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544 articles for “predictive algorithm”
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Smart Street Lighting Enabled by Wireless Sensor Networks: A Path to Energy Efficiency and Fault Monitoring
Abstract: The increasing demand for energy efficiency and smart city infrastructure has led to the adoption of innovative technologies such as wireless sensor networks (WSNs) in street lighting systems. This research explores the design and implementation of a smart street lighting system (SSLS) integrated with WSNs to enhance energy efficiency and enable real-time fault detection. The proposed system utilizes a network of wireless sensors to monitor ambient light levels, vehicular movement, …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 1, 2025 · pp. 24–38 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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AI and IoT in Sustainable Agriculture: A Review
Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) integration have transformed the world of sustainable agriculture, presenting new ways of resource optimization, increasing crop yields, and making environmental sustainability more accessible. The current literature review analyzes the applications of AI and IoT in three significant agricultural systems: aquaponics, hydroponics, and poultry farming. By critically analyzing recent studies, this paper emphasizes how deep learning- enabled computer vision techniques allow for the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article
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IoT-Based Adaptive Irrigation Solution for Smart Farming
Abstract: Facing escalating global challenges such as water scarcity and unpredictable weather conditions, precision farming emerges as a crucial solution for enhancing agricultural productivity and sustainability. This paper introduces a smart irrigation system which employs IoT-based technology, integrating sensors and a designed to enhance water efficiency and boost agricultural productivity. The system leverages live data related to soil moisture and temperature, cloud cover, and precipitation, coupled with a cloud-based infrastructure using …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 17–24 Read article
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AI in Pharmacy Automation: A Review of Innovations in Robotics, Their Ethical Implications, and Impact on Workflow and Workforce
Abstract: The pharmacy profession has witnessed a paradigm shift with the integration of robotics and artificial intelligence (AI) in automation. Traditional practices that relied heavily on manual dispensing, paper documentation, and technician labor are now being augmented or replaced by robotic dispensing systems, sterile compounding machines, and predictive AI algorithms. These innovations enhance safety, improve efficiency, and reduce errors, while also raising complex ethical questions related to workforce displacement, liability, and …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 1, 2026 · pp. 01–07 Read article
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IoT-Based Automated Crop Protection System for Smart Farming
Abstract: The development of current technological advancements produces expanded capabilities for agricultural farming production alongside pest management techniques. The Automatic Crop Protection System requires an Arduino controller and Blynk IoT application for monitoring and managing essential environmental parameters including temperature along with humidity as well as soil moisture and pest behavior. Real-time environmental and soil data obtained by the suggested system's sensor array gets analyzed and controlled by an Arduino controller. …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 1–8 Read article
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Use of Intelligent Control Systems to Manage Traffic Effectively and Productively
Abstract: Intelligent control system is the advanced technology in which the collected data is provided to A.I. and with the help ofvarious methods like machine learning, neural networks, Bayesian probability, fuzzy logic the solution to a particularproblem is found.In a country’s growth the traffic management plays a great role as the maximum industries depends on the highways orroads and when it is well planned it can reduce the commute time and …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 1, 2023 · pp. 22–27 Read article
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A New Systematic Approach of Using SVM, KNN, PNN and CNN to Achieve Higher Accuracy for Classification and Recognition of Music Genre
Abstract: In order to overcome challenges like finding songs that are similar, figuring out which cultures would enjoy particular music, conducting surveys, and using music as therapy, classification and recognition of music genres are essential. The expansion of music-related content available online has created new opportunities for the development of music referral systems, which support user communities in searching, finding, sharing, and producing digitally. Our aim is to develop a systematic …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 1–11 Read article
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Fuzzy Modeling to Specify Various Machining Parameters in Electrical Discharge Machining (EDM) of INCONEL625 Using Copper Electrode
Abstract: Condition monitoring of the machining process is very important in today’s precision manufacturing, especially in the electrical discharge machining (EDM). This paper shows a fuzzy-based algorithm for prediction of material removal rate (MRR) and tool wear ratio (TWR) in the electrical discharge machining (EDM) processes. In this system peak current (Ip), voltage (V) and duty cycle (D) are the input parameters and output parameters are MRR and TWR. The proposed …
Published in Trends in Mechanical Engineering & Technology · Vol. 6, Issue 1, 2016 · pp. 35–42 Read article
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Digital Farming: A Review on Agricultural Technologies and Data- Driven methods
Abstract: The article provides a comprehensive overview of the digitalization of farming and explores the technologies and data-driven approaches revolutionizing modern agriculture. The study examines the role of digital technologies such as precision agriculture, Internet of Things (IoT), artificial intelligence (AI), and data analytics in transforming various aspects of farming practices, including crop management, livestock production, and farm operations. The article reviews the application of sensor technologies for real-time monitoring of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 12, Issue 1, 2023 · pp. 9–15 Read article
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Review on Weather Events Forecasting Using Data Mining Algorithms
Abstract: Weather events forecasting is the most imperious and stimulatingfunctioning responsibilities supported by meteorological departments worldwide. Amongst all weather events, rainfall plays the most authoritative role in the life of human beings. Human society to a great level depends upon its frequency at various scales. Data mining is a process that mechanically abstracts useful patterns from a given data set. Thecommon algorithms and techniques for rain forecasting like Artificial Neural Networks …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 1, 2018 · pp. 12–22 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 26–40 Read article
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DISEASE PREDICTION SYSTEM USING MACHINE LEARNING
Abstract: Machine learning (ML) is a rising field. It already plays an important role in many fields, with projects of all sizes showing its positive impact. One such use of machine learning algorithms is in the healthcare field. Medical facilities need to be improved in order to make better decisions about patient diagnosis and treatment options. In this paper, we attempt to use the performance of Machine learning equipment in health …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 2, 2021 · pp. 14–18 Read article
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Developing a Statbot for Predictive Analytics
Abstract: Automatic Statbot for predictive analytics is the future of the data analytics world where we would have trillions of unprocessed data which needs to be structured, preprocessed, and to be converted into a form which could be used up by the sophisticated users like data scientists, data analysts, business analysts, etc. The Statbot interacts with its user/client in a friendly manner and asks for the dataset to be used for …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 2, 2021 · pp. 22–33 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article
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Abusive Language Detection using ML
Abstract: Detection of abusive language in online content has become a serious problem in recent years. Abusive language is an expression that carries grimy phrases each withinside the context of jokes, threat, vulgar intercourse conservation, or to disrespect someone. Nowadays many people post toxic comments in the social media such as Facebook, Twitter, etc. Many researches have tried to do it using the regular expression and blacklists but this is not …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 3, 2021 · pp. 1–7 Read article
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Prediction of Various Optimal Solutions for Desirable Performance Parameter of Non-edible Oils-based Biodiesel
Abstract: The use of energy has expanded a ton by virtue of the modification in the way of life with the progression of masses. This consistent expansion of energy request began the states of the fossil oil deficiency, regular effects for example nursery impact, an Earth-wide temperature boost and so on. Oil based products are restricted assets of energy; from now on, it is must to look for an elective asset …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 14, Issue 1, 2024 · pp. 25–29 Read article
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Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 Read article
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Enhanced Diabetes Prediction: A Comparative Study of Machine Learning Models
Abstract: Excessively high blood glucose levels lead to diabetes, a condition that can be better managed with early detection, resulting in a longer life and improved health. Machine learning models are essential tools in diagnosing diabetes, especially when trained on appropriate and relevant datasets. In this study, a combination of ensemble methods and nine distinct machine learning algorithms were utilized to develop a predictive model for diabetes diagnosis based on a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article