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IoT Based Smart Disinfection Robot
In recent years, sanitization played a vital role in to fight against infectious diseases. That sanitizing by the human can lead to contamination and infecting the human. So manual cleaning is not a perfect method for the pandemic situation. So in our project, we develop a sanitizing robot. It contains HC-05 Bluetooth for wireless communication, the motor driver for controlling the wheels, DC pumping motor for spraying the sanitizing liquid from the sanitizer container to the floor, wiper for cleaning the excess liquid on the floor. Sprayer is attached in front of the robot and the wiper is attached to the back of the robot. These all processes are controlled by mobile using IoT technology. This method is very useful for the infectious and pandemic situation.
Wireless Fall Sensor with GPS location for Monitoring the Elderly
Fall is the most consequential cause of injury in elderly that may lead to death sometimes, most of the deaths occurs due to the late response after the fall transpires. Elder people living in rural areas face this astringent issue and as the medical centres are very infrequent at those places, doctors cannot attend on them immediately, so this elderly fall detection system provides functionalities to notify the fall information to the server automatically which reduces the burden of caretakers who need to avail them perpetually. The amelioration of low performance utilizing a accelerometer at wrists and the inconvenience of sensor attached to a waist was concentrated on by integrating the efficacious motion sensing technology involved IMU like MPU-6050 which gives digital output from which Acceleration, Velocity and Quaternion data are observed and compared and additionally changing the sensor location from a waist to wrists. The fall detection system server is the web application server; it allows the doctor at medical centre to monitor the real- time fall in the webpage. Once the fall information is received, the server updates the fall information on the page automatically. By this way the doctor who is attending on, can know the health status of his patient immediately by the notification on the webpage whenever there is an emergency.
CNN Based Plant Disease Identification Using PYNQ FPGA
Plant disease is an ongoing challenge for smallholder farmers, which threatens income and food security. The recent revolution in smartphone penetration and computer vision models has created an opportunity for image classification in agriculture. Convolutional Neural Networks (CNNs) are considered state-of-the-art in image recognition and offer the ability to provide a prompt and definite diagnosis. In this paper, the performance of a pre-trained ResNet34 model in detecting crop disease is investigated. The developed model is deployed as a web application and is capable of recognizing 7 plant diseases out of healthy leaf tissue. A dataset containing 8,685 leaf images; captured in a controlled environment, is established for training and validating the model. Validation results show that the proposed method can achieve an accuracy of 97.2% and an F1 score of greater than 96.5%. This demonstrates the technical feasibility of CNNs in classifying plant diseases and presents a path towards AI solutions for small holder farmers.
A Novel Approach for Early Breast Cancer Detection based on Embedded Micro-Bio Heat Ultrasensitive Sensors: IoT Technology
Several diagnostic methods are currently used for providing data about the existence of breast cancer. The aim of this work is to propose a new method of diagnosis using thermography, based on the use of an embedded ultrasensitive micro-bio-heat sensors 3x3 array modelled by Altium, realized as an embedded system for the early detection of breast cancer. This system benefits from IoT technology which offers the possibility of communicating via Smartphone with a server for processing the data subsequently consulted by the treating physician, the patient and/ or a possible medical monitoring centre.
IoT Based Colonoscope
Gynecological cancers are among the most common cancers in women and hence are an important public health issue. Due to the lack of cancer awareness programs, variable pathology, and dearth of proper screening facilities in developing countries such as India, most women report at advanced stages, adversely affecting the prognosis and clinical outcomes. Ovarian cancer has emerged as one of the most common malignancies affecting women in India. Cervical cancer remains the second most common cancer in women after breast cancer. The causes of cervical cancer are HPV (Human Papilloma Virus), smoking, oral contraceptives, multiple pregnancies. It can be prevented in adult women with early detection tests, such as the HPV test or PAP test, followed by treatment. Early detection tests can identify pre-cancerous lesions in the cervix, which can then be treated before the lesion develops into cervical cancer. In our proposed work, we used Machine Learning and Deep Learning algorithms to find a model capable of diagnosing cervical cancer with high accuracy and sensitivity.
IoT Based Smart Shoe for Visually Impaired
IoT based Smart shoe system for visually impaired is a system made with the help of ultrasonic sensors, GPS and GSM module paired to an Arduino UNO board. Internet of things is all about making physical objects communicate with other objects or even with humans. Sightless people face great difficulty to travel independently. They must depend on others in many aspects of their life. The Major problem is when they walk on the road. With a stick in hand, they cannot detect every obstacle that comes in their way. The Smart shoe design provides a long-term solution for the blind to walk on roads independently. The smart shoe will help the Blind person to reach his destination independently. It is built using IoT Technology in which the shoe will be embedded with various sensors, Microcontroller, and buzzers. The shoe warns the user by making noise with the buzzer when he/she walks in front of an obstacle. The smart shoe communicates and coordinate with each other to ensure that the user does not collide with any obstacle in his way. Visually Impaired People face issues while travelling outdoors, this paper presents a literary review of overcoming such issues by making wearable sensors by planting them on shoes using IOT (Internet of Things). Use of ultrasonic sensors and buzzer to notify the end- user regarding upcoming obstacles.
Portable Kidney Machine with Blood Leakage Detector
Haemodialysis (HD) was first used by Wilhem Kolff to treat patients with acute kidney disease during the Second World War. However it was only in the 1960s following advances in vascular access, dialysers and dialysis machine design that HD started to become available as a treatment for patients with advanced chronic kidney disease (CKD). The many limitations on patient life style at that time, particularly the strict dietary and fluid restraint required, were readily appreciated by the early pioneers of HD therapies, who started a search to develop portable and wearable HD devices. However the technology attainable at that time restricted development and, consequently, enthusiasm for developing a wearable device wanted.
An IoT Based System for Remote Patient Monitoring
Following a surgical procedure, patients are monitored in an ICU until physically stable, after which are discharged to a ward for further evaluation and recovery. Usually, ward evaluation does not imply continuous physiological parameters monitoring and therefore patient relapse is not uncommon. The present paper describes the steps taken to design and build a low-cost modular monitoring system prototype. This system aims to offer mobile support in order to facilitate faster and better medical interventions in emergency cases and has been developed using low-power dedicated sensor arrays for EKG, SpO2, temperature and movement. The interfaces for these sensors have been developed according to the IoT model: a central control unit exposes a Restful based Web interface that ensures a platform agnostic behaviour and provides a flexible mechanism to integrate new components.
Attendance Management System Based on RFID and Fingerprint Reader
The attendance operation system using RFID and biometric detectors is a technology- grounded result for recording and managing attendance in associations. This system uses RFID markers and biometric detectors to identify and authenticate individualities, icing accurate and secure attendance shadowing. The system is designed to streamline the attendance process, exclude homemade crimes, and give real- time attendance data to directors. The system has proven to be an effective and effective result for managing attendance in colorful diligence, including education, healthcare, and manufacturing. The use of RFID and biometric detectors has revolutionized attendance operation and made it more dependable, accessible, and secure. These include the time unnecessarily consumed by the scholars to find and subscribe their name on the attendance distance, impersonation, and loss of attendance distance. Therefore, there's a need for a system that would exclude all of these problems.
Pain Reliever for Parallelized People using Shortwave Diathermy
This project report details the development of a pain reliever for parallelized people using short wave diathermy. Short wave diathermy is an effective and safe method for pain relief in many conditions. It has the potential to reduce pain and improve the quality of life for individuals with chronic pain conditions. This project report outlines the development of a device that utilizes short wave diathermy to reduce pain in parallelized people. The device consists of a hand-held device that is placed over the affected area and a remote control. The device is designed to provide the user with the ability to adjust the intensity of the diathermy to their desired level. The device is also capable of tracking the user’s progress and providing feedback on the effectiveness of the therapy. Furthermore, the device is also able to provide the user with an audio-visual cue when the intensity of the therapy needs to be adjusted. The device is also capable of being used in conjunction with other pain relief methods, such as medications, physical therapy, and massage. The development of this device has the potential to provide relief to individuals with chronic pain conditions.
Invention of Electro Magnetic Eddy Braking System
Electromagnetic braking systems use electronic and magnetic power to apply wheel brakes. Our system utilizes the concept of electromagnetism in order to achieve braking without friction. Eddy braking improves the reliability &life of brakes since they do not wear out over time due to friction. This needs comparatively very less maintenance and no oiling. Electromagnetic brakingis an upcoming technological replacement for traditional braking systems. The main objective behind the proposed use of these eddy braking system in automobiles is that it is frictionless. This leads to a very low maintenance cost due to no friction and no oiling. Also traditional braking systems are prone to slipping while this one is guaranteed to apply brakes to the vehicle.
Fabrication of Power Weeder Machine
A weeder is a machine used in agricultural fields to remove the weeds, which are unnecessary crops that hinder the growth of crops. The weeder which is operated with the gasoline engine is called a power weeder. The power weeder has the problem of pollution and excess vibration. To overcome these issues the power weeder is to be converted to an electrically operated system. So here the existing gasoline engine is replaced with a motor for drive and batteries for power source. The gearbox has a forward and reverse gear arrangement. The battery source is given to the motor for drive. A lead-acid battery setup with 4numbers each of 12vcapacity is used. The operating life of the battery is around200-300rechargecycles.
Fabrication of Electromagnetic Suspension System
The power generator electromagnetic suspension system is a system that converts vehicle bump generated linear motion & vibration, into electricity to be used in battery charging. General vehicle shock absorbers are used to simply absorb this energy without converting it to electricity. So here we put forth a way to use this free energy and store it for further needs such as vehicle lights, cooling, indicator lights etc. The devised prototype Suspension System uses the energy to generate electricity which is otherwise dissipated. In this work, process of arriving at the fabricated model of Suspension System for Power Generation is elaborated. The preliminary and existing techniques which help in regenerating energy dissipation in suspensions are discussed and the way they led to contrive the concept of prototype Suspension System is elucidated. With the concept, the derivation of specifications and the process of designing the Suspension System is delineated. The Suspension System generated a potential difference in the range of 125 mV to 350 mV.
Design and Analysis of Propeller Shaft for Automobile
Almost all automobiles have transmission shafts. The propeller shaft have some loss due to weight. The weight reduction of the drive shaft can have a certain role in general weight reduction of the vehicle and is a highly desirable goal. Exploring composite materials in order to obtain reduction of weight without significant decrease in vehicle quality and reliability. To start the vehicle the most of the power consumed in driving transmission system, if we able to reduce the weight of the propeller shaft that surplus available power can be used to propel the vehicle.
Raspberry PI-Based Finger Vein Recognition System Using PCA NET
Despite simultaneously ignoring the intensity distribution that is formed by the finger tissue and, in some instances, processing it as background noise, the majority of finger vein feature extraction algorithms achieve satisfactory performance due to their ability to represent texture. This project makes use of two- directional two-dimensional Fisher Principal Component Analysis, also known as (2D) 2 FPCA, for feature extraction. This type of "noise" is presented as a novel soft biometric trait for improving finger vein recognition performance. In order to demonstrate that the intensity distribution that is formed by the finger tissue in the background can be extracted as a soft biometric trait for recognition, a comprehensive analysis of the finger vein imaging principle and the characteristics of the image are first presented.
Design and Fabrication of Water Can Cleaning Machine
Aim of this project is to develop a mechanical system for cleaning domestic cylindrical 20 litre water can. A Water Can Cleaning Machine is generally used for cleaning the water can inside and outside the can. Sediment scale and algae get deposited on the outer and inner surface of the water can. So, we have proposed the automatic plastic can washing and drying system in order to resolve the problem of the employees. In this system we are using Relay as main controller. Some of the main benefits of this system are high productive, reliable, accurate, cost effective water can cleaning machine enables to save time and it provides high safety and high efficiency.
IoT Based Flood Monitoring and Alerting System
Flood is one of the most dangerous natural disasters in the world and that cannot be avoided. It has the capability to destroy and kills the people. It happens too fast and affected so numerous lives and parcels. When the flood tide occurs in the people living area it come veritably dangerous and beget damage to the people. Other than that, maturity of the public can not cover and have no idea when the flood tide going to be happed since they don't have any information and data about the rainfall conditions. This system is suitable for metropolises and vill areas. Likewise, if the public has an internet access, they can cover what's passing and prognosticate if there is any forthcoming flood tide at the web garcon. This design will modernize the water position at the web garcon and the system will issue an alert signal to the citizens for evacuation so that presto necessary conduct can be taken. For this reason we develop a waking system named “IOT Based Flood Monitoring and Alerting System”.
Design and Analysis of Shaft with Blade and Drum for Kapok Seed Separator
The kapok seed separator has two main parts; one is blade shaft and another one drum. Its primary function is separating the seed from kapok silk cotton. This paper is describes designing and Analysis of blade shaft and drum. Currently, existing kapok seed separator is manufactured by using mild steel. Modelling and analysis carried out by using AUTODESK FUSION 360software. The different materials such as Alloy steel, Carbon steel and Aluminium alloy. The aim of this work is to replace mild steel blade shaft and drum of kapok seed separator with an appropriate material blade shaft and drum. Appling load and pressure to the component and comparing the result.
IoT Based Implementation of Power Saving and Gas Leakage Detector
The implementation of IoT based power saving and gas leakage detector is an innovative approach to reduce energy consumption and enhance safety in households and commercial buildings. This system utilizes smart sensors to detect gas leaks and turn off power in rooms where there is no human presence. The sensor data is transmitted to a central server or cloud-based platform, which triggers alarms and alerts to notify residents and building managers of any potential safety hazards. The implementation of this IoT based solution can significantly reduce energy costs and improve safety by providing real-time monitoring and control of energy usage and gas leaks in buildings.
Fault Diagnosis of Wind Turbines using Scada Data by ML Techniques
Fault diagnosis technology is crucial for the safety and stability of the operation of wind turbines. Efficient wind turbine fault diagnosis technology quickly identifies the types of failures in order to reduce the operating and maintenance costs of wind farms and improve the efficiency of power generation. The majority of wind farms currently use supervisory control and data acquisition (SCADA) systems to acquire operation and maintenance data. SCADA systems are rich in data pertaining to the working parameters of wind turbines. Moreover, fault diagnostic functionality is not common in SCADA systems. SVMs are a common intelligence technique used in the fault diagnostics of wind turbines. The choice of SVM parameters is essential for precise model classification. The penalty factor and kernel function parameter of SVM were optimi zed in this study along with the construction of the SSA-ABC wind turbine defect detection model using the Artificial Bee Colony (ABC), a brand-new and very effective optimization technique. Data are obtained from a wind farm SCADA system and, after pre-processing and feature selection, entail a faulting set. Evidence suggests that the ABC-SVM diagnostic model, which has a quick convergence rate and a potent optimization capability, effectively enhances the accuracy of wind turbine fault diagnosis when compared to the GS-SVM, GA-SVM, and PSO-SVM models. The ABC-SVM diagnostic model may also be utilized in real-world engineering applications to identify defects.