Adaptive AI-Driven Microgrid Control for Real Time Integration of Decentralized Renewable Energy in Emerging Industrial Zones
As localized energy systems, microgrids provide a viable way to solve problems with energy dependability and access in rural and isolated locations. These regions often have inadequate and unstable grid infrastructure, which restricts their access to energy. Artificial Intelligence (AI) improves the overall performance, flexibility, and efficiency of microgrid systems. AI ensures a steady and dependable power supply by enabling predictive maintenance, optimal load forecasting, energy storage management, and renewable energy resource optimization. AI may help microgrids anticipate system faults, better control energy consumption, and prolong the life of vital parts. Additionally, AI ensures the sustainability of microgrids in resource-constrained places by optimizing the usage of renewable energy sources like solar and wind. Successful case studies from places like the US, India, and Africa have shown the promise of AI-enhanced microgrids in raising the standard of living for marginalized areas, despite obstacles like data infrastructure and upfront installation costs. Microgrids have a bright future thanks to developments in artificial intelligence (AI), which might increase electricity availability and promote economic growth in rural and isolated regions of the world.
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An Intelligent Child Safety System Using GPS and GSM Technology
Wearable tracking gadget that school-age children can wear is the topic of this paper. It doesn't need any pricy technology to operate. This technology is usable by persons of all educational levels. It has got two buttons one is alert button and another is panic button The major objective of this gadget is to ensure that the youngster may contact their parents in an emergency. The alert button allows the child to notify their parents of an emergency and provide their current location. For communication, the current technology includes Bluetooth, WI-FI, and RFID. It is hard to communicate across a great distance with these technologies because they only have a narrow range of coverage. Also they are not that accurate. This device solves the issue by utilizing GSM technology. Parents do not need to submit any special code to the device to determine the child's location's latitude and longitude. If a child is in any emergency situation and wants his/her parents to know their current exact location. If a child feels uneasy, there are two methods to let the parents know. The cell phone of the parents or guardian receives the alarm message via SMS by pressing alert button and if the child wants to communicate to parents immediately, a call can also be made via this device using the panic button and the child can talk to the parent in real time.
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Change Detection in Synthetic Aperture Radar (SAR) Images
This paper presents change detection approach for synthetic aperture radar images based on log and mean ratio operators, image fusion and a novel fuzzy local information c means Clustering algorithm. The two multi-temporal SAR images are subjected to ratio operators. The log ratio operator is used to produce the difference image with enhanced low intensity pixels. The mean ratio operator suppresses the unchanged region and improves the homogeneity of the changed region. The difference image is then subjected to image fusion. To improve the intensity of the background pixels Wavelet based image fusion technique is used. The fused image is then subjected to a novel fuzzy algorithm which is Reformulated Fuzzy Local Information C Means Clustering Algorithm. Finally the total number of pixels varied from the difference image is calculated. The kappa and Percentage of correct classification values are more than other algorithms.
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Design and Execute a Real Time Distant Monitoring System
This paper is based on a real time embedded system using ARM7 processor LPC2138 to build a system that helps in achieving remote monitoring of patient's physiological parameters such as Body Temperature, Pulse Rate, Oxygen Saturation in blood and Electronic Cardiogram. If any of the patient's parameters go out of the optimum limits of the human body then an alert SMS is sent to the doctor using a GSM interface and the buzzer is activated on the patient's side to alert the patient's caretaker. The system comprises of low cost transducers for acquiring the parameters and uses MATLAB software to build the GUI for displaying the ECG of the patient on a computer. This system eases the need to keep a patient requiring continuous monitoring at the hospital. The monitoring is achieved by allowing the patient to stay at home.
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Digital Media Based Spread Spectrum Hidden Data
Hiding the information is a vital issue in the 21st century in the field of Data Communication security .It is an important issue because the virtual and digital information transmission faces critical setbacks due to hacking and hackers threats. The transmission of information via the Internet may expose it to detect and theft. So data embedding technologies are developed to provide personal privacy, commercial and national security interests. In this work we consider the problem of extracting blindly data embedded over a wide band in a spectrum (transform) domain of a digital medium (image, audio, video).We develop a novel multicarrier/signature iterative generalized least-squares (M-IGLS) core procedure to seek unknown data hidden in hosts via multicarrier spread-spectrum embedding. Here the original host and the embedding carriers both are assumed as not available. Experimental results shows that the proposed algorithm can achieve recovery probability of error close to what may be attained with known embedding carriers and host autocorrelation matrix.
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Machine learning based identification of digitally modulated signals
The automatic identification of the modulation type of a signal at the receiver is a major task of an intelligent receiver, such as software defined radio (SDR), which is used in different communication systems. With no knowledge of the transmitted data, recognition of the modulation type is a difficult task. A communication system, in which receiver is designed based on Machine learning is trained to detect the message using statistical parameters. In this work, machine learning algorithm is developed for identifying 6 different modulated signal types at the receiving end. MATLAB tool is used to generate different modulated signals. Identification of modulation type is done by analyzing different statistical features such as normalized PSD, kurtosis and sum-fft which are calculated using the sampled version of received signal. The algorithm is tested for different frequency and amplitude signals at the receiving end and results are tested for correctness.
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Optimal Modeling of Grid Connected DC coupled PV/Hydro Hybrid power System
The sustainable power source systems (RESs) are an appealing alternative to energize the group as they are condition amicable, free of cost, and all-overrunning. The effectiveness of these vitality systems is low and can be enhanced by coordinating them in parallel. In this paper, hydro (7.5?kW) and PV (10?kW) are taken as RESs and associated with the utility grid. Because of the discontinuous idea of both the hydro and photovoltaic energy sources, utility grid is associated with the system for guaranteeing the ceaseless power stream. The hydro power generation system uses the 3-phase synchronous machine and converters. The AC/DC/AC converter is used as interface to connect the hydro turbine to the utility grid to adjust the generated voltage to the utility grid voltage. The solar generation system is the combination of PV array, boost converter, and solar inverter. The control of both the hydro and solar power plants is provided through the constant current controller. The analysis has been done to verify the existence of the proposed system. Results demonstrate that the proposed system is able to be put into service and can feed the community.
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Optimization of transmission lines loading in TNEP using improved discrete honey bee mating optimization algorithm
Transmission Network Expansion Planning (TNEP) is a basic part of the power system planning that verifies where, when and how many new transmission lines should be added to the network. In this paper, expansion planning has been implemented by merging lines loading parameter in the TNEP problem using an improved Discrete Honey Bee Mating Optimization (DHBMO) algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. DHBMO algorithm combines the power of genetic algorithms and simulated annealing with a fast problem specific local search heuristic to find the best possible solution within a reasonable computation time. For this reason, the potential of the proposed approach for optimal solution of TNEP problem has been investigated and tested on the Garvers network and a real transmission network in Iran in comparison with the Discrete Particle Swarm Optimization (DPSO) method. The results evaluation show that the using the proposed DHBMO based method, the expansion costs is significantly reduced and the network adequacy is increased considerably than the DPSO algorithm. Also, regarding the convergence curves of both approaches, it can be seen that precision of the proposed algorithm to solve the TNEP problem is more than DPSO one.
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Performance analysis of high resolution images using interpolation techniques in multimedia communication system
This paper presents various types of interpolation techniques to obtain a high quality image The difference between the proposed algorithm and conventional algorithms (in estimation of missing pixel value) is that if standard deviation of image is used to calculate pixel value rather than the value of near most neighbor, the image gives the better result .. The proposed method demonstrated higher performances in terms of PSNR and SSIM when compared to the conventional interpolation algorithms mentioned.
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A Review of Dental Biometrics from Teeth Feature Extraction and Matching Techniques
Biometric is a tool of identification that has been broadly used in many applications. A biometric identification system is based on physical characteristic. Dental biometrics has emerged as vital biometric information of human being on account of its stability, invariant nature and uniqueness. It utilizes dental photograph and dental radiograph for human identification because it provides information about teeth including tooth contour, relative position of neighboring teeth and shapes of dental work like crown, fillings and bridges. A biometric identification system is based on physical characteristics such as face, fingerprint, palmprint, fingerprint, eyes (iris, retina ) and DNA. However, many of those characteristics are only suitable for ante mortem identification when a person to be identified is still alive. They cannot be used for post mortem identification specially in such cases of decay or severe body damage caused by fire or collision, due to this dental biometrics plays an important role in human identification and post mortem identification. This paper address review of such different techniques used in dental biometrics.
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