The aim of this research is to establish a secure method for accessing patients’ personal data and medical records by utilizing RFID tags and a hardware kit, while adhering to industry standards. This system will utilize Web service interfaces to facilitate interoperability with standard Electronic Health Records. The actual level of adoption of RFID technology has fallen short of previous expectations. To provide insight into this matter, this study employs a formal research framework to examine the literature on the use of RFID in healthcare applications. The objective of our research is to identify existing possibilities, potential advantages, and obstacles to the adoption of RFID technology. Our findings indicate that the majority of healthcare providers perceive RFID to be a practical and effective means of patient identification. However, the primary hindrances to widespread implementation of RFID in health care include high costs, technological limitations, and concerns over privacy. Despite the potential benefits of using RFID in clinical practice, more refined RFID systems are required to improve acceptance and ensure appropriate utilization of the technology in health care. A device designed to monitor important COVID-19 symptoms has been introduced. Utilizing off-the-shelf hardware and software components such as basic sensors, general purpose microcontrollers, and mobile devices and peripherals, the device is capable of detecting and tracking changes in body temperature. This enables patients and remote medical staff to receive alerts regarding abnormal symptoms associated with COVID-19 or related illnesses. The device’s underlying concept, including measurement principles, system integration, digital signal processing, and networking, is presented alongside preliminary testing outcomes.

Artificial intelligence (AI) has the capacity to revolutionize the manufacturing sector. Positive effects include things like more output, lower costs, better quality, and less downtime. Large factories are just one group of people who can take advantage of this technology. It is important for many smaller firms to understand how simple it is to obtain high-quality, affordable AI solutions. AI has a wide range of potential applications in manufacturing. It enhances defect identification by automatically classifying faults in a variety of industrial products using sophisticated image processing techniques. Artificial intelligence has various potential applications in manufacturing since industrial IoT and smart factories generate enormous amounts of data every day. To better analyze data and make choices, manufacturers are increasingly using artificial intelligence solutions like deep learning neural networks and machine learning (ML). One common use of artificial intelligence in manufacturing is predictive maintenance.

Robotics is a rapidly evolving technology essential in many industries and a significant pillar for all the following technologies. Selecting the best motor for the ideal robot is a problematic issue if one is developing a robot, especially for industry. Several criteria for arms control, location, and angular and linear movements must be considered when choosing electrical motors for industrial robots. Choosing the suitable motor is a crucial decision in the design of robots that requires careful consideration of factors such as the robot's weight, wheel size, and intended use. Torque, acceleration, and speed must all be considered during the design stage. Industrial robots typically use a range of motor types for various functions. The proposed work uses a stepper motor for high-torque robotic applications and more precise angular movement. The double-ended forward converter is used to operate the stepper motor. For current regulation, loss minimization, and low-power applications, the suggested converter is strongly recommended. This converter increases functionality and has buck. The technology's source is also mentioned: fuel cells. A mathematical model of a double-ended forward converter is presented in this paper. The suggested converter's prototype model's outcomes are compared and verified.

The monitoring of comatose patients is critical for identifying adverse changes in their physiological state and ensuring timely medical intervention. This research presents a novel IoT-based system for remotely monitoring and assessing vital signs in comatose patients. The proposed system utilizes various IoT sensors to measure pulse, respiratory rate, and eye movement, transmitting data to a centralized database and connected devices for real-time monitoring by healthcare professionals and family members. This approach offers a significant improvement over traditional observation methods, which can be time-consuming and prone to human error. By providing up-to-date information about the patient's vital signs and body movements, the IoT-based system enhances the quality of care and improves patient outcomes. This paper discusses the system's characteristics, building blocks, and implementation challenges based on existing research in this area.

As a result of its rapid global spread, cancer has surpassed all other diseases as the top killer of both men and women. The mortality rate for cancer patients is estimated to be between 80 and 85

Underwater Acoustic Sensor Networks, or UW-ASNs, are networks of vehicles and a variable number of sensors that work together to monitor a specific area together. To accomplish this,vehicles and sensors get organized by themselves into an autonomous network which could is capable of adapting to the ocean’s environment. Although underwater communications have been tried since the United States developed an underwater telephone in 1945 to communicate with submarines, underwater networking is a relatively unexplored field. In underwater networks, the typical physical layer technology is acoustic communications. On an honest confront, the radio wavesdiffract at approximate distances throughout the ocean at lower frequencies ranging between 30 Hz -300 Hz, which requires large receiver wires and higher power for transmission. While scattering affects optical waves, they do not have the same high attenuation as sound waves. In addition, pointing the narrow laser beams with extreme precision is necessary for optical signal transmission. Acoustic wireless communications, therefore, serve as the foundation for underwater network links. UWSNs that are dependable are capable of providing the best services for applications in marine engineering that operate in the rapidly changing environment. Wide-ranging applications like underwater ecology, military operations, earthquake prediction, and others are drawing interest in UWSNs. These networks are unique from terrestrial radio networks and face numerous obstacles. In any case, the submerged acoustic correspondence innovation is compelled by the hubs’ constant development, restricted correspondence transmission capacity, and hub energy, which carry extraordinary difficulties to UWSNs.

Semiconductors, petrochemicals, food, and other products for on-site testing and calibration are produced in large quantities using dry-block furnaces. For many years, temperature calibrators have struggled with the accuracy of temperature measurements from dry-block furnaces. The main areas of interest for dry-block furnace research include on-site temperature calibration techniques, stability assessment, and uniformity of temperature distribution. As such, the axial temperature distribution has a major influence on the precision of the dry-block furnace. The most accurate way to calibrate temperature instruments is with a dry-block calibrator. Because of its thermal and thermodynamic qualities, it is used in the metrological calibration of temperature measurement devices, including thermometers, temperature sensors, and other measuring instruments, to keep the temperature of the newborn room between 36 and 37 °C. The system needs to continuously control the temperature within an appropriate range in order to protect premature infants. Another important consideration for premature babies is humidity. The neonatal incubator’s ambient temperature and the air surrounding it are maintained between 70 and 75

One of the renewable energy sources that can be employed in place of traditional energy sources is solar energy. Sun trackers can be used to increase photovoltaic systems’ ability to produce electricity. The design of the control implementation is straightforward and efficient. To demonstrate the effectiveness of this plan, a prototype is created. Experimental verification of the solar tracking’s effectiveness is possible. This work will be a useful resource for applying solar energy in the future. BDHC, which performs DC-DC conversion, is employed in this system to produce energy from solar cells using a single inductor. Battery charging mode is when the remaining energy from the buck-boost converter is used to charge the battery if the system load is less than the amount of energy that was captured. Battery-aided mode, which supplies the load using both the battery and harvested energy, is used when the harvested energy is less than the system load. The crucial charging method is discovered to be the ideal control scheme for maximized power efficiency.

The Use of UPS, Variable Frequency Drives, and Soft Starters is on the Rise. In many continuous plant industries, there is a growing demand for the installation of UPS, Variable Frequency Drives, and Soft Starters. However, these devices are also recognized to generate harmonics that can lead to power quality disturbances, voltage deflection, neutral loading, and a decrease in the lifespan of switchgear. As a result, the need for larger capacity switchgear and increased maintenance costs for distribution devices, such as transformers, also arises. There are several devices available in the market that aim to mitigate harmonic interference, including active and passive filters. Among these, harmonic filters that do not require any system modifications are suitable for industries such as pharmaceuticals, chemicals, agro, food, textiles, and other continuous plant industries. The use of such filters results in a reduction in neutral current, improved power quality, longer lifespan of switchgear, and cost savings in switchgear expenses. In this study, power quality enhancement was achieved by maintaining voltage balancing and reducing total harmonic distortion, using unequal DC sources. The use of MATLAB software was used to conduct simulation work and investigational results were given to validate the theory. This approach reduces initial costs and complexity, making it a suitable solution for industrial applications.

Different medical imaging techniques were used to various different kinds of medical images. It provides the thorough interior composition of the body organs. Radiologist detects the abnormality of the body parts from this image. X-ray, CT, MRI, other tomographic modalities (SPECT, PET, or ultrasound) are the various medical imaging modalities. After image capturing segmentation is the next important process. The segmentation process helps to determine the region of interest partially or automatically. Manual segmentation refers to the partitioning and naming of an image by hand by a human operator or physician. On a three-dimensional volumetric image, segmentation is done slice by slice. Partitioning of medical images is an easy or difficult process based on the presence of artifacts.

VLSI is the process of integrating thousands of transistors into a single chip. VLSI design is mainly used to minimize the interconnecting fabrics area. Among the most extensively utilized sequence syllogisms is the (LFSR), that provides a functional form from its prior state. Memory blocks and XORs make up the traditional LFSR. The (LFSR) is the heart of integrated devices that use randomly generated bits patterns, like as pseudo-random number and pseudo-noise sequencing generators, digitalization clocks, and Created Tests. As a result, fault-tolerant LFSR development is crucial for applications that require dependability. Conventional fault tolerant LFSRs have a sizable percentage of (SPoFs), which means that any error causes the entire project to collapse. To address single goal failure, a novel fault tolerant design for the Fault Tolerant-Linear Feedback Shift Register (FT-LFSR) has been developed, with a drastically decreased number of SPoFs. This work utilizes a new variant of Triple Modular Redundancy (TMR) with additional management components for distinguishing the operating component. TMR (Triple Modular Redundancy) was a very well and widely used spatially duplicate fault tolerance technology. The architecture is particularly tricky in TMR to run a procedure in concurrently, and the result is then analyzed by a largest group mechanism to generate a single output. As a result, in this suggested approach, the probability of single number failures is reduced. Besides its restricted SPoFs and others have of simultaneous faults, empirical studies at Xilinx show that the FT-LFSR is immune to all individual transitory and persistent defects.

Varicose veins are twisted, enlarged veins. Any superficial vein may become varicose, but the veins most commonly affected are those in your legs. Thats because standing and walking upright increases the pressure in the veins of your lower body. The majority of individuals commonly perceive spider and varicose veins as cosmetic concerns, while others acknowledge the potential for pain and discomfort associated with them. Nevertheless, varicose veins can lead to more serious complications. Medical interventions, including procedures like vein closure or removal, as well as various home care treatments, prove effective in managing varicose veins. Approximately, 40 million individuals in the western world are affected by varicose veins, with genetic factors contributing to half of these cases. The prevalence of varicose veins is higher in women, accounting for 55

The Conservative lithography-based VLSI technology has been able to increase processing power and achieve proportionate scaling in feature size. However, present work expose that deterioration of these devices (as a result of vital physical confines of CMOS technology) will head to undesirable consequences such as doping fluctuations, power dissipation, short channel effects and electro-migration failures. These repercussions will cause a decline in a number of parameters, including diffusion barriers, off-state leakage, gate depletion, switching performance, and stray capacitances. Furthermore, it is predicted that the 7 nm channel dimension will mark the conclusion of the CMOS technology's growth process. In order to replace conventional CMOS technology in the near future, extensive nanoscale research has been conducted in recent years. The CMOS technologies can function at frequencies of Tera-Hertz and can attain a consistency of 10 devices/cm2. However, the current strategy of reducing transistor count while maintaining the same design quality may soon be insufficient to overcome the commercial, arhitectural, and physical barriers. A novel c technology that harnesses the advantages of nanoscale physics will have to eplace the MOS transistor. A r plethora of cutting-edge technologies, such as spin transistors, resonant tunnelling diodes (RTDs), carbon nanotubes (CNTs), and single electron transistors (SETs), are being investigated as potential replacements for conventional CMOS technology. Because nanotechnology has unique features that increase at such small feature sizes, it opens up new computational possibilities. When creating ultra-deep submicron circuits and getting around CMOSs limitations, quantum-dot Cellular Automata (QCA) is a nanotechnology that can take the place of CMOS. It is created on various scientific facts, including Effective QCA Designs and Their Applications. The proposed XOR Gate are compared with existing designs in terms of number of cells area and clock cycles. The proposed design is purely logical, fast and occupies ultra-less area.

Diabetes is a highly prevalent metabolic disorder. The conventional method of diagnosing type-II diabetes involves blood sample extraction, which is a painful procedure leading to increased undiagnosed diabetes among the population. Therefore, a non-invasive screening tool is the need of the hour for diagnosis of diabetes. Our aim is to design and develop a non-contact infrared temperature sensor based screening tool to detect the blood glucose level. Infrared-based non-contact temperature sensor using MLX90614 is designed to study the metabolic variations in the form of temperature changes at the contra-lateral regions of the knee and carotid area of the neck region. A portable, compact non-invasive screening tool was developed to estimate the non-invasive blood glucose (HbA 1c ) with AUC: 0.919. The Sensitivity, Specificity, Positive predictive value, Negative predictive value and accuracy were measured (86%, 92%, 90%, 89%, 89%) respectively. The developed screening tool is cost effective, reusable and is able to study the subjects are under diabetic or control state.

This research work proposes an advanced medicine box monitoring system and its analysis. Patients with prolonged illness and elderly patients who have to undergo regular medication face a lot of medical errors with categorizing vast measure of pills every day. This paper insists on the intake and assembling of a medicine box whose purpose is to overcome this facility lacking in the medical field. The pill box will be capable of categorizing the pills by means of automation. The primary application of this medication pill box is concentrated on people who are under regular medical treatment or vitamin supplements and also used by medical attendants who deal with the more number of patients. Our smart medicine container is designed in such a way that it can be programmable anytime which facilitates the patient caretakers or clients to find out the quantity of pills and timing to intake the medicines for every day. The time at which the pill has to be taken should be preset after which the pill box will send reminders to the users or patients to take pills using alarm or buzzer.

Glaucoma is a condition of the eye that is caused by an increase in the eye's intraocular pressure that, when it reaches its advanced stage, causes the patient to lose all of their vision. Thus, glaucoma screening-based treatment administered in a timely manner has the potential to prevent the patient from losing all of their vision. However, because glaucoma screening is a complicated process and there is a shortage of human resources, we frequently experience delays, which can lead to an increase in the proportion of people who have lost their eyesight worldwide. In order to overcome the limitations of current manual approaches, there is a critical need to create a reliable automated framework for early detection of Optic Disc (OD) and Optic Cup (OC) lesions. In addition, the classification process is made more difficult by the high degree of overlap between the lesion and eye colour. In this paper, we proposed an automatic detection of Glaucoma disease. In this proposed model is consisting of two major stages. First approach is segmentation and other method is classification. The initial phase uses a Stacked Attention based U-Net architecture to identify the optic disc in a retinal fundus image and then extract it. MobileNet-V2 is used for classification of and glaucoma and non-glaucoma images. Experiment results show that the proposed method outperforms other methods with an accuracy, sensitivity and specificity of 98.9%, 95.2% and 97.5% respectively.

A brand-new approach to controlling the DC bus voltage for single-phase bi-directional AC/DC converters is presented. The suggested controller can offer a stable and trustworthy closed-loop control system while significantly enhancing the transient performance of the DC voltage bus control loop. In the preliminary technique, a specialized adaptive filter is used to explicitly estimate the DC output of the bus voltage. A very reliable then trustworthy approximation of the DC component of the DC bus is given by the recommended filter construction. A single-phase ac/dc converter with a double-frequency ripple may accurately estimate the amount of DC. current using the current DC. current extraction technique. Sections on simulation and testing exhibit the anticipated closed-loop control systems.

Energy efficient routing has been the mainstay of research in wireless sensor networks. With rising utility of WSNs in a broad range of applications, a significant volume of research contributions are targeted towards obtaining an energy efficient routing with a good quality of service (QoS) metric. In recent times, the utility of evolutionary algorithm for such multi-objective problems has been on the rising trend as evolutionary models closely mimic the real time scenario of any problem optimization. In this research work, a modified ant colony optimization (M-ACO) has been proposed and implemented for optimization in terms of energy conservation and thereby to extend the network lifetime of the network

In this paper, a more efficient, economic, and simpler mechanism of determining the health or disease affecting a plant is proposed. The working concept is demonstrated by identifying some of the existing diseases for a test plant using a system that compares two instances (or) states of the plant to find the difference of color pixel levels occurring (either an increase or a decrease) and mainly consisting of Raspberry Pi and 8051 microcontroller circuit connections. The main scope of the concept can be seen in the field of automation in agricultural care and treatment. The theoretical working of the device is first demonstrated in simulations using Proteus for the physical components and the software-related tests are done in a virtual Python Integrated Development Environment (IDE) called PyCharm. After confirming the working of the theoretical simulations, the hardware and software components are combined and finally verified using a physical model.

OBJECTIVE:In India, usually, oral cancer is mostly identified at a progressive stage of malignancy. Hence, we are motivated to identify oral cancer in its early stages, which helps to increase the lifetime of the patient, but this early detection is also more challenging.METHODS:The proposed research work uses a probabilistic neural network (PNN) for the prediction of oral malignancy. The recommended work uses PNN along with the discrete wavelet transform to predict the cancer cells accurately. The classification accuracy of the PNN model is 80%, and hence this technique is best for the prediction of oral cancer.RESULT:Due to heterogeneity in the appearance of oral lesions, it is difficult to identify the cancer region. This research work explores the different computer vision techniques that help in the prediction of oral cancer.CONCLUSION:Oral screening is important in making a decision about oral lesions and also in avoiding delayed referrals, which reduces mortality rates.