International Research Journal on Advanced Engineering Hub (IRJAEH)

Automated Nuclei Cell Counting is needed in biomedical research and clinical diagnosis traditionally counting manually under a microscope that was time-consuming and prone to error. This paper will outline the QUT system, a system that combines image processing and quantum computation to detect and quantify nuclei within a shorter time. Classical techniques like watershed algorithms and morpholog…

The AI-Driven Legal Research Engine is designed to improve the efficiency and accuracy of legal research in commercial courts by handling large volumes of legal data such as judgments and statutes. It enables deeper understanding of legal texts beyond simple keyword searches, providing more relevant and context-aware results. The system offers concise summaries of lengthy legal documents and allo…

The fast switching to digital documents in educational and professional life has raised the number of screen-based reading enormously, but it is accompanied by a notable decrease in concentration, constant-distraction, and the inability to continue reading. To solve these problems, the following paper gives a gaze-assisted web-based reading platform that can track the eye gaze of users and tell t…

The proliferation of fragmented digital tools across higher education institutions has created significant administrative inefficiencies, data silos, and poor student engagement. Existing platforms — including Moodle, Canvas, Google Classroom, and Blackboard — each address isolated academic functions but fail to deliver a unified, intelligent, mobile-first experience encompassing communication, m…

Customer churn represents one of the most consequential operational challenges facing modern banking institutions. As fintech alternatives and neobanks continue to erode traditional customer loyalty, banks require predictive systems that go beyond historical rule-based triggers. This paper proposes an end-to-end, AI-driven framework that integrates supervised churn prediction, Customer Lifetime V…

Efficient nutrient management is a critical determinant of crop yield and soil longevity. Conventional manual fertilizer application often results in disproportionate distribution. This leads to substantial resource wastage, ecological degradation, and escalated operational costs. Addressing the lack of accessible precision agricultural tools for farmers, this paper proposes a cost effective, Art…

Smart grids generate huge amounts of energy information in real-time, which is vital to the grid's efficiency and reliability, but is often marred by anomalies due to faulty meters, equipment failures, and energy theft, resulting in substantial losses. This paper presents the development of an anomaly detection system named FlowTrack, which is production-ready and uses a hybrid machine learning m…

The parking slots in the campus or the city area provide visual information, which is an important aspect in the efficient utilization of the parking slots. The traditional approach in monitoring the parking slots is not efficient, and many inaccuracies are present in the traditional approach, which may cause congestion and inefficient utilization of the parking slots. The proposed research is fo…

Continuous, covert, and intelligent surveillance is required on the borders to record intrusions and hostile activities in adverse environment conditions. This paper discusses the restrictions of the traditional surveillance systems with a proposal of a Camouflaged Surveillance Pole that can be used in military border patrol. It is a multi-modes system incorporating gas, smoke, vibration, motion,…

For sustainable farming methods and maximum crop yield, early and precise identification of plant diseases is essential. A major agricultural crop, chickpeas (Cicer arietinum) are extremely prone to a number of bacterial, viral, and fungal diseases that significantly lower quality and productivity. In order to effectively extract and classify features, this study suggests a hybrid deep learning m…

Edu-Smart School Management System is designed to simplify and digitalize academic and administrative activities in schools. The system is developed using the MERN stack for the web application and Java in Android Studio for the parent mobile application. It provides a centralized platform for managing student information, attendance, homework, examination results, timetables, and school announce…

The rapid adoption of smart home Internet of Things (IoT) technologies has intensified the demand for secure, efficient, and privacy-preserving user authentication mechanisms. Existing revocable biometric-based authentication schemes provide certain security advantages; however, they often suffer from high computational complexity and limited adaptability to evolving security threats. This paper …

A voice-controlled simulated elevator system designed to improve accessibility for visually impaired and paraplegic users through a touchless interaction model. The system employs speaker-independent Automatic Speech Recognition (ASR) using Sphinx-4 to accurately interpret spoken commands such as floor numbers, movement directions, and door operations within an eight-floor setup. For safety and e…

Construction sites are among the most hazardous work environments, where workers face risks from falling objects, heavy machinery, electrical hazards, and exposure to dangerous materials. Ensuring proper use of Personal Protective Equipment (PPE) such as helmets, safety vests, gloves, boots, and masks is critical to minimizing accidents and injuries. Traditional PPE compliance monitoring relies h…

Due to growing advanced cyber attacks, the security systems used to monitor payment fraud should be smartly tuned in real-time to identify such threats immediately. Our paper proposes an AI-Driven Multi-Threat Cybersecurity & UPI Fraud Detection System that unites elements within a single ecosystem to detect browser extensions aimed at, ransomware activities, and UPI/QR code-related financial…

Location-Based Services (LBS) leverage modern mobile and cloud technologies to deliver relevant information and services based on a user’s geographical position. These systems help users easily find nearby services such as public utilities, thereby improving convenience, safety, and decision-making in everyday life. By using real-time location data, LBS applications provide accurate, personalized…

As the need for remote healthcare monitoring increases, especially among elderly individuals and patients with chronic diseases, intelligent systems capable of detecting emergencies in real time have become essential. Existing IoT-based health monitoring systems often suffer from limitations such as high false alarm rates, limited processing capabilities, and reliance on single-sensor data. This …

The rapid expansion of digital platforms and online financial ecosystems has substantially increased vulnerabilities to fraudulent activities, account takeovers, and anomalous user behaviors. Traditional risk detection methodologies operate reactively, identi- fying threats only after financial losses or security breaches have materialized. This paper presents the Behavioral Drift Analytics Early…

Diabetes mellitus remains one of the most prevalent chronic conditions worldwide, demanding continuous and accurate monitoring of blood glucose levels to prevent life-threatening complications such as hypoglycemia and hyperglycemia. Traditional glucose prediction systems rely solely on historical glucose readings, overlooking the physiological relationship between cardiovascular activity and glyc…

The convergence of Big Data analytics, Internet of Things (IoT), and fifth-generation (5G) wireless networks is transforming next-generation intelligent systems. IoT devices continuously generate massive volumes of heterogeneous data, requiring high-speed connectivity and intelligent analytics for real-time decision-making. Traditional network infrastructures and centralized processing models are…