Bandar Lampung

Nov 25, 2024 | ijircst.org | Siti Nur |Bandar Lampung

Siti Nur Abstract The rapid advancement of digital health technologies and sensor innovations has transformed wearable health monitoring systems, enabling unprecedented levels of personalized care, real-time health tracking, and early disease detection. This paper explores the pivotal role of these technologies in revolutionizing the healthcare landscape.

Nov 12, 2024 | ijircst.org | Siti Nur |Bandar Lampung

Siti Nur Abstract The rapid evolution of drone technology has expanded its applications across variodus domains, including delivery services, environmental monitoring, and search and rescue operations. However, many of these applications face significant challenges in GPS-denied environments, such as dense urban areas and heavily forested regions, where traditional navigation methods falter.

Sep 1, 2024 | ijircst.org | Siti Nur |Bandar Lampung

Siti Nur Abstract This study presents an algorithm for mobile node localization in wireless sensor networks, leveraging the Extended Kalman Filter (EKF). The algorithm demonstrates robustness in handling non-linear dynamics and adaptability to varying environmental conditions. While initial conditions and Gaussian noise assumptions pose challenges, ongoing efforts aim to address these limitations.

Aug 8, 2024 | ijircst.org | Siti Nur |Bandar Lampung |Muhammad Ashfaq

Siti Nur , Muhammad Ashfaq Abstract This paper presents a novel hybrid localization algorithm designed for healthcare systems, integrating Received Signal Strength Indicator (RSSI) and Time of Arrival (ToA) measurements with machine learning techniques. The algorithm aims to enhance the accuracy, robustness, and computational efficiency of sensor localization in dynamic healthcare environments.

Jun 12, 2024 | ijircst.org | Siti Nur |Bandar Lampung

Siti Nur Abstract Accurate localization is crucial for numerous applications, spanning from navigation systems to indoor positioning and asset tracking. However, achieving precise localization remains challenging, especially in environments where traditional positioning technologies face limitations. To address this challenge, this paper proposes a novel approach: the fusion of multiple positioning technologies.