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Smart Agriculture-Based Food Quality Analysis with Healthcare Security System Using Cloud Machine Learning Model

Remote Sensing in Earth Systems Sciences 2024年第4期7卷 389-398页

作者： Vaithianathan, V. Rebecca, B. Begum, M. Fathima Sundarraj, Antony Allwyn Kumar, M. Prema Kiran, Ajmeera Department of Electronics and Communication Engineering Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Chennai 603110 India Department of Computer Science and Engineering Marri Laxman Reddy Institute of Technology and Management Hyderabad Telangana Dundigal 500043 India Assistant Professor Department of Computer Science and Engineering (Cyber Security) Madanapalle Institute of Technology and Science Andhra Pradesh-517325 Madanapalle India Department of Food Technology Sri Shakthi Institute of Engineering and Technology Coimbatore Tamilnadu Coimbatore India Dept. of ECE Shri Vishnu Engineering College for Women (A) Andhra Pradesh Bhimavaram 534202 India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

The primary sector of our Indian economy is agriculture. Today’s world’s most important and vital industries are agriculture and irrigation. Information and communication technology must be used in our agriculture sectors in order to support farmers and agriculturalists in improving their practices across the entire crop-growing and post-harvest processes. It is still challenging to define processed food, even in light of mounting research that suggests consuming more ultra-processed food has negative health effects. This research proposes novel technique in smart agriculture model based on cloud machine learning in cloud machine learning and healthcare system. By leveraging IoT and cloud-based data to create data-driven product decisions, cloud computing in agriculture can assist farmers with smart agriculture practices. Here, the input has been collected as food quality based on smart agriculture using a cloud model as well as processed for noise removal and normalisation. Then, based on this data, the healthcare security system has been analysed using reinforcement adversarial stacked encoder with Markov fuzzy algorithm. The experimental analysis has been carried out for various food quality datasets in terms of training accuracy, random precision, normalised correlation ratio, F-1 score, and AUC. The proposed technique achieved training accuracy of 96%, F-1 score of 94%, random precision of 97%, normalised correlation ratio of 93%, and AUC of 92%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Adversarial stacked encoder Cloud machine learning Cloud machine learning Healthcare system Smart agriculture

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Deep Reinforcement Learning Based Grid-Forming Inverter

Deep Reinforcement Learning Based Grid-Forming Inverter

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ebrahim Balouji Karl Bäckstrüm Tomas McKelvey Dept. of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Dept. of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden

This research work introduces Deep Deterministic Policy Gradient (DDPG), a type of Reinforcement Learning (RL), for grid modeling, estimating voltage and phase angle, and control method for grid-forming inverters. The aim is to develop a grid-forming inverter that sets the voltage level and frequency of the grid and mitigates voltage dips originating from faults and frequency deviation fluctuations. Unlike conventional methods for estimating setpoints for the controller loops, we do not need several chains of estimation tools such as Fast Fourier Transform (FFT), Synchronous Reference Frame (SRF), or lowpass filters. With the DDPG, we also optimize the phase lock-loop (PLL) and accurately deliver the angle for the actuation part of the inverter to generate the given reference signal. The developed method does not need exhaustive tuning of parameters such as coefficients of PID controllers and lowpass filters. We observe that the proposed method has a faster response time than the PID-based control unit (15ms compared to 50ms) for the grid-forming inverter in the case of compensating voltage dips. We also observed that the DDPG-based grid-forming inverter is more efficient in compensating continuous voltage variations and frequency deviations than a trivial PID-based version.

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Leveraging UAV technology for Enhanced Disaster Management: Innovations and Applications

Leveraging UAV Technology for Enhanced Disaster Management: ...

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2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Upadhyay, Govind Murari Vats, Prashant Shanker, Surabhi Bhushan, Saloni Mittal, Sonu Mandot, Manju Manipal University Jaipur Dept. of Computer Application Rajasthan Jaipur India Manipal University Jaipur School of CSE Dept. of CSE Rajasthan Jaipur India K.R. Mangalam University School of Engineering & Technology Dept. of CSE Sohna Road Haryana Gurugram India Chhatrapati Shivaji Maharaj University Dept. of Computer Science/IT Maharashtra Panvel India Amity Institute of Information Technology Amity University Noida Dept. of CSE Uttar Pradesh India J. R. N. Rajasthan Vidyapeeth University Dept. of Computer Science/IT Rajasthan Udaipur India

ISBN: (纸本)9798350385199

Unmanned Aerial Vehicles (UAVs) have substantially advanced the sector by providing improved real-time monitoring, data collecting, and situational awareness capabilities when integrated into disaster management techniques. This study examines the creative uses of unmanned aerial vehicles (UAVs) in disaster relief, emphasising how they may speed up reaction times and increase operational effectiveness in emergency situations. With an emphasis on their usefulness in human detection, damage assessment, and coordination efforts, we propose a thorough framework that describes the design, deployment, and evaluation of UAV systems customised for catastrophe situations. The study shows how UAVs may be used to enhance processes of decision-making and enable more efficient recovery and catastrophe response through instances and quantitative evaluation. The results demonstrate how UAV technology may revolutionise conventional disaster management procedures and provide insightful information for future studies and real-world applications in the field. © 2024 IEEE.

关键词： Disaster prevention

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Design and simulation of band stop plasmonic filter with high quality factor and enhanced optical performance

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Optik 2025年 334卷

作者： Shams, Amirhossein Kaatuzian, Hassan Shafagh, Sara Gholinezhad Photonics Research Laboratory Dept. of Electrical Engineering Amirkabir University of Technology Tehran Iran

In this paper, we present the design and performance of a band-stop plasmonic filter incorporating a triangular resonator and a central circular cavity within a Metal-Insulator-Metal (MIM) waveguide configuration. The filter operates based on Surface Plasmon Polaritons (SPPs), which are excited at the metal-dielectric interface, allowing for a compact design with excellent optical performance. The filter design was optimized through a combination of numerical simulations using the Finite Difference Time Domain (FDTD) method and theoretical analysis. The simulation results indicate that the filter achieves a high-quality factor of 272 at a resonance wavelength of 818 nm and a cavity width (d) of 35 nm, significantly outperforming previously designed filters. Additionally, the paper presents a detailed comparison of the plasmonic performance of silver and gold, examining their effects on the quality factor, transmission spectrum, resonance wavelength, and overall optical performance. The results highlight that the choice of material plays a crucial role in optimizing the filter's characteristics, as silver demonstrates a higher-quality factor and sharper resonance compared to gold. The filter's high-quality factor provides excellent wavelength selectivity and suppresses unwanted interference effectively, ensuring efficient performance. Moreover, the proposed structure exhibits a small full width at half maximum (FWHM) and tunable resonance wavelengths through precise control of geometric parameters such as cavity dimensions and resonator shape. These tunable characteristics make the filter highly suitable for advanced photonic applications, including optical filtering, high-speed communication systems, and biosensing. The significant results of this study confirm that the proposed plasmonic filter structure is a promising candidate for future nanophotonic systems, where high efficiency and precise wavelength control are essential. © 2025 Elsevier GmbH

关键词： MIM devices

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A Satisfibility based Watermarking Approach for Hardware Security in High Level Synthesis

A Satisfibility based Watermarking Approach for Hardware Sec...

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IEEE India Conference (INDICON)

作者： Ashwin Cs Vipul Poddar Suchismita Roy Dept. of Computer Science & Engineering National Institute of Technology Durgapur India Dept. of Electrical Engineering National Institute of Technology Durgapur India

In today’s world Time-To-Market (TTM) plays a very important role in the success of any given chip. To reduce the TTM, many manufacturers rely on reusable IP cores. These reusable Intellectual Property(IP) cores may come with a lot of unforeseen security issues related to reliability and verifiable point of origin. This paper presents a way of watermarking to reduce these security threats by embedding the designer’s watermark into an IP design at High Level Synthesis (HLS) stage. A boolean Satisfibility (SAT) based approach is proposed which has no additional area and performance overhead.

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Feature Extraction Based Acoustic Signal Detection in a Cost Effective Φ-OTDR System

Feature Extraction Based Acoustic Signal Detection in a Cost...

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International Conference on Microwave, Optical and Communication engineering (ICMOCE)

作者： Shruti Verma Jimson Mathew Sumanta Gupta Dept. of Electrical Engineering Indian Institute of Technology Patna India Dept. of Computer Science and Engineering Indian Institute of Technology Patna India

The paper presents an experimental demonstration of acoustic signal detection in a phase-optical time domain reflectometer (Φ-OTDR) system based on feature extraction. A commercially available off-the-shelf distributed feedback (DFB) laser is used as a light source with a minimum of 25kHz of linewidth. Also, a low sampling rate (60MS/s) data acquisition (DAQ) system is used to collect the backscattered traces. Using the digital signal processing (DSP) technique, the noisy signal from the Φ-OTDR system is processed to extract the different features of the signal. The location of the acoustic signal source is identified based on variance along the fiber length. Besides, power spectral density at that perturbed location is estimated to determine the acoustic signals frequencies. Using this low cost experimental set-up, the location of the acoustic signal source having 100Hz, 125Hz, and 150Hz frequencies were successfully detected over a 1 km of fiber length.

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Moth flame optimization algorithm for efficient feature selection and hybrid classification technique for intrusion detection system

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Multimedia Tools and Applications 2025年 1-21页

作者： Keerthanarani, U. Selvakumar, V. Singaravelan, S. Raja, S. Edwin Thenmozhi, K. Shunmugam, D. Arun Dept. of Computer Science and Engineering P.S.R Engineering College Sivakasi India Dept.Of Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R & d Institute of Science and Technology Chennai Avadi India Dept. Of Computer Science and Engineering Coimbatore Institute of Engineering and Technology Coimbatore India Dept. Of Electronics and Communication Engineering P.S.R Engineering College Sivakasi India

The rapid expansion of the Internet of Things (IoT) brings numerous benefits but further presents fresh difficulties, especially in terms of security. The distributed and interconnected nature of IoT devices makes them susceptible to various security threats. An Intrusion Detection System (IDS) plays a crucial role in safeguarding IoT networks by monitoring, detecting, and responding to potential security incidents. The Internet of Things (IoT) connects billions of devices, sensors, and systems, transforming industries and everyday life. However, this extensive interconnectivity also introduces significant security risks, making Intrusion Detection Systems (IDS) a critical component for safeguarding IoT environments. Feature selection is a crucial aspect of building effective Intrusion Detection Systems (IDS). Selecting relevant features not only helps in achieving better classification accuracy but also contributes to reducing false alarm rates. In the proposed system a moth flame optimizer is utilized to select the efficient features from the dataset, overall accuracy of over 97%. Further it is classified employing Random Forest and J48 classifier which attains high classification accuracy and low false alarm rate. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Feature Selection

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Design, Analysis, and Economic Study of Solar Rooftop PV Systems in Metro Rail Stations in Bangladesh

Design, Analysis, and Economic Study of Solar Rooftop PV Sys...

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International Conference on electrical engineering and Information & Communication technology (ICEEICT)

作者： Rahat Redwan Md. Sabid Khan Mohtasim Sadman Zannatul Mifta Mahmudul Hasan Nahid-Ur-Rahman Chowdhury Dept. of Electrical and Electronic Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh Dept. of Electrical and Electronic Engineering Rajshahi University of Engineering and Technology Rajshahi Bangladesh Dept. of Electrical and Electronic Engineering Northern University Bangladesh Dhaka Bangladesh

ISBN: (数字)9798350385779

ISBN: (纸本)9798350385786

Dhaka, the densely populated capital of Bangladesh, is addressing urban intervention challenges with a Mass Rapid Transit (MRT) system to cater to its growing population's transportation needs. The metro rail project requires 160 MWh of electricity daily. As energy demand rises in emerging countries, ensuring energy security is crucial. This study focuses on a rooftop solar PV grid-connected power system on metro rail station rooftops to address the energy demand. It delves into the design aspects and evaluates the techno-economic and environmental performances. The performance test of the rooftop solar PV system was simulated using PVsyst 7. From this project CO 2 emissions savings over the 25-year project lifetime, with a total of 7585.929 tons saved per station. Per year 303.437 tCO 2 and per kW 12.653 tCO 2 saved from one metro station. The solar power project in question involves a total installation cost of 4,25,00,000 BDT (equivalent to 3,80,000 USD). With a commitment to sustainability, the project aims to generate a significant amount of clean energy, producing a total of 10.7 gigawatt-hours (GWh) annually. This metrics collectively affirm the viability of the system as an effective solution for addressing energy needs, concurrently diminishing reliance on fossil fuels, and fostering the adoption of sustainable energy practices.

关键词： Rails Measurement Costs Electricity Transportation Solar energy Software

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Comparative Survey of Various Intelligent Methods for Breast Cancer Diagnosis and Prognosis 14

Comparative Survey of Various Intelligent Methods for Breast...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Mondal, Manik Dasgupta, Sudakshina Bhattacharya, Indrajit Govt. College of Engg. & Textile Tech. Dept. of Computer Science & Engineering Serampore India Govt. College of Engg. & Textile Tech. Dept. of Information Technology Serampore India Kalyani Govt. Engineering College Dept. of Computer Applications Kalyani India

ISBN: (纸本)9798350335095

Cancer remains a major contributor to mortality rates across the globe, causing nearly 10 million fatalities in 2020. Among all cancer types, breast cancer has the highest incidence, around 2.26 million cases reported across the globe by the World Health Organization. In the last few years, breast cancer was diagnosed in approximately 2.3 million people and caused around 685,000 deaths. In this paper, our investigation entails executing a statistical scrutiny of the worldwide proliferation of breast cancer, as well as delving into various machine learning and deep learning techniques for detecting breast cancer, along with their constraints and intricacies. Additionally, we have proposed a hybrid Machine Learning (ML) approach for detecting breast cancer with utmost accuracy, which streamlines the assessment procedure presently employed by radiologists in screening mammograms. © 2023 IEEE.

关键词： Medical imaging

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On Rejecting Low Quality Images to Improve Deep Smartphone Wound Assessment 22

On Rejecting Low Quality Images to Improve Deep Smartphone W...

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22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023

作者： Ditthapron, Apiwat Agu, Emmanuel O. Pedersen, Peder Lindsay, Clifford Tulu, Bengisu Strong, Diane Computer Science Dept. WorcesterMA United States Electrical and Computer Engineering Dept. WorcesterMA United States Univ. Massachusetts Medical School Department of Radiology WorcesterMA United States WorcesterMA United States

ISBN: (纸本)9798350345346

Automatic assessment of wounds using smartphones can facilitate the tracking of healing progress outside the clinic. Prior work proposed SS-PMG-EfficientNets, a state-of-the-art, multi-scale, convolutional neural network architecture for accurate wound assessment. However, the model was previously only trained and evaluated on high-quality wound images captured in controlled environments. This study systematically evaluated the effects of low-quality images on SS-PMG-EfficientNets, finding that the model's performance and consistency are reduced when input wound images are blurry or captured in adverse lighting (too bright or too dark), two factors previously identified as the most prevalent issues in crowdsourced images. Specifically, SS-PMG-EfficientNet was first trained on three high-quality wound datasets containing images labeled with Photographic Wound Assessment Tool (PWAT) wound healing scores, stages of pressure injury wounds, and wound types, respectively. The model was then evaluated on a test wound dataset that was augmented with real-world image luminance, blur, and image compression effects and found that wound assessment accuracy decreased by up to 27%. To improve model performance, we propose a method for instant image quality assessment on the smartphone, enabling low-quality wound images to be rejected immediately after image capture so that the nurse or patient can be prompted to recapture the image. Our evaluation of the proposed image quality assessment and rejection method showed that it increases average accuracy from 73 % to 87%. © 2023 IEEE.

关键词： Chronic wounds Image quality assessment Smart health

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