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5 articles for “Climate Anomaly Detection”
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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IoT Based Weather Monitoring System
Abstract: The Internet of Things (IoT)-Based Weather Monitoring System is developed to provide accurate, real- time monitoring of essential environmental parameters, including temperature, humidity, and atmospheric pressure. The system integrates high-precision sensors with a microcontroller, enabling continuous data acquisition from the surrounding environment. Collected data is transmitted wirelessly to a dedicated IoT platform via an internet connection, allowing remote users to access and visualize the information through web or mobile interfaces. …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 26–34 Read article
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Smart Weather Monitoring System Using ESP32 and IoT
Abstract: The increasing unpredictability of climate conditions necessitates an efficient and real-time weather monitoring system. The following paper describes an IoT weather monitoring system using the ESP32 microcontroller, connected to various environmental sensors to gather and process atmospheric information. The system uses a DHT11 sensor to measure temperature and humidity, an MQ135 gas sensor for measuring air quality, and a PM2.5 sensor to measure the level of particulate matter. The ESP32 …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 2, 2025 · pp. 25–36 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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Artificial Intelligence and Machine Learning Applications in Optimizing Air Conditioning Systems
Abstract: The growing demand for air conditioning systems, especially in the wake of climate change and increasing global temperatures, has led to a significant increase in energy consumption. This, in turn, contributes to the growing concerns of environmental sustainability and operational costs. As a result, there is a pressing need for innovative solutions to optimize the performance and energy efficiency of air conditioning (AC) systems. Artificial Intelligence (AI) and Machine Learning …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article