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IoT Baby Monitoring System Using Node MCU
This paper presents an idea to design a Smart Cradle System using IOT which will help the parents to monitor their child even if they are away from home & detect every activity of the Baby from any distant corner of the world. It is an innovative, smart & protective Cradle System to nurture an infant in an efficient way. This system considers all the minute details required for the care & protection of the Baby in the cradle. The design of smartness & innovation comes with the use of technologies/methodologies which include the Internet of Things (IoT) (Modules like Arduino UNO, Humidity & Temperature sensing, etc..,), Cry Detecting Mechanism, Live Video Surveillance, Cloud Computing (Data Storage) & User Friendly Web application (for User Controls). In order to detect each & every activity of the Baby, different Sensors/Modules are attached to the Cradle: Humidity & Temperature Sensing Module for detection of Wetness of the bed, A Camera on top of the Cradle for live video footage & Cry Detection Circuit to analyze Cry Patterns. All the data which has been taken from the sensors/modules will be stored in Cloud? & analyzed at regular intervals.
Smart Anti-Burglary Surveillance System using Image AI
In today's world, with an increasing number of robberies, looting and shoplifting, it is indispensable to ensure the safety of our belongings and valuables. When it comes to certain places like bank vaults, uninhabited houses, business establishments like retail shops, jewellery stores, watch stores, etc., surveillance for observing the premise is very essential and has become the unavoidable need of the hour. At such places, it is unlikely to continuously monitor the venue using conventional cameras or a security guard person. To address such type of issues which involve uncertainty of safety, our project proposes a system which will tirelessly monitor the venue at required hours, intimate the intended person (administrator) via mobile communication (Short Message Service), initiate an alert alarm at the premise in order to aware the surroundings and also save the intrusion detected frames in the specified choice of storage. Also, it is developed in such a manner that the system recognizes and does not initiate alert/notification for persons those who are reliable and trustworthy (such as the shopkeeper, habitant of the house, etc.). This system is implemented with specific considerations using Image AI and Tensor flow built upon Convolutional Neural Networks, remotely operatable by users, without compromising the importance of security and protection.
EXPLORING THE DIASPORIC CONSCIOUSNESS IN THE POETRY OF AGHA SHAHID ALI
Diaspora is much talked and celebrated discourse across the disciplines. Confrontation of diasporic community with native community gives rise to multi-dimensional problems. Diasporic community thus undergoes different levels of realities that change their perceptions as a person who migrated from his/her homeland in search of new opportunities. Their perception as a segment in foreign land is marked with the sense of alienation, hybridity, identity crisis and many other mental and physical, cultural-religious, and spatial-geographical turmoil. In a sense they come across the diasporic reality. Diasporic reality is a combined study of Diaspora and problems of migrants. This paper explores the meaning of diaspora through the definitions of different writers and the problems of migrants. It specifically attempts to trace the problems of identity crisis and hybridity as confrontation with different often contradictory socio-cultural, religious, and different historical backdrop in which diasporic community is located in.
The Nano Revolution: Shaping the Future with Nano Technology
Nanotechnology is an emerging technology with limitless real- world applications. It is a technology that explores the unknown potential of science and technology. It is a multidisciplinary field that applies and develops in various fields such as applied science, mechanical, electrical, and others. Nanotechnology has revolutionized various applications in the current era. In this paper, we discuss the role of nanotechnology in computer science and the recent developments and opportunities. This is a review paper that provides a brief overview of the research done so far. Nanotechnology has various applications in almost every field in today’s world. Whether it is medical or electrical, nanotechnology is widely used in every branch. Nanotechnology is not only about materials and their synthesis, but it is also useful for computers and software. In this paper, we focus on some applications of nanotechnology that are related to computers. Nanomaterials have greater strength and smaller sizes, so they can be used to make computer chips (memory chips, ICs) smaller as needed. These chips can have large storage spaces with less size. These chips are flexible and can fit easily within the CPU, which improves the memory and efficiency of the computer.
A Complete Overview of Cloud Computing
The Coronavirus pandemic has had a variety of effects on the legal system, its businesses, and activities, including the closing of law firms and courts, a decline in services, a lack of clients, the withdrawal of client schedules and settlements, a decline in the workforce's accessibility because of the virus or social exclusion, and difficulties holding clear appointments and services. As a result, the law has undergone a comprehensive transformation to include technology and keep up with the rapidly evolving digital world. This essay emphasizes the advantages and risks of cloud computing as it relates to the digitization of the legal profession. Additionally, Case Lines, a cloud-based application that is increasingly used for conducting court proceedings, will be covered.[1],[2]
Detection of Stress using Wearable Biosensor
As the population increases in the world, the ratio of health care takers is rapidly decreasing. Therefore, there is an urgent need to create new technologies to monitor the physical and mental health of people during their daily life. In particular, negative mental states like depression and anxiety are big problems in modern societies, usually due to stressful situations during every day activities including work. This paper presents a machine learning approach for stress detection on people using wearable physiological sensors with the final aim of improving their quality of life. The presented technique can monitor the state of the subject continuously and classify it into”stressful” or”non stressful” situations. Our classification results show that this method is a good starting point towards real-time stress detection Stress is a natural reaction to various stress-inducing factors which can lead to physiological and behavioural changes. If persists for a longer period, stress can cause harmful effects on our body. Stress is a major concern in our day-to-day life. The human environments including worksite, home or society can induce stress on an individual to some extent. There are many ways that our body can react to stress, these reactions are mainly classified to either physiological reactions which includes the ‘fight or flight’ response by the Autonomous nervous system (ANS) of our body or behavioural reactions which includes defensive behaviour, days functional and expressive behaviour, the body sensors along with the concept of the Internet of Things can provide rich information about one’s mental and physical health.
A Smart Car Rental Management System using Data Mining
The car rental management system is a comprehensive software application designed to help car rental companies manage their operations efficiently. It includes features such as vehicle registration, inventory management, pricing management, billing and invoicing, customer management, and reporting. The system provides a user-friendly interface for customers to search for available vehicles, make reservations, and manage their bookings. The CRMS encompasses a comprehensive suite of features aimed at automating and optimizing various aspects of car rental operations. These include customer registration and authentication, vehicle inventory management, reservation handling, rental duration tracking, payment processing, and reporting functionalities. By integrating these components into a unified platform, the CRMS simplifies and streamlines the entire rental process, enabling car rental companies to operate efficiently and deliver a superior customer experience. Key benefits of the CRMS include improved operational efficiency, enhanced accuracy in managing rental bookings, minimized administrative tasks, and reduced paperwork. Customers can conveniently browse vehicle options, make reservations, and complete transactions through user-friendly interfaces, fostering a seamless and hassle-free rental experience. Additionally, the car rental management system provides reporting and analytics features, enabling the company to analyse rental patterns, track revenue, and monitor performance metrics. This information can help in making informed business decisions, optimizing fleet utilization, and enhancing customer satisfaction. Overall, the car rental management system streamlines operations, improves efficiency, and enhances customer service in the car rental industry by automating key processes and providing real-time access to crucial information.
Microcontroller Based Aeronautical Crash Prevention System through RF Communication
Embedded system is a special-purpose computer, designed to perform a dedicated function. Embedded system is quickly growing in various fields like industrial automation, home appliances, automobiles, aeronautics etc. The main aim of this project is to prevent the collision among air flights. Many methods are available to prevent the collision between the flights, but here RF technology and Microcontroller is used which provides some additional features for future enhancement. The system uses a microcontroller to collect data from sensors on the aircraft and process it to determine the distance and velocity of other aircraft in its vicinity. The system then sends signals to other aircraft in its range through RF communication to alert them about the potential danger. In addition performance evaluation of the system, which includes the detection accuracy, response time, and communication reliability, is monitored.
An Access Control Framework using Blockchain on Medical Data
Cloud is a computing model that provides sharing and supports ubiquitous on-demand access computing, providing new data processing and services for many industries, significantly reducing user computing and storage costs, and improving ease of use. With the development of cloud-scale and intensification, cloud security has become an essential issue in the field of cloud computing. Access control is one of the critical security technologies for protecting sensitive data stored in the cloud by enterprises and individuals. Since the centralized access control mechanism is adopted in the cloud, the sensitive data in the cloud are easy to be tampered with or leaked by hackers or cloud internal managers. To address this issue, we propose a blockchain- based access control framework with privacy protection called AuthPrivacyChain. Firstly, we use the account address of the node in blockchain as the identity, and at the same time, redefine the access control permission of data for the cloud, which is encrypted and stored in blockchain. After that, we design processes of access control, authorization, and authorization revocation in AuthPrivacyChain. Finally, we implement AuthPrivacyChain based on enterprise operation system (EOS), and the results show that AuthPrivacyChain can not only prevent hackers and administrators from illegally accessing resources, but also protect authorized privacy.
Cell Disease Identification Using Enhanced Salp Swarm Algorithm in Machine Learning
Computerized diagnosis of white blood cells cancer diseases for instance Leukemia and Myeloma is a demanding biomedical research area. Our method presents for the first time a new state of the application that assists in diagnosing the white blood cells diseases. We divide these diseases into two types; each type includes similar symptoms a disease that may my method is applied on one of the two diseases category by computing different features. Finally, Random Forest classifier is enforced for final decision. The proposed method aims to early discovery of white blood cells cancer, reduce the misdiagnosis cases in adding up to develop the system learning methodology. Moreover, allowing the experts only to have the final modification on the result obtained from the system. The proposed approach achieved an accuracy of 93% in the first type and 95% in the second type.
Computer Aided Medical Bed
Background and goal: Being bedridden long-term can motive deterioration in sufferers’ physiological feature and overall performance, restricting each day sports and growing the prevalence of falls and different unintentional injuries. Little research has been carried out in designing effective detecting systems to screen the posture and status of bedridden sufferers and to provide correct real-time comments on posture. The functions of these studies were to develop a laptop-aided gadget for actual-time detection of bodily sports in bed and to validate the system’s validity and check–retest reliability in determining 8 postures: movement leftward/rightward, turning over leftward/rightward, getting up leftward/rightward, and getting out of bed leftward/rightward. Strategies: The in-bed physical interest detecting system consists specifically of a clinical sickbed, signal amplifier, a records acquisition (DAQ) machine, and working software program for computing and figuring out postural modifications related to four load cellular sensing components. Thirty healthy subjects (15 males and 15 ladies, suggest age = 27.8 ± 5.3 years) participated within the look at. All topics were asked to execute eight in-bed sports in a random order and to take part in an evaluation of the take a look at–retest reliability of the outcomes 14 days later. Spearman’s rank correlation coefficient was used to examine the gadget’s determinations of postural states with researchers’ recordings of postural modifications. The test–retest reliability of the gadget’s potential to decide postures was analyzed the use of the interclass correlation coefficient ICC(three,1). Consequences: The machine was determined to show off excessive validity and accuracy (r = zero.928, p < zero.001; accuracy rate: 87.nine %) in determining in-bed displacement, turning over, and sitting up, and getting out of bed. The machine become mainly correct in detecting motion rightward (ninety %), turning over leftward (83%), sitting up leftward or rightward (87–93%), and getting out of bed (100%). The test–retest reliability ICC (three,1) fee was 0.968 (p < zero.001).
Face Recognition Using Raspberry PI for Mentally Retarded Person
The face recognition system described in this paper focuses on addressing the needs of individuals with intellectual disabilities. Intellectual disabilities often affect an individual's cognitive and adaptive functioning, making it challenging for them to perform everyday tasks independently. This system utilizes the capabilities of Raspberry Pi , a low cost single-board computer, to create an accessible and user-friendly solution for face recognition. The main objective of this system is to assist mentally challenged individuals in recognizing and identifying familiar faces. By utilizing face recognition technology, the system aims to enhance their independence, social interactions, and overall quality of life. The Raspberry Pi platform provides a flexible and affordable hardware foundation for implementing this system. The system leverages a pre-trained deep learning model for face recognition, such as OpenCV or dlib, to perform face detection and identification tasks. The model is trained on a dataset containing facial images of familiar individuals to ensure accurate recognition. Raspberry Pi's computational capabilities enable real-time processing of the captured video feed, facilitating prompt recognition and response.
IOT Assisted ECG Monitoring Framework with Secure Data Transmission Application
The growing Internet of Things (IoT) frame work enables us to create tiny devices that are capable of sensing processing and communicating, enabling sensors, embedding devices and other' things 'to be created which will help to understand the environment. In this paper, the IoT assisted electrocardiogram (ECG) monitoring framework with secure data transmission has been proposed in this research. With the proposed IoT assisted ECG monitoring system, the development and implementation of a light weight ECG Signal Strength Analysis has been proposed for automatic classification and real time implementation, using ECG sensors, Arduino, Android phones, Bluetooth and cloud servers. The Light weight Secure IoT (LS-IoT) and Light weight Access Control (LAC) have been introduced for asecuredatatypetransmission.Real-timeanalysisandverificationareperformedontheECGsignalsobtainedfromtheMIT-BI Hand Physio Net Challenges databases as well as the ECG signals for various physical activities. The potential for determining the clinical acceptability of ECG signals to increase the effectiveness, accuracy, and dependability of an unsupervised diagnostic system is significant in the proposed IoT assisted ECG monitoring framework.
IoT Based Complete Green House Monitoring And Controlling System
An overview of a greenhouse monitoring system that was constructed utilizing IoT devices and sensors is provided in this abstract. By offering real-time monitoring and management of environmental elements essential for plant development, the system attempts to optimize the cultivation process. Sensors with IoT capabilities gather information on temperature, humidity, light intensity, soil moisture, and CO2 levels, which is then sent to a central hub or cloud platform for analysis. The system has benefits including automation, data-driven decision-making, and remote monitoring. On their cell phones, farmers may get real-time data and warnings, allowing for flexible control of greenhouse operations. In order to find trends and recommend measures for enhancing agricultural output and resource utilisation, machine learning algorithms analyse the sensor data. Automation enables accurate environmental parameter management, lowering human error and increasing productivity. Farmers may increase crop output, maximise resource usage, and support sustainable agricultural practises by putting in place an IoT-based greenhouse monitoring system.
Sensor Network Based Smart Helmet for Bike Riders for Accident Prevention
Road accidents are increasing day by day because riders do not use helmet and due to alcohol consumption. A huge amount in today's world people die in traffic accidents. Accidents can occur when using a smart helmet detected. The Project Goal is to design smart helmet in case of an accident alcohol avoidance and alcohol detection. The IR sensor checks if the person is wearing it helmet or not. The gas sensor recognizes the alcohol substance in the rider breath. If the person doesn’t have a helmet and if they are consuming alcohol, a bike won't start. If there are no signs of alcohol and a helmet is worn, then only the bike starts. The moment the rider met with an accident, the sensor recognizes the condition of the motorcycle and reports the accident. Then The GPS in the bike sends the location of the accident site to the main server nearby hospitals.
Implementation and Design of Agriculture Robot Using IoT
Agriculture can be defined as the art, the science, and business of cultivating crops and livestock for economic purposes. At certain stages of human development, agriculture used to be the only known means of living. It is derived from the ‘Latin’ terms ager referring to the soil and culture to its cultivation. Agriculture is a broad term encompassing all aspects of crop production, horticulture, live stock farming, forestry etc.
An Optimized Technique for Image Classification Using Deep Learning
We propose a deep learning image classification model that aimed to serve as a framework and support for the recognition of big datasets of images. This paper explained the many forms of convolution neural networks and the fundamental steps involved in their use in image classification, starting with an analysis of the fundamental theory of neural networks. Secondly, an image classification deep learning model was proposed based on the improved convolution neural network structure, and noise reduction and parameter adjustment were carried out in the feature extraction process based on the current convolution neural network model. Finally, the deep learning model's structural optimisation was done to raise the model's classification efficiency and accuracy. Through studies, the association between the accuracy of many popular network models in image classification and the number of iterations was evaluated in order to confirm the effectiveness of the deep learning model proposed in this study in image classification. The model put forward in this paper was superior to other models in classification accuracy, according to the data. The training set and test set were used to evaluate and analyse the classification accuracy of the deep learning model before and after optimisation. The results demonstrated that, after the model recommended in this study had been fairly optimised, the accuracy of image classification had been substantially enhanced.
GSM Based Fall Alert Monitoring System Using Keypad Device
The International Classification of Diseases 11 (2018), published by the World Health Organization, divides vision impairment into two categories: distance and near-presenting vision impairment. The system prototype is necessary. It is a control order from the operator. It is the main form of communication for mute, visually impaired, and hearing persons. The goal of this initiative is to improve the quality of life for people with disabilities. By making things more accessible, it will be easier to meet their requirements and offer them challenges that will keep them motivated. The improvement of speech, hearing, and vision impairments is the main goal of this initiative. Here, organizing and categorizing the portable key- board device for information transfer from one location to another is the major objective.
A Non-Invasive Glucose Monitoring Device using NIR (Near Infra Red)
In a developing country like India, systemic chronic diseases reach unsustainable heights as the population grows. According to WHO, diabetes affects an estimated 28.7 million people worldwide, or 28.5% of the population. Diabetes affects around 8.5 million people who have yet to be diagnosed (2022). Diabetes is one of these metabolic systemic chronic diseases that has captured the world's attention. The primary goal of our research is to develop non-invasive blood glucose monitoring technology that will benefit a large number of patients. We analyze the research progress and significant problems of non-invasive blood glucose detecting technologies in our project evaluation. In our study, we present an effective NIR-based optical detecting system. The existing non-invasive glucose monitoring device had a 60% accuracy level, however the proposed model will have an accuracy of 80% and will have a significant advantage over the existing system. Furthermore, the information is continuously delivered to the personal computer via serial communication via the UART protocol.
Coffee Dispenser Machine
Coffee is one of the favorite drinks. He way of making coffee is brewing and using a machine, this paper proposes the design of Automatic Dispenser machine. The main objective of our project is to launch new technology application in society. This is Arduino based Dispenser machine that sales of coffee from machine. This paper attempt to provide solution on coin based Dispenser machine which is not returning the money. This paper attempt to provide solution on based Dispenser machine which is helps to coffee users. Most people are loves to drink coffee/tea which is made by an ordinary coffee shop or coffee maker machine. Also, the coffee trade exceeds US $ 10 Billion worldwide. The development of new modern hardware and software systems allows us to build an excellent coffee maker machine that satisfies customer needs. The Vending Machine is which delivers different products based on what the customer likes to drink. This kind of machine placed in shops, offices, institutes and various places where it required. It provides a wide variety of products in an automated process, without any manpower and easy to save precious time of humans in a fast-moving world. This paper compares different features like space, size, and time to prepare the drink and how fast it works. The power dissipation of a vending machine is one of the major problems faced by the users. And the availability of the product is known only in some places not every. This is an automated product to create our day to day life more convenient. The product must be hygienic.