count Estimation Using CSI of WiFi Signals
    (International Conference on Electronics Computer and Computation (ICECCO), 2019-12-01) Omotayo Oshiga; Hussein U. Suleiman; Sadiq Thomas; Petrus Nzerem; Labaran Farouk; Steve Adeshina
    We address the problem of crowd estimation in situations such as indoor events using anonymous and non-participatory CSI of WiFi Signals. Observing the great resemblance of Channel State Information (CSI, a finegrained information captured from the received Wi-Fi signal) to texture, we propose a brand-new framework based on statistical mechanics, and relying only on sets of machine learning techniques.In this paper, a framework for crowd count estimation is presented which utilizes Chebyshev filter and SVD to remove background noise in the CSI data, PCA to reduce the dimensionality of the CSI data and spectral descriptors for feature extraction. From the extracted feature, a set of classiffying algorithms are then utilised for training and testing the accuracy of our crowd estimation framework The aim of this framework to effectively and efficiently extract the channel information in WiFi signals across OFDM carriers reflected by the presence of human bodies. From the experiments conducted, we demonstrate the feasibility and efficacy of the proposed framework. Our result depict that our estimation becomes more–rather than less–accurate when the crowd count increases.
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    Improved Liquid Level Control Design Using Mamdani Fuzzy Inference System.
    (International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS)., 2023-11-01) Nathaniel U. Nathaniel; Suleiman U. Hussein; Omotayo Oshiga; Nyangwarimam Ali; Petrus Nzerem; Sadiq Thomas
    In industrial applications such as those in petrochemicals, nuclear, etc. liquid level control is very important: hence we have elaborated a straightforward case of control scenario, that can further be applied in multiple of these areas by simply varying the design to suit each case. We have given preference to the application of fuzzy logic rather than other control methods – hence describing a lot of the background information about it. Then, we move forward to apply the Mamdani type Fuzzy Inference System in demonstrating how the logic works in controlling the liquid level in a single tank system; first using 3-rules, then, 5-rules. We have designed and simulated in MATLAB, the 3-rules and the 5-rules systems. Unlike previous works on these cases, our results show better choices in that, key performance parameters viz rise time, settling time and overshoot, are better than previous results we have seen in literatures. We achieve these better results by varying some parameters, initial conditions and improved Simulink designs; to explore the viability of our chosen method of control. This work also further proves that the FLC is a better controlling method in these areas of its application than other control methods.