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18 articles for “satellite IoT”
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AI Driven IoT based Satellite remote sensing system: KSK Approach in Satellite Remote Sensing
Abstract: The convergence of the Internet of Things (IoT) and satellite remote sensing has traditionally been bottlenecked by massive data latency and limited downlink bandwidth. This paper proposes a decentralized framework for an "AI-Driven IoT-based Satellite Remote Sensing System," which shifts the paradigm from raw data transmission to onboard edge-intelligence. By integrating lightweight convolutional neural networks (CNNs) directly into satellite payloads, the system performs real-time feature extraction and anomaly detection before …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 50–57 Read article
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Doppler Limits of LoRa in LEO: A Critical Review of the First In-Orbit Flight Tests
Abstract: This study provides a comprehensive review of the seminal work by Zadorozhny et al., which presented the first in-orbit flight test results evaluating the impact of Doppler effects on LoRa modulation for Low Earth Orbit (LEO) satellite communications. The review summarizes the original study's methodology using the NORBY CubeSat, details its key findings regarding the operational limits imposed by static and dynamic Doppler shifts across various LoRa configurations (Spreading Factor …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 21–27 Read article
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An Integrated Satellite and Underwater IoT Framework for Real-Time Oceanic Disaster Monitoring and Resilient Communication
Abstract: Ocean-based environmental disasters such as tsunamis and underwater earthquakes pose significant risks to human life, coastal infrastructure, and regional stability. However, traditional communication networks often collapse during such events, leading to delayed alerts and uncoordinated response efforts. This study presents an integrated framework that combines underwater Internet of Things (IoT) systems with satellite communication technologies to enable real-time oceanic disaster monitoring and reliable emergency communication. The system connects underwater sensor …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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Development of Compact RF Filters for Modern Wireless Communication Systems
Abstract: Modern wireless communication systems such as 5G, 6G, Internet of Things (IoT), satellite communication, radar systems, and smart wireless networks require compact and highly efficient RF filters for reliable signal transmission and interference suppression. RF filters are important components that allow desired frequency signals to pass while rejecting unwanted frequencies and noise. With the rapid growth of wireless devices and limited spectrum resources, the demand for miniaturized, low-loss, multi-band, and …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
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Real-Time Ocean Monitoring and Early Warning Systems with IoT Technology
Abstract: The increasing frequency of extreme weather events, rising sea levels, and threats to marine biodiversity This paper explores the application of IoT in enhancing real-time ocean monitoring and early warning systems, focusing on the deployment of smart sensors, connected buoys, and data analytics to collect key parameters such as temperature, salinity, pH, and wave activity. To preserve and responsibly utilise the seas, oceans, and marine resources in support of sustainable …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 13–24 Read article
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A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
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Oceanmind Systems: AI-Driven Marine Life Intelligence for Climate Prediction and Ocean Ecosystem Stability
Abstract: Oceans regulate global climate systems, support biodiversity, and serve as critical carbon sinks, yet they remain under-monitored relative to their ecological importance. Traditional oceanographic methods rely heavily on satellite sensing, buoy networks, and periodic marine surveys, which often fail to capture real-time biological dynamics at micro-ecosystem levels. This paper introduces OceanMind Systems, an artificial intelligence (AI)-driven marine intelligence framework that integrates marine life behavior, oceanographic data, and computational modeling to …
Published in International Journal of Marine Life · Vol. 3, Issue 2, 2026 Read article
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Integrating RF Technologies for Robust Disaster Response and Recovery Systems
Abstract: In the aftermath of disasters, one of the greatest challenges is the failure of communication networks, which delays rescue operations and worsens human suffering. Radio Frequency (RF) technologies offer promising solutions as they enable wireless communication, sensing, and tracking without depending on fragile infrastructure. This paper presents a study of RF applications in disaster management and proposes a unique hybrid multi-layer framework that integrates environmental RF sensors, RFID-based tracking, drone-mounted …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 24–27 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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IoT-Based School Bus Transportation Safety and Tracking System
Abstract: The safety of children during school commutes is a growing concern for both parents and school administrations. This paper presents an IoT-based School Bus Transportation Safety System that offers real-time tracking, biometric authentication, and emergency detection to ensure the safety of school children. The system utilizes a combination of NodeMCU, Arduino Uno, GPS, fingerprint modules, and sensors to provide a secure and efficient school transportation process. Parents and administrators can …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 56–65 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Integrating Internet of Things and Global Navigation Satellite System for Advanced Accident Detection and Road Safety Enhancement
Abstract: The purpose behind this project is to improve road safety through the development of an innovative internet of things (IoT)-based accident detection and reporting system. This research paper proposes the integration of GSM (Global System for Mobile Communications) and LoRa (long-range communications) technologies, utilizing the A9G module, Arduino Nano, and LoRa module RA02, to achieve real-time accident detection and efficient reporting. By leveraging accelerometer data analysis, the system promptly identifies …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 1, 2025 · pp. 29–35 Read article
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Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article