Papers by Pravin Kshirsagar
Wireless Communications and Mobile Computing
Mobile network nodes are trustworthy nodes; the data access in transmitting and receiving the dat... more Mobile network nodes are trustworthy nodes; the data access in transmitting and receiving the data packet is not efficient in different network procedures. The malicious nodes are available in routing path making the packet loss, in packet transmission for time instance. Since the regular mobile network must not verify every mobile node approved else illegal, subsequently the reserved level of nodes also was not considered, to injure the packet transmission procedure by link failure called connection loss. It minimizes the transmission rate and network lifetime and improves packet latency and energy usage. The proposed novel link establishment communication (NLEC) technique is used to find the dependable routing path against intruder node available in the network. This scheme selects genuine node for routing path production, by using the node reward with dependence level estimating algorithm to compute every node trust level and resource range, to disconnect higher trust level node ...
A multi-model unified disease diagnosis framework for cyber healthcare using IoMT- cloud computing networks
Journal of Discrete Mathematical Sciences and Cryptography
The past several decades of research into machine learning have been of great assistance to human... more The past several decades of research into machine learning have been of great assistance to humanity in the diagnosis of a variety of ailments using various forms of automated diagnostic procedures. Machine learning, combined with smart health devices, has improved health monitoring, timely diagnoses, and treatment. This paper introduces a unified disease diagnosis framework, integrating cloud computing, machine learning, and IoT. The framework has three layers: physical (collects patient data), fog (intermediate layer with a domain identification unit to determine input and diagnosis type), and transmission (cloud server with a disease detection unit). The performance evaluation shows the robustness and efficiency of the model as compared to state-of-art models.
Sustainability
Microgrids are an essential element of smart grids, which contain distributed renewable energy so... more Microgrids are an essential element of smart grids, which contain distributed renewable energy sources (RESs), energy storage devices, and load control strategies. Models built based on machine learning (ML) and deep learning (DL) offer hope for anticipating consumer demands and energy production from RESs. This study suggests an innovative approach for energy analysis based on the feature extraction and classification of microgrid photovoltaic cell data using deep learning algorithms. The energy optimization of a microgrid was carried out using a photovoltaic energy system with distributed power generation. The data analysis has been carried out for feature analysis and classification using a Gaussian radial Boltzmann with Markov encoder model. Based on microgrid energy optimization and data analysis, an experimental analysis of power analysis, energy efficiency, quality of service (QoS), accuracy, precision, and recall has been conducted. The proposed technique attained power anal...
This paper presents hinge-shaped conductor backed (CB) monopole antenna designed to operate at 5.... more This paper presents hinge-shaped conductor backed (CB) monopole antenna designed to operate at 5.8 GHz frequency in the frequency range of 4 to 8 GHz with reflection co-efficient below − 29 dB with impedance as 50Ω. The wearable flexible antenna is of the dimensions 10mm X 10 mm. An array of 4 antenna model has also been tested for analysis. Kapton polyimide (substrate) and copper materials were used for the fabrication process. Flexible monopole antennas on a Kapton polyimide are designed to be in contact with the breast tissues with respective dielectric models. The flexible Kapton material with antennas is to be placed on the breast phantom which makes the detection easier. The proposed model is eco-friendly, cost effective and reliable product to be readily launched.
Prediction of breast cancer based on computer vision and artificial intelligence techniques
Measurement
Deep learning technique for patients healthcare monitoring using IoT body based body sensors and edge servers
Journal of Intelligent & Fuzzy Systems
Architectural, cognitive, and service layers are the three components that come together to form ... more Architectural, cognitive, and service layers are the three components that come together to form the system as a whole. The data that is acquired by the instruments at the application layer is processed by the system that is in charge of the network. The conceptual layer, which is where edge sensors are put, is responsible for managing radio resource management and intersensor connections in order to solve the issues raised by the physical layer about increasing power consumption and increased latency. In response to the processed data provided by the logical layer, the application layer will make judgements. The key objective is to lower prices so that they are more accessible to regular people. Patients will not only be able to maintain their financial stability, but they will also have easy access to private therapy. This research presents a solution based on the Internet of Things (IoT), which will simplify the usage of a generally complicated medical device while allowing you t...
Machine learning algorithm for improving the efficient of forgery detection
AIP Conference Proceedings, 2022
Computational Intelligence and Neuroscience
Diabetes problems can lead to a condition called diabetic retinopathy (DR), which permanently dam... more Diabetes problems can lead to a condition called diabetic retinopathy (DR), which permanently damages the blood vessels in the retina. If not treated, DR is a significant cause of blindness. The only DR treatments currently accessible are those that block or delay vision loss, which emphasizes the value of routine scanning with high-efficiency computer-based technologies to identify patients early. The major goal of this study is to employ a deep learning neural network to identify diabetic retinopathy in the retina’s blood vessels. The NN classifier is put to the test using the input fundus image and DR database. It effectively contrasts retinal images and distinguishes between classes when there is a legitimate edge. For the resolution of the problems in the photographs, it is particularly useful. Here, it will be tested to see if the classification of diabetic retinopathy is normal or abnormal. Modifying the existing study’s conclusion strategy, existing diabetic retinopathy tech...
Journal of Healthcare Engineering
This article examines distinctive techniques for monitoring the condition of fishes in underwater... more This article examines distinctive techniques for monitoring the condition of fishes in underwater and also provides tranquil procedures after catching the fishes. Once the fishes are hooked, two different techniques that are explicitly designed for smoking and drying are implemented for saving the time of fish suppliers. Existing methods do not focus on the optimization algorithms for solving this issue. When considering the optimization problem, the solution is adequate for any number of inputs at time t. For this combined new flanged technique, a precise system model has been designed and incorporated with a set of rules using contention protocols. In addition, the designed system is also instigated with a whale optimization algorithm that is having sufficient capability to test the different parameters of assimilated sensing devices using different sensors. Further to test the effectiveness of the proposed method, an online monitoring system has been presented that can monitor an...
Identification of people affected from Corona virus using artificial intelligence
RECENT TRENDS IN SCIENCE AND ENGINEERING
Covid-19 diagnostic system using artificial intelligence and machine learning which precisely det... more Covid-19 diagnostic system using artificial intelligence and machine learning which precisely detect likelihood of the Covid-19. The proposed system can detect likelihood of the respiratory diseases, measure oxygen saturation and temperature of the patient. One of its goals is to test the patient for Covid-19 (i.e. pneumonia like symptoms). The system includes a testing stand which consists of respiratory sound recording unit, a pulse oximeter unit, an IR temperature check unit and a computer which consists of a software unit. The respiratory sound recording unit includes stethoscopes mounted inside a pillow on the testing stand which are connected to a microphone module which is further connected to the computer via an audio cable. The pulse oximeter unit includes a pulse oximeter sensor which is mounted on the right arm of the testing stand which is further connected to an OLED display, buzzer and the computer. The IR temperature check unit includes an IR temperature sensor which is mounted on the top arm of the testing stand which is further connected to an OLED display, buzzer and computer. It is to be noted that all the units can be adjusted according to the height of the patient. The software unit includes a machine learning program i.e. Covid-19 diagnostic management system, present in the computer which is connected with all the above-mentioned parameters.
Covid heuristic analysis using machine learning
RECENT TRENDS IN SCIENCE AND ENGINEERING
Infection detection in older person using artificial intelligence
RECENT TRENDS IN SCIENCE AND ENGINEERING
Artificial intelligence based algorithm to support disable person
RECENT TRENDS IN SCIENCE AND ENGINEERING
Sensors
High security for physical items such as intelligent machinery and residential appliances is prov... more High security for physical items such as intelligent machinery and residential appliances is provided via the Internet of Things (IoT). The physical objects are given a distinct online address known as the Internet Protocol to communicate with the network’s external foreign entities through the Internet (IP). IoT devices are in danger of security issues due to the surge in hacker attacks during Internet data exchange. If such strong attacks are to create a reliable security system, attack detection is essential. Attacks and abnormalities such as user-to-root (U2R), denial-of-service, and data-type probing could have an impact on an IoT system. This article examines various performance-based AI models to predict attacks and problems with IoT devices with accuracy. Particle Swarm Optimization (PSO), genetic algorithms, and ant colony optimization were used to demonstrate the effectiveness of the suggested technique concerning four different parameters. The results of the proposed meth...
Countering Dis-information by Multimodal Entailment via Joint Embedding
2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE)
Correction and Estimation of Workout Postures with Pose Estimation using AI
2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE)
Detection of Liver Disease Using Machine Learning Approach
2022 5th International Conference on Contemporary Computing and Informatics (IC3I)
A Review on Application of Deep Learning in Natural Language Processing
2022 5th International Conference on Contemporary Computing and Informatics (IC3I)
A Review on Comparative study of 4G, 5G and 6G Networks
2022 5th International Conference on Contemporary Computing and Informatics (IC3I)
Artificial intelligence based women security and safety measure system
RECENT TRENDS IN SCIENCE AND ENGINEERING
There is much immoral domestic abuse for women across the world. This is accelerated due to the a... more There is much immoral domestic abuse for women across the world. This is accelerated due to the absence of an effective tracking system. This study focused on a female's safety system focused on AI which offers security to women at risk. This framework can automatic and manual respond correctly in crucial circumstances. In order to accurately track the condition of victim and raspberry pi, the proposed device comprises a speech recognition device, Gsm modem and several other detectors, such as pulse detectors and an accelerometer, to monitor the collected information and avoidance or safety measures shall be carried out according to the significance of the problem. In this paper we present a mobile applications, SWMS, which offers an important function should provide emergency assistance. And we use one program and several collar chains artifacts and displays which are in everyday use. The machine is identical to a monitor on the collar with a button as a source, where, when turning on the shouting warning, the electric shock device and the monitor and location details of contacts and the closest police station are enforced for the self-defense intent. Video camera electric shock and streaming live footage are built into shows that serve like a digital technology tool, which we also think can have an impact on women's life. We'll use the Raspberry pi and python platform for execution
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Papers by Pravin Kshirsagar