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Self Operated Ground Lifting Wheelchair for People with Disability
Pro wheelchair users are at a height disadvantage during many function activities, such as transferring or reaching. Retrieving objects from the ground or a higher shelf while seated in the wheelchair can be both difficult and unsafe. Lateral transfers between surfaces at different heights can be hard and unstable. Sit-to-stand transfers are made simpler with a higher seat. This research project seeks to assist reach and transfers by designing a system to raise and lower a wheelchair seat over a 4’’ range. The project followed a multi-step iterative design process that included: needs assessment by conducting interviews and surveys, identify design needs from different stakeholder groups; analysis of stakeholder groups’ feedback and synthesis into design criteria; and creation of design concepts for the adjustable height wheelchair seat; evaluation of the design by setting up heuristic evaluation criteria and performance of user testing; design revision based on user’s test performance and feedback. The design process included fabricating and testing of various concepts, validating design through user testing, and addresses technology transfer of the device.
Real Time Monitoring of Vitals of a Baby Using IoT- Enabled Smart Baby Incubator
Recently born babies are exceptionally touchy to unpleasant situations. The tidy and temperature issues here can be life debilitating. Due to these issues, a child hatchery is made that can give the same temperature and natural conditions as a mother's womb does, as well as it screens the baby's restorative conditions such as heart beat, skin temperature, inside temperature, spo2 level, baby weight etc. Being physically show with the patients has gotten to be a gigantic issue for specialists. In such cases, actualizing IoT with healing center hardware such as a Child Hatchery has gotten to be one of the fundamental objectives for us. Giving an app that can track the baby's condition remotely will demonstrate to be exceptionally productive. Our fundamental objective is to make a savvy infant hatchery that can distinguish baby's condition and in case anything goes off-base, the framework can trip itself so that the conditions can return to a typical state. We will coordinate it with IoT and a versatile app so that specialists can check the baby's condition remotely. It can be simple to think of a hatchery as fair a bed for a sick infant, but it's so much more than a put for resting. An hatchery is outlined with such methods and care that it can give a safe and sound climate for a infant child to rest until it’s imperative organs are still in a advancement arrange. When we compare our incubator to a basic healing center bed, and hatchery will give a totally controlled environment as well as the required sum of oxygen levels, idealize light presentation and mugginess matches with the mother's womb. In expansion to climate control, a hatchery offers security from other hurtful components that can harm a child such as allergens, boisterous commotions, microscopic organisms and infections, etc. An incubator's capacity to control stickiness too permits it to secure a baby's skin from losing as well much water and getting to be delicate or cracking. An hatchery can incorporate hardware to track a run of things counting a baby's temperature and heart rate. This monitoring permits medical caretakers and specialists to always track a baby's well being status.
Medical Drone a Life Saver in Emergency Situations (Organ Delivery Drone)
This paper explores the emerging field of medical drones for organ delivery, addressing the critical need for timely transportation of organs to enhance transplantation procedures and save lives. Medical drones offer a novel solution to overcome geographical barriers, particularly in remote or inaccessible regions, by providing rapid and efficient delivery of organs and blood samples. By significantly reducing transportation times compared to conventional methods, medical drones have the potential to revolutionize healthcare logistics and improve access to critical care services. This abstract highlights the key benefits and challenges associated with the integration of medical drones in organ delivery, emphasizing their role in expediting transplant procedures and ensuring timely interventions for patients in need.
Low Cost Motorized Patient BED with Voice Control
In recent years, there has been a growing interest in integrating advanced technologies into healthcare settings to improve patient care and enhance medical infrastructure. One such innovation is the motorized voice-controlled hospital bed, which represents a significant advancement in patient comfort, mobility, and overall healthcare management. This paper presents the design, development, and implementation of a motorized voice- controlled hospital bed aimed at revolutionizing patient care in medical facilities. The motorized voice-controlled hospital bed incorporates cutting- edge technology, including voice recognition systems, motorized actuators, and wireless connectivity. Through voice commands, patients can effortlessly adjust the bed's position, including height, tilt, and backrest angle, enhancing their comfort and facilitating activities such as eating, reading, and watching television. Moreover, healthcare providers can remotely monitor and adjust bed settings, ensuring optimal patient positioning and reducing the risk of complications such as pressure ulcers. Key features of the motorized voice-controlled hospital bed include an intuitive voice interface, customization positioning options, safety mechanisms to prevent unintended movements, and seamless integration with existing healthcare infrastructure. Additionally, the bed's design prioritizes patient safety, infection control, and ease of maintenance, adhering to stringent healthcare standards and regulations.
Height Adjustable Wheel Chair for Differently Abled Person
The height adjustable wheel chair focuses on meeting the needs of paraplegics ‘ patients and the poor disabled persons who desire to perform certain tasks independently and privately, such as sitting on the chair, picking items from shelves, cupboard and wardrobes at the standing height of average human being. Hence, an appropriate wheelchair to meet their need has been designed using low cost and readily available materials to achieve this product. The existing wheelchair was evaluated before its modification was done in justifying the established improvement. To achieve this, the wheel chair was redesigned with a low centre of gravity to enhance stability with the introduction of sizeable hydraulic jack to aid height adjustment. By controlling hydraulic pressure, users can elevate or lower the seat to preferred heights, facilitating ease of access to various surfaces and environments. Additionally, the hydraulic system offers stability and durability, ensuring safe operation for users of different body weights and sizes Performance evaluation of the developed wheelchair was carried out to ensure standardization in meeting the needs of the intended users. On basis of ease of operation to a chosen height of 2m using pulses generated, 79 pulses/ minutes was recorded for the improved wheelchair as against the 95 pulses/minutes of the existing wheelchair. Also it takes 28 seconds and 36 seconds for the modified and existing wheelchairs to reach the set height respectively. It offers confinement for adjustment to desired height position and provides mobility while at chosen elevated position.
Breast Cancer Detection Using Deep Learning
The most frequently occurring cancer among Indian women is breast cancer. The second major cause of women's death is breast cancer (after lung cancer). 246,660 of women's new cases of invasive breast cancer are expected to be diagnosed in the US during 2016 and 40,450 of women’s death is estimated. The number of breast cancer cases is steadily growing especially with increasing number of ageing population. Breast cancer is a type of cancer that starts in the breast. Cancer starts when cells begin to grow out of control. Breast cancer cells usually form a tumour that can often be seen on an x-ray or felt as a lump. The screening practice using mammography needs to be better and potentially efficient. There is always room for advancement when it comes to medical imaging. Early detection of cancer can reduce the risk of death for cancer patients. Breast cancer can spread when the cancer cells get into the blood or lymph system and are carried to other parts of the body. This overview looks at the results of a proposed system for automatically diagnosing breast cancer using several convolutional neural network (CNN) designs and compares them to those achieved using machine learning (ML) techniques. All buildings were built from a large database. Validation tests were conducted in order to provide quantifiable results using the performance parameters of each approach. Functions like VGG16 and ResNet50 are used in this model to improve the accuracy of the model. The cause of Breast Cancer includes changes and mutations in DNA. Women are seriously threatened by breast cancer with high morbidity and mortality. The breast cancer dataset is publicly available on the UCI Machine Learning Repository and therefore the implementation phase dataset is going to be partitioned as 80% for the training phase and 20% for the testing phase then apply a significant performance in respect of all parameters.
Classification of Alzheimer’s Disease Detecting Using Deep Learning
There are a wide range of reasons for dementia, yet Alzheimer's Infection is the most normal structure. As the condition advances, it restricts one's capacity to play out any errand without help, and the analysis timetable and maturing populace are supposed to make its commonness increment. The regular approaches to distinguishing Alzheimer's is tiring for the two patients, specialists where it includes recovering the previous clinical records and having Attractive Reverberation Imaging sweeps and even neuro actual testing which can be awkward for patients. An early determination of cerebrum infections has a major effect with regards to endeavouring to fix them. Our work has utilized profound learning (brain organizations) to identify Alzheimer's sickness sooner than expected by joining it with profound learning. As the got dataset from UCI Storehouse is vigorously imbalanced, we equitably conveyed the information between the classifications utilizing Destroyed. Then the model is prepared and tried with the ordered X-ray information for example extremely gentle, gentle, moderate and serious Promotion lastly remove elements to look at the outcomes. The outcomes we accomplished are contrasted and the past endeavours on recognition of Alzheimer's and emerged to be fundamentally more noteworthy with regards to accuracy and exactness.
Text Recognition for the Speed Control of the Vehicle
An automatic vehicle human-voice-based safety control is proposed to decrease the happening of vehicle accidents due to an eye or hand activities while driving. The design is implemented using an Arduino microcontroller. One of the most important safety control features is the automotive speed control (ASC). In this safety control function, which prevents a vehicle sudden hit, the necessary action is issued based on the vehicle-to- vehicle distance measure. To prevent the driver from attention withdraw and maintain a proper road and situation focus (as especially is the case at night), several other automated safety control operations are provided (i.e., radio, flasher, left flasher, right flasher, wipers, drive, and stop). These features are controlled according to human voice commands using an EasyVR module. The proposed model has been designed, built, and tested providing suitable results as desired.
Smart Irrigation and Pesticides System for Enhancing Harvesting in Agriculture Using IoT
Agriculture plays a vital role in the economy of many countries, serving as a primary source of food. However, traditional farming practices often face challenges such as inefficient water usage, over-reliance on pesticides, and inconsistent monitoring of crop conditions. In recent years, the Internet of Things (IoT) has emerged as a promising technology to address these challenges by providing real-time monitoring and control of agricultural processes. This leads in excessive water use, which has an impact on agricultural output. This integrated system means that farmers only need to perform little manual monitoring. The opening and closing of the reservoir and field gates, as well as the verification of the plant's age and the matching optimal water level necessary for that time of plant age, are all automated. Farmers may use their mobile phones to check the water level in the field since they are continually receiving updates on the field work. The most labour-intensive and time consuming activity in agriculture is water management. In our project, the water level in the agriculture harvest sting is measured, and if it is lower than the required level, the paddy field is automatically irrigated for the water source or tank using a water pump. It can comprehensively monitor air temperature and humidity, light intensity, ultraviolet light and other environmental elements. In specific use, the agricultural production environment monitoring system starts from the actual needs of the plantation zone and is assembled according to the environmental elements it needs to monitor.
Integrated Poultry Care System (IPCS)
The Integrated Poultry Care System (IPCS) is an innovative IoT-based real-time monitoring and control system designed specifically for poultry farms. Leveraging the power of Internet of Things (IoT) technology, IPCS offers comprehensive monitoring capabilities, allowing farmers to remotely track with using individual tags for identifying the temperature, humidity in their poultry houses in real-time. Raspberry Pi 4 serves as the central processing unit and data hub, collection, processing, and transmission of sensor data from the poultry houses. The ESP8266 module is specifically utilized for its capability to connect to Wi-Fi networks, allowing seamless communication between sensors. These modules then transmit the collected data wirelessly to the central control unit, typically powered by a Raspberry Pi or a similar computing device, for processing, analysis, and monitoring. It also serves as the interface through which farmers can remotely access and monitor the conditions within their poultry houses via a user-friendly dashboard or mobile application.
Diabetic Retinopathy Detection Using Image Processing
In today’s world, Diabetes is a very common disease that affects a lot of people’s health. As the number of diabetic patients is increasing significantly in India, there is a rise in numerous associated diseases that have disturbed society.Diabetic Retinopathy (DR) is considered to be one of such silent diseases that occur as a result of either Type 1 or Type 2 diabetes. Late diagnosis of this disease may lead to permanent eye blindness. Thus, for early diagnosis of Diabetic Retinopathy, a software-based algorithm is designed here. This technique can be promising for the pre-detection of DR without any involvement of an expert doctor and hence will save both time and money. Here, MATLAB-based image processing is used which exploits the knowledge of Computer Science and Biomedical Engineering to identify whitish lesions, cotton wool spots and hard exudates associated with DR. Based on the value of pixel counts, the image of the patient’s eye under examination is classified. Diabetic retinopathy (DR), a complication of diabetes, poses a significant threat to global vision health. Early detection and timely intervention are crucial to prevent irreversible vision loss.
Identification of Fake Currency Using Convolution Neural Network
The progression of shading printing innovation has expanded the rate of Fake currency copying notes on a large scale. Albeit electronic monetary exchanges a returning out to be more popular and the utilization of paper cash has been diminishing as of late, banknotes still remain in distribution attributable to their dependability and straight forwardness in use. Few years ago, the printing should be possible in a printing-house, yet presently anybody can print a money paper with most extreme exactness utilizing a straightforward laser printer. As an outcome, the issue of duplicate currency rather than the authentic ones has been increases generally. India had reviled the problems like defilement and dark cash and fake of money notes is likewise a big issue to it. To handle this problem, a deep learning- based framework is proposed to identify the fake Indian currency. The MATLAB tool has been used to identify the fake currency. The outcome will classify whether the Indian currency note is Real or Fake.
Question Paper Generator
The automatic question paper generator (AQPG) is a software tool designed to streamline and automate the process of generating examination question papers. It leverages algorithms and databases to create balanced, fair, and diverse sets of questions based on predefined parameters such as topic, difficulty level, and question type. By incorporating machine learning techniques, natural language processing, and data mining, AQPG can analyze vast amounts of educational content to ensure the integrity and quality of the generated questions. This abstract provides an overview of the AQPG system, highlighting its significance in reducing manual effort, enhancing efficiency, and maintaining the integrity of assessment practices in educational institutions.
Secure DNA Data Storage with Similarity Search in Cloud Environments
DNA similarity search has been widely applied in human genomic studies including DNA marking, genomic sequencing and genetic disease prediction. Meanwhile, with the explosive growth of data, users are increasingly inclining to store DNA data on the cloud for saving local cost. However, the high sensitivity of DNA data has forced the government to strictly control its acquisition and utilization. One potential solution is to encrypt DNA data before outsourcing them to the cloud. Nevertheless, private DNA similarity query has been an active research issue, state-of-the-art results are still defective in security, functionality and efficiency. In this paper, we propose EFSS, an Efficient and Fine-grained Similarity Search scheme over encrypted DNA data. In specific, firstly, we design an approximation algorithm to efficiently calculate the edit distances between two sequences. Secondly, we put forward a novel Boolean search strategy to achieve complicated logic queries such as mixed “AND” and “NO” operations on genes. Thirdly, data access control is also supported in our EFSS through a variant of polynomial based design. Moreover, the K-means clustering algorithm is exploited to further improve the efficiency of execution. In the end, security analysis and extensive experiments demonstrate the high performance of EFSS compared with existing schemes.
Trust Enabled Cluster Aware Routing Protocol Design with Energy Considerations using Fuzzy Strategies
In this modern era, wireless communication technologies are getting high impact over network industries. Due to this drastic development of communication technologies, a network needs to be more precise with certain metric such as: energy consumption, throughput, trust management, performance and lifetime. These are all the primary concern while handling the transactions with wireless communication systems. In this paper, a new approach of network routing protocol is introduced, which will replace the issues found in existing routing protocols and provide good support while communication between entities. The proposed paper introduces a new routing protocol called Modified Adhoc On-Demand Distance Vector (MAODV), in which the classic AODV protocol supports mobile nodes with several impacts such as mobility, failure prevention, loss management and so on. However, the issues in industry still remains, so, that a new approach or routing protocol is required to overcome such issues. This is the concern to develop a new routing protocol for establishing communication between mobile nodes or wireless devices. The drastic development of communication devices requires some latest technologies to provide range free communication model with the assistance of internet support. A term, 'Internet of Things (IoT)', which rules the world now-a-days through its power of connectivity and establishing the bridge between communication devices around the globe without any range restrictions. In this paper, a cluster based routing strategy is designed with the help of fuzzy assistance. The cluster based routing protocols divides the range of communication into clusters and electing the cluster head based on the communication needs and provides a range free communication model with the hands of IoT support. This cluster based routing model provides support for both inter and intra-cluster communications, which all will be brief in further sections. The proposed model of wireless communication assures the following things such as Improved Energy Efficiency, reduced packet loss and delay, improved throughput ratio and lifetime over resulting scenario with the help of a new algorithm called Fuzzy Assisted Cluster enabled Routing Model (FACeRM) with the association of new routing protocol MAODV.
Secure Date Storage Using ECC Encryption with Verifiable Data Sharing in Cloud
Cloud data storage has become increasingly popular, but the security and privacy of data stored in the cloud remain major concerns. Cloud computing is the most feasible approach for implementing Digital Twin services since it has prodigious advantages. It provides on demand services, computing resources, ubiquitous network access, etc., making it suitable for the next-generation information technology architecture. In cloud-assisted data storage environments, the data owners generate data from physical assets and disseminate it to the cloud server.
Enhancing Gym Safety and Workout Efficiency during Squats and Deadlifting Exercises with an IoT based Novel Smart Workout Belt
This paper introduces a smart workout belt specifically tailored for squats and deadlifting exercises and is designed to improve safety and workout effectiveness in gyms. Traditional protocols often overlook cardiac distress and muscle injuries, increasing the risk of fatalities. Our solution integrates sensors like ECG, EMG, and accelerometer into a Node MCU microcontroller ESP32 for real-time monitoring. It detects cardiac issues, muscle fatigue, and unsafe behaviours, alerting users through audible and visual cues. This system aims to enhance gym safety by providing continuous monitoring and timely interventions, reducing exercise-related risks.
Instagram Fake Account Detection Based on Machine Learning
The popularity of social media continues to grow, and its dominance of the entire world has become one of the aspects of modern life that cannot be ignored. The rapid growth of social media has resulted in the emergence of ecosystem problems. Hate speech, fraud, fake news, and a slew of other issues are becoming un-stoppable. With over 1.7 billion fake accounts on social media, the losses have al-ready been significant, and removing these accounts will take a long time. Due to the growing number of Instagram users, the need for identifying fake accounts on social media, specifically in Instagram, is increasing. Because this process takes a long time if done manually by humans, we can now use machine learning to identify fake accounts thanks to the rapid development of machine learning. We can detect fake accounts on Instagram using machine learning by implementing the combination of image detection and natural language processing.
Design and Fabrication of Unmanned Aerial Vehicle for Object Recognition
The innovative realm of unmanned aerial vehicle assisted human face recognition. By amalgamating unmanned aerial vehicle technology and advanced computer vision algorithms, the research presents a robust system capable of detecting and identifying human faces from aerial perspectives. Real-time image processing and artificial intelligence methodologies are harnessed to ensure accurate performance across diverse environmental conditions. The proposed framework showcases its potential in surveillance, search and rescue missions, and crowd monitoring. Ethical considerations, limitations, and effectiveness are scrutinized through empirical evaluations, contributing valuable insights to the discourse surrounding privacy, security, and responsible unmanned aerial vehicle utilization.
Efficient and Secure Communication in VANETS Using Block Chain
We have made great progress in resolving the crucial problem of location privacy in Vehicular Impromptus Networks (VANETs), an essential component of Intelligent Traffic Systems (ITS), using our innovative block chain-based trust management methodology. VANETs' high inherent mobility has long presented security issues, especially when it comes to using Location-Based Services (LBS). Our creative solution gives cars the ability to request LBS while protecting their personal data with a secure verification process. Vehicle privacy is protected via the creation of anonymous shrouding zones, and vehicle behaviour is controlled and governed by an advanced trust management algorithm. By using block chain technology, the system's data security is strengthened even more, resulting in a strong, impenetrable architecture. Thorough testing has proven the system's resilience against a range of assaults based on trust models, proving its efficacy in protecting vehicle privacy. The outcomes of our simulation demonstrate the practicality of our suggested method in actual VANET circumstances, pointing to the possibility of a new era in safe and private ITC systems.