HARNESSING AI FOR COMMUNITY HEALTH: DESIGN FRAMEWORK AND PILOT PROTOCOL FOR A HAUSA-LANGUAGE CHATBOT FOR MALARIA PREVENTION IN BAUCHI STATE, NIGERIA

ABSTRACT This paper presents a design framework and study protocol; no empirical results are reported. Malaria is a critical health burden in Bauchi State, Northern Nigeria, driven partly by the absence of communication tools accessible in Hausa, functional under low-bandwidth conditions, and suitable for low-literacy users. We propose a dual-platform AI chatbot for malaria prevention

Read More

DEVELOPMENT OF CLINICAL DECISION SUPPORT ENSEMBLE-BASED SYSTEM FOR THE PREDICTION OF CHILDHOOD KILLER DISEASES IN RESOURCE-LIMITED SETTINGS

ABSTRACT Childhood killer diseases like malaria, pneumonia, diarrhoea are still the major causes of death among children under the age of five in resource-limited settings especially in sub-Saharan Africa. Poor healthcare infrastructure, shortage of skilled manpower and absence of smart diagnostic tools at Primary Health Care (PHC) level are often a barrier to early diagnosis.

Read More

ENHANCED DEEP LEARNING-BASED REAR COLLISION AVOIDANCE SYSTEM USING A HYBRID CNN–RNN ARCHITECTURE AND MULTI-SENSOR FUSION

Abstract Rear-end collisions remain a major contributor to road traffic accidents, accounting for nearly 28% of all road accidents in Nigeria in 2022, with existing collision avoidance systems limited by rigid, rule-based logic and reliance on costly or single-modality sensing. This work enhances a Raspberry Pi 4B-based Rear Collision Avoidance System (RCAS) that originally relied

Read More

EXPLAINABLE AND RESILIENT FACE RECOGNITION SYSTEMS FOR INCLUSIVE ECONOMIC GROWTH

Abstract Face recognition systems are increasingly used in digital identity, financial services, and public-sector applications, yet many existing models remain opaque and vulnerable to bias, exclusion, and performance degradation under real-world conditions. This paper presents an integrated framework for explainable and resilient face recognition that combines robust deep feature extraction, post-hoc explainable AI techniques, and

Read More

STRENGTHENING NIGERIA’S DIGITAL INFRASTRUCTURE: STRATEGIES FOR CYBERSECURITY RESILIENCE AND POLICY INNOVATION

ABSTRACT With the digital revolution, the question of resilience in the face of cybersecurity is of great importance to Nigeria’s security, economy and development. In this research paper, the focus is on the issues of how digital infrastructure resilience can be achieved in Nigeria through the use of cybersecurity and innovation. In the case of

Read More

ENHANCING SOFTWARE QUALITY THROUGH MACHINE LEARNING- BASED DEFECT PREDICTION FOR ECONOMIC GROWTH AND DIGITAL INCLUSION

ABSTRACT The increasing reliance on software systems in modern economies necessitates the development of reliable and high-quality software to support sustainable economic growth and digital inclusion. Meeting end-user requirements and expectations during the initial stage of software deployment is one of the most difficult tasks in the software development process. Therefore, detecting defects before deployment

Read More

INTELLIGENT POWER MANAGEMENT FOR BASE STATION IN CELLULAR NETWORKS USING MODEL-BASED REINFORCEMENT LEARNING

ABSTRACT This study creates base station as an intelligent agent for power management in wireless communication using reinforcement learning (RL). Base station (BS) operations in a cellular network were modelled as a Markov Decision Process with five tuples (states or S, actions or A, transition or T, discount factor or Y, horizon or H) represented

Read More

APPLYING ARTIFICIAL INTELLIGENCE IN MUTATION BREEDING

ABSTRACT Many studies have highlighted the transformative role of artificial intelligence (AI) and machine learning (ML) in the field of agriculture.  However, works on the application of AI algorithms in breeding initiatives for improved varieties remain underexplored. To bridge this gap, this study presents a computational modelling approach to cowpea mutation breeding. Three cowpea landraces

Read More