22 research outputs found

    IoT-Enhanced Public Safety in Smart Environments: A Comparative Analysis Using the Public Safety IoT Test

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    The present study does a comparative analysis to evaluate the efficacy of public safety measures boosted by the Internet of Things (IoT) in various smart settings. The "Public Safety IoT Test" methodology is used in the research to evaluate costs, user happiness, and safety improvement percentages. Smart Surveillance devices showed a noteworthy 35% increase in safety in metropolitan City A, while Wearable Health devices showed a surprising 40% increase in safety in rural Village D. At a cost of 500,000inCityAand500,000 in City A and 10,000 in Village D, these results emphasize the potential of IoT technology to improve public safety and well-being. User satisfaction scores of 4 and 5, respectively, demonstrate the acceptance and efficacy of these devices. Policymakers and urban planners may benefit greatly from this study, which highlights the flexibility of IoT devices in a variety of smart settings and their important role in creating communities that are safer and more resilient

    Sustainability Measures: An Experimental Analysis of AI and Big Data Insights in Industry 5.0

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    In the context of Industry 5.0, this empirical research investigates the concrete effects of artificial intelligence (AI) and big data insights on sustainability metrics. Real-world data analysis shows that during a two-year period, there was a 10% rise in the energy used by solar panels, a 6.7% increase in the energy consumed by wind turbines, and a 6.7% drop in the energy consumed by the grid. Paper trash output was reduced by 14% and plastic waste by 24% as a consequence of waste reduction initiatives. Product quality was maintained by AI-driven quality control, with quality ratings ranging from 89 to 94. Moreover, there was a 6% decrease in carbon emissions from industry, 3.1% from transportation, and 4.6% from energy production. These results highlight how AI and Big Data may revolutionize Industry 5.0 by promoting environmental responsibility, waste reduction, energy efficiency, sustainability, and high-quality products

    Generalized Gravi-Electromagnetism

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    A self consistant and manifestly covariant theory for the dynamics of four charges (masses) (namely electric, magnetic, gravitational, Heavisidian) has been developed in simple, compact and consistent manner. Starting with an invariant Lagrangian density and its quaternionic representation, we have obtained the consistent field equation for the dynamics of four charges. It has been shown that the present reformulation reproduces the dynamics of individual charges (masses) in the absence of other charge (masses) as well as the generalized theory of dyons (gravito - dyons) in the absence gravito - dyons (dyons). key words: dyons, gravito - dyons, quaternion PACS NO: 14.80H

    Role of Serine/Threonine Kinase 11 (STK11) or liver kinase B1 (LKB1) Gene in Peutz-Jeghers Syndrome

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    Peutz-Jeghers syndrome (PJS) is a well-described inherited syndrome, characterized by the development of gastrointestinal polyps and characteristic mucocutaneous freckling. PJS is an autosomal prevailing disease, due to genetic mutation on chromosome 19p, manifested by restricted mucocutaneous melanosis in association with gastrointestinal (GI) polyposis. The gene for PJS has recently been shown to be a serine/threonine kinase, known as LKB1 or STK11, which maps to chromosome subband 19p13.3. This gene has a putative coding region of 1302 bp, divided into nine exons, and acts as a tumor suppressor in the hamartomatous polyps of PJS patients and in the other neoplasms that develop in PJS patients. It is probable that these neoplasms develop from hamartomas, but it remains possible that the LKB1 or STK11 locus plays a role in a different genetic pathway of tumor growth in the cancers of PJS patients. This article focuses on the role of LKB1 or STK11 gene expression in PJS and related cancers

    Causes of Noise Generation & its Mitigation in Transformer

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    Abstract: This paper presents causes of noise generation in transformers and its mitigation. The ministry of environment has specified noise level for different areas i.e. industrial, commercial and residential. In this paper there are three causes of noise generation in transformer i.e. core sound, load sound and sound by cooling fans & pumps. Various methods are suggested in this paper in order to mitigate the sound in transformer

    Smart and Sustainable Surveillance System

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    Safety and security are major concerns in the modern day. People and organizations can employ security mechanisms to safeguard their property for their homes or commercial enterprises. Present security systems involve the utilization of Assorted Sensors in cameras for video surveillance. This paper aims at providing one such idea to ensure the protection and security of one’s property. This technique performs Face Recognition as an authentication procedure when a new face is detected by a snapshot. We propose to present a sensible, smart and sustainable Closed - Circuit Television (CCTV) camera with intrusion detection using the LBPH-Local binary pattern histogram algorithm, SIM-Structural Similarity Index Measure, Haar Cascade Classifier, and TKinter. By utilizing intrusion detection, CCTV cameras record real-time videos and process the video at the time of recording to search out the unwanted people arriving within the surveillance area. Our GUI has different buttons supported with features. Adding DL support would create broad scope in this paper such as with DL we would be able to add up much more functionality. We can have future enhancements on this paper such as creating Portable CCTV, Deadly weapon detection, Accident Detection, Fire Detection

    Sustainability Measures: An Experimental Analysis of AI and Big Data Insights in Industry 5.0

    No full text
    In the context of Industry 5.0, this empirical research investigates the concrete effects of artificial intelligence (AI) and big data insights on sustainability metrics. Real-world data analysis shows that during a two-year period, there was a 10% rise in the energy used by solar panels, a 6.7% increase in the energy consumed by wind turbines, and a 6.7% drop in the energy consumed by the grid. Paper trash output was reduced by 14% and plastic waste by 24% as a consequence of waste reduction initiatives. Product quality was maintained by AI-driven quality control, with quality ratings ranging from 89 to 94. Moreover, there was a 6% decrease in carbon emissions from industry, 3.1% from transportation, and 4.6% from energy production. These results highlight how AI and Big Data may revolutionize Industry 5.0 by promoting environmental responsibility, waste reduction, energy efficiency, sustainability, and high-quality products
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