AJASA ABIODUN AFIS

Meet AJASA ABIODUN AFIS, an Academic Staff of Lagos State University.

Specialization

Control Engineering, Electronics, Internet Of Things

Designation

Lecturer II

Department

Electronics and Computer Engineering

Office

At the Electronics And Computer Engineering department office

Visiting Hour

Appointment on Visitation important

Research Interest

Topic: DESIGN AND IMPLEMENTATION OF PIPELINE LEAKAGE DETECTION SYSTEM ( DETECTION OF PIPELINE VANDALISATION / LEAKAGE)

Description: Pipeline vandalisation is a problem facing the oil sector especially in Nigeria. Nigeria loses billions of naira to vandalisation yearly. The sole responsibility of securing the pipelines lies on the shoulders of the various security officers, including the police and other paramilitary agencies, but rather than arresting the oil thieves or vandals, these officers collaborated and conspired with them, thereby compounding the menace of pipeline vandalism and crude oil theft. Some pipeline networks pass through remote villages where security personnel are not deployed – cases like this will surely result into complete vandalisation of the pipeline. The major benefits to be derived from this study include early detection of pipeline intrusion before pipeline is damaged, the consequence of which can lead to reduction in financial losses and alleviation of environmental degradation as well as the possibility of the authority to take action towards successful arrest and prosecution of the culprits by a way of capturing the vandalisation video footage, which can eventually serve as exhibit in the court of law. This work offers a solution model to this problem in such a way that intruders to the demarcated pipeline area are detected and prevented from vandalizing the pipelines. The necessary authorities will then be notified secretly via SMS when there is an intruder in the pipeline region.

Qualifications

# Certificate SchoolYear
1. M.Sc (CONTROL ENGINEERING OPTION) DEPARTMENT OF ELECTRICAL/ELECTRONIC ENGINEERING/ UNIVERSITY OF LAGOS 2003

Current Research

Data-Driven Performance Evaluation of IoT-Based Human Tracking Method Using Kalman Filter and Extended Kalman Filter with Particle Swarm Optimization

Research Details

INTRODUCTION: Various crimes have necessitated using security and protection systems to keep people and their properties safe. Unfortunately, since they are so easily broken, locks and bolts do little to deter intruders and burglars. Homes require better security. IoT, biometrics, and tracking provide better safety. Information security, identity authentication, smart cards, access control systems, and law enforcement are areas of interest. Many applications rely on biometric identity and IoT. Therefore, human detection with recognition is the best solution. Life and property attacks require IoT systems with Kalman filter tracking.

OBJECTIVES: To design an IoT-based testbed utilizing Arduino and RFID sensors to monitor human movement. To develop KF and EKF algorithms to track human movements and predict their successive positions. To develop PSO algorithm to optimize KF and EKF errors for human motion tracking.

METHODOLOGY: The methodology describes the research context, design, implementation process, and adopted techniques and tools.  It includes IoT design implementation as a monitoring tool for human motion tracking, formulation and theoretical framework of KF and EKF, and concept and development of PSO as error optimization.

RESULTS: The measured (or exact) position vs. the estimated (or predicted) position plots overlap because their curves are close. However, the % error curve, which shows the difference between exact and predicted positions, is nearly insignificant. Therefore, the models can reliably predict the tracked person's future position. The performance analysis of the models was also carried out.

CONTRIBUTION TO KNOWLEDGE/SOCIETY: The work proposes the Kalman filter model for IoT-based human tracking. Most prior PSO-KF or PSO-EKF models employed computer vision or video surveillance to track vehicles, animals, balls, or humans. However, the proposed work uses an IoT platform as the monitoring system

Biography

AJASA ABIODUN is a Lecturer II at the Department of Electronics and Computer Engineering

AJASA has a M.Sc in CONTROL ENGINEERING OPTION from DEPARTMENT OF ELECTRICAL/ELECTRONIC ENGINEERING/ UNIVERSITY OF LAGOS

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