IOT
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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A Study on Security Requirements of IOT
Abstract: In terms of speed, internet technologies have surpassed traditional technologies. Although the Internet's explosive growth has allowed it to reach its full potential, there are several security dangers associated with it. Many consumer-grade IoT devices are not designed with robust authentication protocols, making them easy targets for hackers. To address this, stronger multi-factor authentication (MFA) methods and certificate-based authentication should be implemented to ensure that only legitimate devices gain access …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 24–28 Read article
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Envirosense Nexus: IoT-Driven Precision Waste Management for Urban Sustainability
Abstract: In modern urban environments, the improper handling of waste has become a significant issue, particularly due to insufficient and inefficient management of trash collection. This growing problem is leading to unhygienic conditions and pollution, requiring the introduction of smart waste disposal systems. To address this, we propose the development of an Internet of Things (IoT)-based intelligent trash bin that can autonomously detect, monitor, and report its waste levels. The system …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 26–31 Read article