FACULTY OF COMPUTING

Farm produce marketing is the process of moving agricultural products from the farm gate to the final consumer through activities. The aim of this study is to develop an online platform for farm produce marketing that enhances efficiency, accessibility, and transparency in agricultural transactions. The motivation that led to the implementation of the proposed system is that there is lack of direct access to profitable markets for smallholder farmers. Also, farm produce consumers face challenges in accessing fresh farm produce directly from farmers without relying heavily on intermediaries. The research identified major challenges in farm produce marketing, including poor access to market information reported by 30% of farmers, high dependence on middlemen (20%), and poor transportation and logistics (15%). The methodology adopted in this study is the object-oriented analysis and design methodology (OOADM) which is a technical approach for analyzing and designing an application or system by applying object throughout the software development process. The web programming languages (HTML, CSS, JAVASCRIPT, and PHP) was used in the software development process because, it is platform independent and it is a web-based application. The proposed farm produce marketing system will enhance agricultural commercialization by linking farmers directly with consumers and wholesalers. The expected result is an online platform for farm produce marketing that will establish training and support programs within the platform to improve digital literacy and encourage adoption among farmers.

This study addresses the inefficiencies of manual food ordering systems commonly used by Nigerian restaurants, such as order errors, delayed service, limited accessibility, and poor record management. The objective of the study was to design and implement a secure, efficient, and user-friendly web-based online food ordering system to automate the ordering and management process. An iterative Software Development Life Cycle (SDLC) methodology was adopted, encompassing system analysis, design, implementation, and testing, using modern web technologies including HTML5, CSS3, JavaScript, React.js, and Tailwind CSS. The developed system enables user authentication, menu browsing, cart management, order placement, and administrative control, and evaluation results demonstrated high functional accuracy, good usability, and reliable performance. However, the study is limited to a web-based prototype with sandbox payment integration and does not include live payment gateways, delivery tracking, mobile application support, or large-scale deployment, which are recommended for future enhancement

The rapid growth of online food delivery platforms has introduced challenges in supporting multiple restaurants on a single system. This research proposes a multi-tenant backend system for food delivery platforms, enabling each restaurant to operate independently while sharing the same backend infrastructure. The system ensures that tenants maintain full control over orders, menus, and operational data, eliminating the risk of conflicts or data overlap. Unlike traditional single-tenant or loosely structured multi-vendor systems, this implementation ensures strong tenant isolation by design which means each restaurant experiences the system as if it were built specifically for them. All operations including order processing, background jobs, inventory updates, and notifications are executed in a tenant-aware context. This work contributes a practical approach for anyone building a multi-vendor platform and not just in food delivery but also in areas where clean isolation, predictable behavior, and efficient resource sharing are required.

This project presents the design and implementation of a web-based student marketplace aimed at improving buying and selling activities within an academic environment. The system was developed to address challenges commonly faced by students, such as limited access to affordable goods, lack of organized trading platforms, and trust issues in informal transactions. The marketplace provides a centralized online platform where students can register, list products or services, search for items, and communicate securely with other users. The system was designed using structured system analysis and developed with modern web technologies to ensure efficiency, usability, and data security. Emphasis was placed on user-friendly interfaces and reliable database management to support smooth transactions. The implementation and testing of the system showed that it effectively enhances accessibility, promotes entrepreneurship among students, and reduces the time and effort involved in campus trading activities. The project demonstrates that a web-based student marketplace can significantly improve commerce and interaction within tertiary institutions.

This study investigates how transparency and explainability influence user trust in AI-driven interfaces. As AI systems become increasingly embedded in decision-making, users often struggle to understand their processes, leading to skepticism and reduced adoption. Using a mixed-methods approach, data were collected from 62 participants through structured questionnaires assessing transparency, explainability, trust, and user experience. Statistical analyses revealed that higher transparency and clear, human-centered explanations significantly enhance user trust and perceived fairness. However, overly technical or complex disclosures reduce comprehension and engagement. The study proposes a Human-Centered AI framework that integrates adaptive explainability, layered transparency, and user feedback mechanisms. Findings contribute to the growing field of trustworthy AI by offering practical guidelines for designing transparent, ethical, and user-aligned AI interfaces.

This research addresses critical challenges in Nigerian e-commerce through the development of a web-based Competitive Analysis System (CAS). The system tackles persistent issues of product authenticity verification, inaccurate descriptions, and limited competitive intelligence that undermine consumer trust and vendor competitiveness. Built on a Django REST Framework and React.js architecture with MySQL database management, the system integrates computer vision technology using Convolutional Neural Networks and FAISS similarity search, achieving 97% accuracy in product image verification. Natural Language Processing pipelines validate description accuracy against visual content, while automated web scraping modules provide real-time competitor intelligence across major e-commerce platforms. The research successfully delivered a fully functional platform that enables multi-vendor product comparison, automated verification, and competitive analysis. The system's theoretical framework combines Technology Acceptance Model with trust theory, specifically addressing the unique socio-technical challenges of emerging e-commerce markets. Practical implementation provides SMEs with accessible competitive intelligence tools while establishing new standards for transparency in digital commerce. The CAS platform demonstrates that integrating artificial intelligence and real-time analytics can effectively address core e-commerce challenges in developing economies, offering a scalable solution for enhancing market transparency and consumer confidence through verified product listings and data-driven vendor insights.

This project addresses the inefficiencies inherent in the manual appointment scheduling system at the University of Benin Health Centre, characterized by long waiting times, overcrowding, and poor data management. The study aimed to develop a centralized, web-based hospital appointment management system to enhance operational efficiency and patient access. The solution was designed using a three-tier client-server architecture and UML modeling (Use Case, Class, Activity, and Sequence diagrams) to define the clear interactions between Patients, Doctors, and Administrators. Implementation utilized PHP, MySQL, and Bootstrap to deliver a secure, responsive platform. Key functionalities include real-time appointment booking, doctor profile management, administrator approval/cancellation. Testing and evaluation confirmed the system's robustness and its successful fulfillment of all functional requirements. In conclusion, the developed system successfully digitizes the entire appointment workflow, significantly reducing administrative burdens and patient waiting times, thereby improving the overall quality of healthcare service delivery. Future recommendations include integration with external hospital systems, SMS reminders and advanced security features.

This study examines the degree to which digital identity systems have enhanced access to public services in Nigeria. In recent years, initiatives such as the National Identification Number (NIN), Bank Verification Number (BVN), and digital voter registration platforms have been introduced to improve identification, reduce fraud, and streamline service delivery. Despite these developments, many Nigerians still experience delays, verification challenges, and limited access to essential services. This study, therefore, investigates the level of awareness, usage, benefits, and challenges associated with digital identity systems. A quantitative research design was adopted, and data were collected using a structured
questionnaire administered to 100 respondents across different sectors, including banking, education, health, and government services. Data was analyzed using descriptive statistics
such as frequency and percentage distribution. The findings revealed that a majority of respondents have registered for at least one digital identity and frequently use it for accessing services such as account verification, SIM registration, and online transactions. The results further show that digital identity has improved service delivery by reducing manual processes, enhancing security, and increasing convenience. However, challenges such as network failures, long enrollment queues, data errors, and system downtime still limit efficiency. The study concludes that digital identity systems play a significant role in improving access to public services, but greater investment in infrastructure, public awareness, and system integration is required. It recommends improved government funding, periodic system upgrades, and better data management policies to enhance effectiveness and public trust.

Incidents of social injustice, including discrimination, harassment, and unfair treatment, are common in Nigerian tertiary institutions but are often underreported due to fear of retaliation, lack of confidentiality, or inadequate reporting mechanisms. This project presents the development of the SpeakUp App, a web-based platform designed to enable students to report social injustices securely, anonymously, and efficiently. Data for this study was collected via a structured survey administered to students, providing insights into the challenges they face in reporting incidents and their expectations from a reporting system. The system incorporates features for submitting incident reports, attaching evidence, tracking report status, and providing administrative oversight, ensuring complaints are managed effectively while protecting user privacy. Developed using Django for the backend and ReactJS for the frontend, the application leverages Django’s security framework and a responsive, user-friendly interface. Survey findings informed the design, and system testing confirmed usability and reliability. The results indicate that the SpeakUp App can significantly improve the reporting and management of social injustice incidents, empowering students and promoting fairness within academic environments.

This project presents the design and development of a simulated Transaction Verification and Reversal Request Model for Nigerian’s mobile payment systems. It aims to reduce mistaken money transfers and improve user rust by combining two key components: The Verify- HoldConfirm (VHC) Model, which prevents transaction errors through smart verification errors through smart verification and timed holds, and the Mistaken Transfer Protocol (MTP), which enables quick and automated reversal of incorrect payments. The system was implemented as a mobile application using React Native and SQLite, and tested with real users to evaluate usability and performance. Results show that the model effectively reduces transaction errors, improves recovery sped, and increases user confidence in mobile transfers. This research contributes to Nigeria’s financial technology growth by offering a practical, user-friendly, and secure framework for mobile transaction management.