This document describes a project that aims to help non-profit organizations maintain food quality and provide balanced diets. It involves developing both hardware and software components. The hardware uses sensors like MQ3 and temperature sensors connected to an Arduino board to detect spoiled food. If spoilage is detected, a buzzer and LED lights activate. Sensor data is sent to a Blynk app. The software is a web app that estimates food calories using machine learning. Users can upload images of foods, which are classified and linked to calorie information displayed on the app. Together, the system works to ensure unspoiled food is served and balanced diets with appropriate calorie levels are provided.
1. The document describes a smart refrigerator system that uses sensors and IoT technology to monitor food levels and conditions inside the refrigerator.
2. An ESP32 microcontroller is used as the central processing unit, connected to sensors like a load cell to detect food levels, temperature/humidity sensors, and a water level sensor.
3. The sensor data is sent to an Android app via WiFi to allow users to remotely monitor the refrigerator conditions and food levels, with features like automatic reordering when food gets low.
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This document describes a smart wearable system for patients with respiratory disorders using IoT. The system monitors patients' vital signs like heart rate, temperature, blood oxygen levels, etc. using sensors. It sends this data to the cloud for analysis and alerts doctors if thresholds are exceeded. An Android app allows doctors to monitor patients remotely and receive emergency notifications. The system aims to help manage respiratory conditions and detect exacerbations early through continuous remote monitoring.
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This document describes an IoT-based food tracking and management system that monitors temperature, humidity, and gas levels inside a food storage unit in real-time using sensors. The system utilizes a DHT11 sensor to measure temperature and humidity, an MQ4 gas sensor to detect harmful gases, a NodeMCU controller to manage the sensors, and a Blynk server and mobile app for remote monitoring. The system is designed to maintain safe storage conditions and reduce food waste through real-time monitoring and control of the storage environment. Testing showed the system can effectively monitor conditions and activate an exhaust fan when temperature exceeds thresholds to ensure food safety.
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This document proposes a smart recipe system that uses sensors to detect the level of ingredients in containers in a user's kitchen. It connects to a cloud database to store this ingredient level information. When a user wants to cook, the system can quickly generate a list of recipe recommendations based on the ingredients that are available. It aims to help users decide what to cook by checking current ingredient levels in real-time and matching them to recipes. The system architecture involves level sensors, cloud data storage, and a mobile app for users to select from the recommended recipes. The goal is to minimize the time users spend deciding what to make after a long day by leveraging sensor data and automated recommendations.
IRJET - Farmer Surveillance System with Paddy Disease DetectionIRJET Journal
This document describes a farmer surveillance system using sensors and image processing techniques to monitor fields and detect diseases in paddy crops. The system uses sensors to monitor soil moisture, temperature, and humidity and sends that data to the cloud for remote access via a web application. A camera captures images of the crop which are analyzed using deep learning algorithms like VGG16 and AlexNet to detect common rice diseases. When a disease is identified, the system recommends appropriate fertilizer treatments. The system is intended to help farmers efficiently monitor crops and address diseases early to minimize losses and reduce costs.
“Plant Disease Detection by Using Deep LearningAlgorithm with Product, Price ...IRJET Journal
This document summarizes a research paper that proposes using deep learning algorithms like convolutional neural networks (CNNs) to detect plant diseases, recommend products and prices, and predict crops. The system is designed to help farmers by identifying diseases from images, providing treatment options and costs, and recommending suitable crops for their soil conditions and location based on parameters like temperature, humidity and moisture. It describes collecting seed data, training a CNN model on a plant disease image dataset, and using neural networks to identify disease colors and textures for diagnosis. The system aims to automate crop yield prediction and guide new farmers in India by deploying machine learning technologies.
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This document proposes a smart medical assistant system using a wearable device to monitor health and predict medical emergencies like heart attacks. The system has 5 modules: 1) a hardware module containing sensors to monitor heart rate and temperature, 2) a web application for hospitals, 3) a heart attack prediction module using machine learning, 4) a mobile application for patients and ambulances, and 5) an API module connecting the web and mobile applications. The system aims to detect medical emergencies using sensor data, alert hospitals and contacts, and provide health advice and ambulance tracking to assist users.
A Review Paper on Doctorless Intelligent Covid CenterIRJET Journal
This document reviews a proposed contactless patient health monitoring system for COVID centers. The system would employ touchless technology to prevent infection spread by avoiding direct contact with patients. Sensors would collect patient data like temperature and oxygen levels and transmit it to a microcontroller. The data would be stored in LabVIEW on a server. Applications like paramedic robots would be used to deliver meals and medicine to eliminate personal contact between patients and healthcare providers. The goal is to minimize physical contact with COVID patients and allow remote monitoring by doctors.
1. The document describes a smart refrigerator system that uses sensors and IoT technology to monitor food levels and conditions inside the refrigerator.
2. An ESP32 microcontroller is used as the central processing unit, connected to sensors like a load cell to detect food levels, temperature/humidity sensors, and a water level sensor.
3. The sensor data is sent to an Android app via WiFi to allow users to remotely monitor the refrigerator conditions and food levels, with features like automatic reordering when food gets low.
Smart Wearable System For Patients With Respiratory DisordersUsing IOTIRJET Journal
This document describes a smart wearable system for patients with respiratory disorders using IoT. The system monitors patients' vital signs like heart rate, temperature, blood oxygen levels, etc. using sensors. It sends this data to the cloud for analysis and alerts doctors if thresholds are exceeded. An Android app allows doctors to monitor patients remotely and receive emergency notifications. The system aims to help manage respiratory conditions and detect exacerbations early through continuous remote monitoring.
IoT-Based Food Tracking and Management System Employing NodeMCU and the Blynk...IRJET Journal
This document describes an IoT-based food tracking and management system that monitors temperature, humidity, and gas levels inside a food storage unit in real-time using sensors. The system utilizes a DHT11 sensor to measure temperature and humidity, an MQ4 gas sensor to detect harmful gases, a NodeMCU controller to manage the sensors, and a Blynk server and mobile app for remote monitoring. The system is designed to maintain safe storage conditions and reduce food waste through real-time monitoring and control of the storage environment. Testing showed the system can effectively monitor conditions and activate an exhaust fan when temperature exceeds thresholds to ensure food safety.
IRJET- Smart Recipe-An Innovative Way to CookIRJET Journal
This document proposes a smart recipe system that uses sensors to detect the level of ingredients in containers in a user's kitchen. It connects to a cloud database to store this ingredient level information. When a user wants to cook, the system can quickly generate a list of recipe recommendations based on the ingredients that are available. It aims to help users decide what to cook by checking current ingredient levels in real-time and matching them to recipes. The system architecture involves level sensors, cloud data storage, and a mobile app for users to select from the recommended recipes. The goal is to minimize the time users spend deciding what to make after a long day by leveraging sensor data and automated recommendations.
IRJET - Farmer Surveillance System with Paddy Disease DetectionIRJET Journal
This document describes a farmer surveillance system using sensors and image processing techniques to monitor fields and detect diseases in paddy crops. The system uses sensors to monitor soil moisture, temperature, and humidity and sends that data to the cloud for remote access via a web application. A camera captures images of the crop which are analyzed using deep learning algorithms like VGG16 and AlexNet to detect common rice diseases. When a disease is identified, the system recommends appropriate fertilizer treatments. The system is intended to help farmers efficiently monitor crops and address diseases early to minimize losses and reduce costs.
“Plant Disease Detection by Using Deep LearningAlgorithm with Product, Price ...IRJET Journal
This document summarizes a research paper that proposes using deep learning algorithms like convolutional neural networks (CNNs) to detect plant diseases, recommend products and prices, and predict crops. The system is designed to help farmers by identifying diseases from images, providing treatment options and costs, and recommending suitable crops for their soil conditions and location based on parameters like temperature, humidity and moisture. It describes collecting seed data, training a CNN model on a plant disease image dataset, and using neural networks to identify disease colors and textures for diagnosis. The system aims to automate crop yield prediction and guide new farmers in India by deploying machine learning technologies.
IRJET- Smart Medical Assistant using Wearable DeviceIRJET Journal
This document proposes a smart medical assistant system using a wearable device to monitor health and predict medical emergencies like heart attacks. The system has 5 modules: 1) a hardware module containing sensors to monitor heart rate and temperature, 2) a web application for hospitals, 3) a heart attack prediction module using machine learning, 4) a mobile application for patients and ambulances, and 5) an API module connecting the web and mobile applications. The system aims to detect medical emergencies using sensor data, alert hospitals and contacts, and provide health advice and ambulance tracking to assist users.
A Review Paper on Doctorless Intelligent Covid CenterIRJET Journal
This document reviews a proposed contactless patient health monitoring system for COVID centers. The system would employ touchless technology to prevent infection spread by avoiding direct contact with patients. Sensors would collect patient data like temperature and oxygen levels and transmit it to a microcontroller. The data would be stored in LabVIEW on a server. Applications like paramedic robots would be used to deliver meals and medicine to eliminate personal contact between patients and healthcare providers. The goal is to minimize physical contact with COVID patients and allow remote monitoring by doctors.
IRJET- Soil, Water and Air Quality Monitoring System using IoTIRJET Journal
This document summarizes a research paper on developing a soil, water, and air quality monitoring system using IoT technologies. Sensors are used to measure various parameters of soil, water, and air quality, including pH, moisture, temperature, turbidity, and nutrients. The sensor data is sent to a Raspberry Pi controller and then uploaded to the cloud. If measurements are abnormal, an alert message is sent. The system aims to help farmers and users monitor natural resource quality and make informed decisions. Future work could include using machine learning to analyze trends and make crop recommendations based on sensor readings.
IoT Based Patient Biomedical Signal Tracking SystemIRJET Journal
This document describes an IoT-based patient biomedical signal tracking system that monitors physiological parameters like temperature, heart rate, and oxygen levels in the blood. Sensors are connected to a Node MCU microcontroller which collects and displays the data on an OLED display. The data is also sent to the cloud using WiFi and can be accessed by doctors through a website or app. If emergency conditions are detected, such as high temperature, notification messages and an email are sent to the doctor. The system provides low-cost remote patient monitoring and aims to improve healthcare access and outcomes.
This document describes an IOT-based health monitoring system that measures a patient's temperature, heart rate, and oxygen levels remotely. Sensors are used to monitor these vital signs, which are sent to a microcontroller and displayed on an LCD screen and website. This allows healthcare providers to remotely track patients' conditions in real-time. The system aims to improve medical care, especially for those in rural areas or those wanting to avoid hospital visits during infectious disease outbreaks. Results showed the IOT system was low-cost, non-invasive, and flexible in monitoring health from different locations. Future work could involve adding more sensors to monitor additional physiological parameters.
IRJET- Remotely Monitoring Health of the Solar Power System using ArduinoIRJET Journal
This document describes a system to remotely monitor the health of a solar power system using Arduino. The system monitors parameters like voltage, current from the solar panels using sensors and transmits the data via ESP8266 WiFi module to a cloud server (ThingSpeak). The data is displayed on a LCD screen and can be accessed from anywhere via the internet. This allows real-time monitoring of the solar power system for performance evaluation and preventative maintenance to address any issues impacting output.
IRJET - Prevention of Crop Disease in Plants (Groundnut) using IoT and Ma...IRJET Journal
The article discusses international issues. It mentions that globalization has increased economic interdependence between nations while also raising tensions over immigration and trade. Solutions will require cooperation and compromise and a recognition that isolationism is not a viable strategy in an interconnected world.
AI Based Smart Agriculture – Leaf Disease Prediction Using Optimized CNN ModelIRJET Journal
This document discusses using optimized convolutional neural network (CNN) models for leaf disease prediction in smart agriculture. Sensors are used to collect environmental data from fields, and images of plant leaves are analyzed for disease identification. Three CNN methods - fast R-CNN, faster R-CNN, and Mask R-CNN - are evaluated and the best method is selected based on prediction accuracy. The optimized CNN model identifies diseases and recommends suitable pesticides, while sensor data is also used for irrigation control and crop recommendations based on soil conditions. The system aims to help farmers detect diseases early and improve crop productivity using artificial intelligence and internet of things technologies.
This document describes a proposed calorie detection system using convolutional neural networks and image processing. The system aims to classify food items from images and estimate calorie counts to help users monitor their diets. It uses a CNN model trained on image data to classify foods and estimate portions. The CNN model is built using TensorFlow and trained on segmented image data. Once trained, the model can classify new images and provide estimated calorie counts to help users track their diets and calorie intake.
Android application for detection of leaf disease (Using Image processing and...IRJET Journal
This document describes an Android application for detecting leaf diseases using image processing and neural networks. The application uses a convolutional neural network (CNN) model trained on a dataset of images of healthy and unhealthy plant leaves. The CNN classifies leaf images uploaded by users to identify the disease and provide an accurate diagnosis. The application aims to help farmers and students quickly identify plant diseases to control their spread and reduce agricultural losses. It analyzes leaf images using techniques like preprocessing, augmentation, feature extraction, and classification with a CNN architecture. The trained model is integrated into an Android application using TensorFlow Lite to enable real-time disease detection from smartphone photos of leaves.
IOT Based Monitoring of Fruit Freshness Using Arduino NanoIRJET Journal
This document describes an IOT-based system to monitor the freshness of fruits using an Arduino Nano microcontroller. The system measures the concentration of ethylene gas and other gases in the fruit's atmosphere using MQ3 and MQ5 gas sensors. It also measures temperature and humidity using a DHT11 sensor. The sensors detect factors that indicate ripeness and spoilage. If thresholds for ethylene levels, other gases, temperature or humidity are exceeded, the system triggers a buzzer and displays warnings on an LCD screen. The system was tested on apples and bananas. It was found that excessively decayed fruit produces over 300ppm of ethylene. The simple and low-cost device could
Plant Disease Detection Using InceptionV3IRJET Journal
This document summarizes a research paper that proposes using an InceptionV3 convolutional neural network (CNN) to detect diseases in cotton plant leaves. The paper first reviews existing methods for plant disease detection using digital image processing and machine learning algorithms. It then describes collecting a cotton disease dataset and preprocessing the images. Next, it explains using transfer learning with the InceptionV3 CNN model for feature extraction and disease recognition. The proposed method is implemented and tested on the cotton disease dataset, achieving accurate detection. Finally, the paper concludes that CNNs like InceptionV3 show promise for automated and reliable plant disease detection but that more research is still needed.
An effective identification of crop diseases using faster region based convol...IJECEIAES
The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop.
IoT Based Smart Ventilator & Patient Monitoring SystemIRJET Journal
This document describes an IoT-based smart ventilator and patient monitoring system. The system has two parts - an IoT ventilator that uses a servo motor to pump air into an Ambu bag to ventilate patients, and a patient monitoring system that measures vital signs like temperature, blood oxygen levels, and heart rate. Both systems connect to the internet using ESP8266 and send data to a website where doctors can monitor patients. The integrated system provides low-cost ventilation and health monitoring, especially important during the COVID-19 pandemic. It allows remote patient monitoring to help doctors track vitals and decide if ventilation is needed.
IRJET- Design and Implementation of Aquaculture Monitoring and Controlling Sy...IRJET Journal
This document describes the design and implementation of an aquaculture monitoring and controlling system using IoT. The system monitors temperature and pH levels in an aquarium and updates the data to the cloud. It uses heating and cooling mechanisms to automatically control the temperature. If the pH level changes, a notification is sent to the user. The goal is to create a controlled environment for prawn hatcheries by reducing human error and monitoring from anywhere using collected data.
WEB BASED NUTRITION AND DIET ASSISTANCE USING MACHINE LEARNINGIRJET Journal
The document describes a proposed web-based nutrition and diet assistance system using machine learning. The system aims to accurately identify foods from images using a convolutional neural network (CNN) model, calculate the nutritional content of the foods, determine the user's BMI, and provide personalized diet recommendations. The system uses techniques like pre-processing, region proposal networks, feature extraction, and CNNs to classify foods, retrieve nutritional data, and suggest diets tailored for the user's BMI and food choices. The goal is to help users conveniently track their nutrition intake and maintain a balanced diet for better health outcomes.
IRJET - Remote Health Monitoring System using IoTIRJET Journal
This document describes a remote health monitoring system using IoT (Internet of Things) and Arduino. The system collects health parameters like temperature, heart rate, and blood pressure from sensors and sends the data remotely to be viewed and analyzed. It notifies patients and doctors if any parameters exceed thresholds. The system is intended to help monitor patients outside of clinical settings and reduce healthcare costs. It discusses implementing the system using an Arduino microcontroller to process sensor data and an ESP8266 WiFi module to transmit data to a remote server. Results show the system can successfully post sensor readings online. The system provides a low-cost way to remotely monitor patients' health.
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This document describes a proposed system called the Eating Habit and Health Monitoring System Using Android Based Machine Learning. The system uses a wearable device with a vibration sensor that is worn around the neck to collect acoustic signals during eating. The signals are processed by an embedded hardware prototype and sent via Bluetooth to a smartphone. The smartphone application analyzes the signals using hidden Markov models to detect chewing and swallowing events and recognize food types. It provides notifications to the user about their food intake and suggests healthier habits based on their calorie consumption goals. The overall goal is to develop an easy-to-use, non-invasive solution for continuously monitoring daily food intake using machine learning techniques.
IRJET - Poultry Farm Controlling based on IoTIRJET Journal
This document describes a poultry farm monitoring system using IoT technology. The system uses sensors to monitor temperature, humidity, gas levels and food levels in the farm. An Arduino Mega controller collects data from the sensors and sends it to the cloud. Users can then view the sensor data through a mobile app, which will also notify them of any abnormal conditions. The system aims to automate 80% of the farm monitoring process and remotely manage conditions in the poultry house.
Solar Powered Smart Agriculture Systems Using WSN Via IoTIRJET Journal
The document describes a proposed solar-powered smart agriculture system using wireless sensor networks and the Internet of Things. Sensors would monitor soil moisture, water level, humidity, temperature, and other crop/field conditions. A NodeMCU microcontroller would collect sensor data and send it via the cloud to a mobile app for farmers to monitor in real-time. This would help farmers optimize crop yields, efficiency, and reduce stress on farmers by automating some agriculture tasks. The system is intended to advance smart agriculture using renewable energy and modern technologies.
This document describes a smart yoga instructor system that uses accelerometer sensors and an IoT platform to detect a user's yoga postures and provide feedback on correctness. Sensors placed on the user's limbs measure orientation data, which is sent to a microcontroller and then to the cloud. A mobile app accesses the cloud data to compare real-time poses to predefined poses and instruct the user. The system aims to help users practice yoga correctly anywhere without an in-person instructor.
Smart system for Milk quality analysis and billing systemIRJET Journal
This document discusses a smart system for milk quality analysis and billing. The system uses sensors to analyze milk samples and determine key quality metrics like fat content, pH levels, humidity, and harmful gases. Sensors include an LDR sensor to measure fat, a pH sensor, humidity sensor, and gas sensor. The Arduino microcontroller reads the sensor data and sends it to an Android phone app for remote monitoring and billing calculations. The system aims to automate milk testing, save labor costs, and ensure farmers are paid fairly based on real-time quality analysis.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
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2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
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