The document describes a proposed fire detection and extinguishing system using image processing techniques and a Maixduino AI controller. The system uses cameras to capture images or video and analyzes them using computer vision algorithms to detect fires. Upon detection, the system automatically triggers an extinguishing mechanism to suppress the fire. The goal is to enhance fire safety through early detection and a swift response.
IRJET- Intruder Detection System using Camera with Alert ManagementIRJET Journal
This document describes a proposed intruder detection system using a camera. The system would work as follows:
1. A camera would continuously capture video frames and an image processing processor would compare the latest frame to a static threshold frame to detect differences.
2. If a difference is detected above a certain threshold using a sum of absolute differences (SAD) algorithm, it would indicate a potential intruder.
3. The system would then raise an alert if an intruder is confirmed, such as sending an email or message with the captured photo of the intruder.
The goal is to create an affordable intruder detection system that can detect intruders and raise alerts, providing security for places when unattended.
Forest Fire Detection Using Deep Learning and Image RecognitionIRJET Journal
This document describes a proposed system for forest fire detection using deep learning and image recognition techniques. The system aims to build a more accurate fire detection model using a customized VGG16 convolutional neural network. It involves collecting fire and non-fire images to train and test the model. The proposed system is expected to achieve higher accuracy than existing sensor-based systems by directly analyzing images to classify fires versus other heat sources.
IRJET- Fire Detection using Infrared Images for Uav-Based Forest Fire Sur...IRJET Journal
This document describes a system for detecting forest fires using infrared images from unmanned aerial vehicles (UAVs). The system uses a simple fire detection algorithm based on thresholding infrared images to detect areas of high heat that could indicate a fire. Multiple UAVs can work collaboratively to monitor large forest areas. The system was tested using controlled forest fires involving three UAVs: two autonomous helicopters and one blimp. The algorithm detects fires by analyzing differences in pixel intensities between consecutive image frames to identify changes that indicate areas of high heat and potential fires.
Fire Detection based on Color, Shape and MotionIRJET Journal
This document describes a computer vision-based fire detection system that analyzes video frames captured by a camera. It uses algorithms to detect fires based on color, shape, and motion in the video frames. The system sends SMS alerts to notify emergency services if a fire is detected. It works by continuously capturing frames with a camera and applying fire detection algorithms to analyze the color, convert the images to HSV color space, and perform background subtraction to isolate moving objects. If fire is detected in the image processing, a microcontroller sends an SMS using a GSM module and also triggers an alarm with a buzzer and message on an LCD display. The system provides faster response times than traditional smoke detectors through real-time video analysis.
The document proposes a new fire detection system with a multifunctional artificial intelligence (AI) framework and a data transfer delay minimization mechanism. The framework includes multiple machine learning algorithms and an adaptive fuzzy algorithm to improve fire detection accuracy. Additionally, Direct-MQTT based on SDN is introduced to solve traffic concentration problems and reduce the end-to-end delay by an average of 72%. The system aims to improve fire safety in smart cities by more accurately and quickly detecting fires.
Dependable fire detection_system_with_multifunctioBharath Kumar
This document proposes a new fire detection system that uses a multifunctional artificial intelligence framework and a data transfer delay minimization mechanism. The AI framework includes multiple machine learning algorithms and an adaptive fuzzy algorithm to improve fire detection accuracy by analyzing data from multiple fire sensors. A Direct-MQTT approach based on SDN is also introduced to reduce data transfer delays by minimizing queuing delays that occur with traditional centralized MQTT brokers. The proposed system achieved over 95% accuracy in fire detection and reduced average end-to-end delays by 72% compared to existing systems.
IRJET- Review on Image Processing based Fire Detetion using Raspberry PiIRJET Journal
The document describes a proposed image processing system using a Raspberry Pi to detect fires. The system would use a camera to capture images and the Raspberry Pi would process the images to detect fire signatures using heat patterns and colors. If a fire is detected, the system would sound an alarm. The proposed system aims to provide early fire detection without the need for additional sensors. It reviews existing fire detection methods and outlines the modules of the proposed system, including image capture, color-based segmentation, fire pattern recognition, and an emergency alarm trigger.
IRJET- Fire Detector using Deep Neural NetworkIRJET Journal
This document summarizes a research paper that proposes using a deep neural network for real-time fire detection from CCTV surveillance videos. Specifically, it uses the SqueezeNet architecture, which requires fewer parameters and memory than other networks. The proposed system analyzes frames from surveillance videos and compares images to a trained dataset of fire and non-fire images using SqueezeNet. If a fire is detected, an alert message is immediately sent to the fire station. The system aims to provide early detection of fires from existing CCTV infrastructure to reduce accidents.
IRJET- Intruder Detection System using Camera with Alert ManagementIRJET Journal
This document describes a proposed intruder detection system using a camera. The system would work as follows:
1. A camera would continuously capture video frames and an image processing processor would compare the latest frame to a static threshold frame to detect differences.
2. If a difference is detected above a certain threshold using a sum of absolute differences (SAD) algorithm, it would indicate a potential intruder.
3. The system would then raise an alert if an intruder is confirmed, such as sending an email or message with the captured photo of the intruder.
The goal is to create an affordable intruder detection system that can detect intruders and raise alerts, providing security for places when unattended.
Forest Fire Detection Using Deep Learning and Image RecognitionIRJET Journal
This document describes a proposed system for forest fire detection using deep learning and image recognition techniques. The system aims to build a more accurate fire detection model using a customized VGG16 convolutional neural network. It involves collecting fire and non-fire images to train and test the model. The proposed system is expected to achieve higher accuracy than existing sensor-based systems by directly analyzing images to classify fires versus other heat sources.
IRJET- Fire Detection using Infrared Images for Uav-Based Forest Fire Sur...IRJET Journal
This document describes a system for detecting forest fires using infrared images from unmanned aerial vehicles (UAVs). The system uses a simple fire detection algorithm based on thresholding infrared images to detect areas of high heat that could indicate a fire. Multiple UAVs can work collaboratively to monitor large forest areas. The system was tested using controlled forest fires involving three UAVs: two autonomous helicopters and one blimp. The algorithm detects fires by analyzing differences in pixel intensities between consecutive image frames to identify changes that indicate areas of high heat and potential fires.
Fire Detection based on Color, Shape and MotionIRJET Journal
This document describes a computer vision-based fire detection system that analyzes video frames captured by a camera. It uses algorithms to detect fires based on color, shape, and motion in the video frames. The system sends SMS alerts to notify emergency services if a fire is detected. It works by continuously capturing frames with a camera and applying fire detection algorithms to analyze the color, convert the images to HSV color space, and perform background subtraction to isolate moving objects. If fire is detected in the image processing, a microcontroller sends an SMS using a GSM module and also triggers an alarm with a buzzer and message on an LCD display. The system provides faster response times than traditional smoke detectors through real-time video analysis.
The document proposes a new fire detection system with a multifunctional artificial intelligence (AI) framework and a data transfer delay minimization mechanism. The framework includes multiple machine learning algorithms and an adaptive fuzzy algorithm to improve fire detection accuracy. Additionally, Direct-MQTT based on SDN is introduced to solve traffic concentration problems and reduce the end-to-end delay by an average of 72%. The system aims to improve fire safety in smart cities by more accurately and quickly detecting fires.
Dependable fire detection_system_with_multifunctioBharath Kumar
This document proposes a new fire detection system that uses a multifunctional artificial intelligence framework and a data transfer delay minimization mechanism. The AI framework includes multiple machine learning algorithms and an adaptive fuzzy algorithm to improve fire detection accuracy by analyzing data from multiple fire sensors. A Direct-MQTT approach based on SDN is also introduced to reduce data transfer delays by minimizing queuing delays that occur with traditional centralized MQTT brokers. The proposed system achieved over 95% accuracy in fire detection and reduced average end-to-end delays by 72% compared to existing systems.
IRJET- Review on Image Processing based Fire Detetion using Raspberry PiIRJET Journal
The document describes a proposed image processing system using a Raspberry Pi to detect fires. The system would use a camera to capture images and the Raspberry Pi would process the images to detect fire signatures using heat patterns and colors. If a fire is detected, the system would sound an alarm. The proposed system aims to provide early fire detection without the need for additional sensors. It reviews existing fire detection methods and outlines the modules of the proposed system, including image capture, color-based segmentation, fire pattern recognition, and an emergency alarm trigger.
IRJET- Fire Detector using Deep Neural NetworkIRJET Journal
This document summarizes a research paper that proposes using a deep neural network for real-time fire detection from CCTV surveillance videos. Specifically, it uses the SqueezeNet architecture, which requires fewer parameters and memory than other networks. The proposed system analyzes frames from surveillance videos and compares images to a trained dataset of fire and non-fire images using SqueezeNet. If a fire is detected, an alert message is immediately sent to the fire station. The system aims to provide early detection of fires from existing CCTV infrastructure to reduce accidents.
Development in building fire detection and evacuation system-a comprehensive ...IJECEIAES
Fire is both beneficial to man and his environment as well as destructive and deadly among all the natural disasters. A fire Accident occurs very rarely, but once it crops up its consequences will be devastating. The early detection of fire will help to avoid further consequences and saves the life of people. During the fire accidents, it is also important to guide people within the building to exit safely. Because of this, the paper gives a review of literature related to recent advancements in building fire detection and emergency evacuation system. It is intended to provide details about fire simulation tools with features, suitable hardware, communication methods, and effective user interface.
SUPPORT VECTOR MACHINE-BASED FIRE OUTBREAK DETECTION SYSTEMijscai
This study employed Support Vector Machine (SVM) in the classification and prediction of fire outbreak based on fire outbreak dataset captured from the Fire Outbreak Data Capture Device (FODCD). The fire outbreak data capture device (FODCD) used was developed to capture environmental parameters values used in this work. The FODCD device comprised DHT11 temperature sensor, MQ-2 smoke sensor, LM393 Flame sensor, and ESP8266 Wi-Fi module, connected to Arduino nano v3.0.board. 700 data point were captured using the FODCD device, with 60% of the dataset used for training while 20% was used for testing and validation respectively. The SVM model was evaluated using the True Positive Rate (TPR), False Positive Rate (FPR), Accuracy, Error Rate (ER), Precision, and Recall performance metrics. The performance results show that the SVM algorithm can predict cases of fire outbreak with an accuracy of 80% and a minimal error rate of 0.2%. This system was able to predict cases of fire outbreak with a higher degree of accuracy. It is indicated that the use of sensors to capture real world dataset, and machine learning algorithm such as support vector machine gives a better result to the problem of fire management.
IRJET - Real-Time Analysis of Video Surveillance using Machine Learning a...IRJET Journal
This document discusses a proposed real-time video surveillance system that utilizes machine learning, computer vision, and image processing algorithms. The system aims to detect and analyze objects of interest in CCTV footage in order to identify suspicious activities and assist authorities. It employs algorithms for face detection and recognition, as well as detection of weapons and abnormal movements. The system uses frameworks like OpenCV and TensorFlow to perform tasks like facial analysis, age and gender estimation, human pose estimation, and weapon detection in real-time video streams. It analyzes existing algorithms and evaluates their suitability for the system. The results of implementing and testing various algorithms on sample footage are also presented.
IRJET- Surveillance of Object Motion Detection and Caution System using B...IRJET Journal
This document describes a proposed surveillance system using a block matching algorithm for motion detection. The system would use IP cameras to stream video that is monitored for unauthorized activity. Motion detection is performed by comparing frames using the block matching algorithm to detect changes in pixel intensity values, which would trigger an alarm. The block matching algorithm divides frames into blocks of pixels and validates the maximum and minimum intensity of each pixel. Comparing blocks between frames identifies motion if intensity values change beyond a threshold. If motion is detected in a designated sensitive area, the system saves the video and sends alerts by email and mobile notification to users.
Human Motion Detection in Video Surveillance using Computer Vision TechniqueIRJET Journal
The document discusses a technique for detecting human motion in video surveillance using computer vision. It proposes a method called DECOLOR (Detecting Contiguous Outliers in the LOw-rank Representation) that formulates object detection as outlier detection in a low-rank representation of video frames. This allows it to detect moving objects flexibly without assumptions about foreground or background behavior. DECOLOR simultaneously performs object detection and background estimation using only the test video sequence, without requiring training data. The method models the outlier support explicitly and favors spatially contiguous outliers, making it suitable for detecting clustered foreground objects like people. It achieves more accurate detection and background estimation than state-of-the-art robust principal component analysis methods.
Computer Vision-Based Early Fire Detection Using Machine LearningIRJET Journal
This document presents a computer vision-based system for early fire detection using machine learning. It captures video using a webcam and processes the frames to detect fire. The frames are converted to different color models and compared using OpenCV. Morphological transformations and thresholding are applied to detect fire regions. If fire is detected, an alarm is triggered and a notification email is sent. The system aims to reduce limitations of conventional fire detection methods and optimize detection using image processing techniques. A literature review is also presented discussing previous works on fire detection using computer vision and machine learning.
IRJET- Intrusion Detection through Image Processing and Getting Notified ...IRJET Journal
This document describes a proposed smart home intrusion detection system that uses image processing, face recognition, and notification technologies. The system would use an infrared camera and sensors to detect intruders, capture images of their faces, compare the images to a database to identify known intruders, and immediately notify home owners via mobile app with push notifications and images of the intruders. It discusses the system architecture, use of Raspberry Pi, image processing algorithms like LBPH, challenges with current systems, and outlines the development of an Android mobile app to facilitate user notifications.
Smart surveillance systems play an important role in security today. The goal of security systems is to protect users against fires, car accidents, and
other forms of violence. The primary function of these systems is to offer security in residential areas. In today’s culture, protecting our homes is
critical. Surveillance, which ranges from private houses to large corporations, is critical in making us feel safe. There are numerous machine learning algorithms for home security systems; however, the deep learning convolutional neural network (CNN) technique outperforms the others. The
Keras, Tensorflow, Cv2, Glob, Imutils, and PIL libraries are used to train and assess the detection method. A web application is used to provide a
user-friendly environment. The flask web framework is used to construct it. The flash-mail, requests, and telegram application programming interface (API) apps are used in the alerting approach. The surveillance system tracks
abnormal activities and uses machine learning to determine if the scenario is normal or not based on the acquired image. After capturing the image, it is
compared with the existing dataset, and the model is trained using normal events. When there is an anomalous event, the model produces an output from which the mean distance for each frame is calculated.
The document presents a deep learning-based fire and smoke detection system. It proposes a convolutional neural network (CNN) architecture for feature extraction from images to classify scenes as containing fire, smoke, or neither. The CNN was trained on a dataset of over 5000 images across three classes and achieved 96.3% accuracy for fire/smoke detection over 100 epochs. Future work could focus on improving model accuracy through additional data and real-time recognition capabilities. The system shows potential for computer vision-based fire detection as an alternative to traditional sensor-based methods.
IRJET-An Automatic Fire Detection and Warning System under Home Video Surveil...IRJET Journal
This document presents an automatic fire detection and warning system using video surveillance. The system uses a Raspberry Pi connected to a USB camera to capture images and detect fires based on color analysis in real-time. It also includes smoke, LPG, and motion sensors. If a fire is detected, it will send a warning message via email with location details. The system was tested under different scenarios and proved efficient at identifying fires. It provides an improved method over conventional sensors by leveraging video analysis and integrating multiple sensors for robust detection.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Motion Detection System for Security Using IoT- SurveyIRJET Journal
This document discusses a survey of motion detection systems for security using IoT. It begins with an abstract describing how intrusion detection systems with alarm systems have become necessary due to frequent burglaries. It then discusses how motion can be detected using devices that detect changes in speed, vector, or environment. The project discussed uses a PIR sensor coupled with a microcontroller to detect intruder motion and activate an alarm. It also reviews related works involving using sensor networks and deep learning models for motion detection, comparing performance of different motion detectors, PIR sensor-based security systems, and adaptive background removal for motion detection in video surveillance. It concludes that a modular home security system communicating via phone call could be useful for homes, businesses, and
IRJET- Convenience Improvement for Graphical Interface using Gesture Dete...IRJET Journal
This document discusses a proposed system for improving graphical user interfaces using hand gesture detection. The system aims to allow users to access information from the internet without using input devices like a mouse or keyboard. It uses a webcam to capture images of hand gestures, which are then processed using techniques like skin color segmentation, principal component analysis, and template matching to recognize the gestures. The recognized gestures can then be linked to retrieving specific data from pre-defined URLs. An evaluation of the system found it had an accuracy rate of 90% in real-time testing for retrieving data from 10 different URLs using 10 unique hand gestures. The proposed system provides a more convenient interface compared to traditional mouse and keyboard methods.
Sensor Fault Detection in IoT System Using Machine LearningIRJET Journal
This document summarizes research on using machine learning techniques for sensor fault detection in IoT systems. The researchers collected temperature and humidity data from a DHT22 sensor and injected drift faults using an Arduino microcontroller. They extracted time-domain features from the normal and faulty signals and used them to train classifiers like artificial neural networks, support vector machines, naive Bayes, k-nearest neighbors, and decision trees. The trained models detected drift faults in the sensor output in real-time on an ESP8266 device. Support vector machines and artificial neural networks achieved the best performance based on accuracy, recall, F1-score metrics. The lightweight system demonstrates potential for low-cost, real-time sensor fault detection using machine learning.
IRJET- A Hybrid Approach for Fire Safety Intensives Automatic Assistance ...IRJET Journal
This document presents a hybrid approach for an automatic fire safety assistance system. It proposes extracting frames from video to convert to images, then using edge detection and image segmentation to separate the foreground fire from the background. Features are then extracted using 7 rules to identify fire pixels based on their color space values. Color detection is used to isolate pixels meeting thresholds for red, green, and blue channel values as well as saturation to accurately identify flame pixels despite lighting conditions. The system aims to provide early fire detection to minimize damage through computer vision techniques.
IRJET - Contactless Biometric Security System using Finger Knuckle PatternsIRJET Journal
This document proposes a contactless biometric security system using finger knuckle patterns for authentication. Finger knuckle patterns provide accurate identification similar to fingerprints but can be captured contactless. The proposed system uses a convolutional neural network and Speedup Robust Feature algorithm for fast and accurate matching of knuckle patterns from images. This combination allows recognition within the shortest time for a live security system. An illumination controller is also used to standardize lighting and improve image quality. The system aims to securely authenticate users by matching their knuckle patterns against a stored database.
Design And Development of Fire Fighting RobotIRJET Journal
This document discusses the design and development of a firefighting robot based on an Arduino microcontroller. The robot is equipped with sensors to detect fires and obstacles. It can navigate manually through an environment and extinguish fires using a water pump and nozzle. The robot also has wireless communication via Bluetooth to allow for remote control. Computer vision algorithms using OpenCV are used for the primary fire detection system, while additional sensors provide secondary verification of fires. Testing showed the robot could accurately detect and localize fires. The conclusion discusses how such robots could assist firefighters by making firefighting safer and more effective.
Virtual Yoga System Using Kinect SensorIRJET Journal
The document describes a virtual yoga system using the Microsoft Kinect sensor. The system aims to make yoga exercises more engaging and motivating for patients by tracking their poses in real-time and providing feedback. It recognizes skeleton joints and yoga postures using the Kinect's depth sensing capabilities. Voice instructions guide users through different poses. The system is intended to address issues with traditional physiotherapy being tedious and repetitive. It allows customizing exercises to individual needs and challenges. Recognizing poses accurately in real-time could help patients perform exercises correctly and consistently at home without direct supervision.
The document describes a gesture recognition system that uses computer vision techniques. It discusses different approaches to hand gesture recognition including vision-based, glove-based, and depth-based techniques. The proposed system uses computer vision and media pipe libraries to track hand landmarks and recognize gestures in real-time. It then uses those gestures to control functions like a virtual mouse, change volume, and zoom in/out. The system aims to provide natural human-computer interaction through contactless hand gesture recognition.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
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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This document discusses a proposed real-time video surveillance system that utilizes machine learning, computer vision, and image processing algorithms. The system aims to detect and analyze objects of interest in CCTV footage in order to identify suspicious activities and assist authorities. It employs algorithms for face detection and recognition, as well as detection of weapons and abnormal movements. The system uses frameworks like OpenCV and TensorFlow to perform tasks like facial analysis, age and gender estimation, human pose estimation, and weapon detection in real-time video streams. It analyzes existing algorithms and evaluates their suitability for the system. The results of implementing and testing various algorithms on sample footage are also presented.
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This document describes a proposed surveillance system using a block matching algorithm for motion detection. The system would use IP cameras to stream video that is monitored for unauthorized activity. Motion detection is performed by comparing frames using the block matching algorithm to detect changes in pixel intensity values, which would trigger an alarm. The block matching algorithm divides frames into blocks of pixels and validates the maximum and minimum intensity of each pixel. Comparing blocks between frames identifies motion if intensity values change beyond a threshold. If motion is detected in a designated sensitive area, the system saves the video and sends alerts by email and mobile notification to users.
Human Motion Detection in Video Surveillance using Computer Vision TechniqueIRJET Journal
The document discusses a technique for detecting human motion in video surveillance using computer vision. It proposes a method called DECOLOR (Detecting Contiguous Outliers in the LOw-rank Representation) that formulates object detection as outlier detection in a low-rank representation of video frames. This allows it to detect moving objects flexibly without assumptions about foreground or background behavior. DECOLOR simultaneously performs object detection and background estimation using only the test video sequence, without requiring training data. The method models the outlier support explicitly and favors spatially contiguous outliers, making it suitable for detecting clustered foreground objects like people. It achieves more accurate detection and background estimation than state-of-the-art robust principal component analysis methods.
Computer Vision-Based Early Fire Detection Using Machine LearningIRJET Journal
This document presents a computer vision-based system for early fire detection using machine learning. It captures video using a webcam and processes the frames to detect fire. The frames are converted to different color models and compared using OpenCV. Morphological transformations and thresholding are applied to detect fire regions. If fire is detected, an alarm is triggered and a notification email is sent. The system aims to reduce limitations of conventional fire detection methods and optimize detection using image processing techniques. A literature review is also presented discussing previous works on fire detection using computer vision and machine learning.
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This document describes a proposed smart home intrusion detection system that uses image processing, face recognition, and notification technologies. The system would use an infrared camera and sensors to detect intruders, capture images of their faces, compare the images to a database to identify known intruders, and immediately notify home owners via mobile app with push notifications and images of the intruders. It discusses the system architecture, use of Raspberry Pi, image processing algorithms like LBPH, challenges with current systems, and outlines the development of an Android mobile app to facilitate user notifications.
Smart surveillance systems play an important role in security today. The goal of security systems is to protect users against fires, car accidents, and
other forms of violence. The primary function of these systems is to offer security in residential areas. In today’s culture, protecting our homes is
critical. Surveillance, which ranges from private houses to large corporations, is critical in making us feel safe. There are numerous machine learning algorithms for home security systems; however, the deep learning convolutional neural network (CNN) technique outperforms the others. The
Keras, Tensorflow, Cv2, Glob, Imutils, and PIL libraries are used to train and assess the detection method. A web application is used to provide a
user-friendly environment. The flask web framework is used to construct it. The flash-mail, requests, and telegram application programming interface (API) apps are used in the alerting approach. The surveillance system tracks
abnormal activities and uses machine learning to determine if the scenario is normal or not based on the acquired image. After capturing the image, it is
compared with the existing dataset, and the model is trained using normal events. When there is an anomalous event, the model produces an output from which the mean distance for each frame is calculated.
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This document presents an automatic fire detection and warning system using video surveillance. The system uses a Raspberry Pi connected to a USB camera to capture images and detect fires based on color analysis in real-time. It also includes smoke, LPG, and motion sensors. If a fire is detected, it will send a warning message via email with location details. The system was tested under different scenarios and proved efficient at identifying fires. It provides an improved method over conventional sensors by leveraging video analysis and integrating multiple sensors for robust detection.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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Sensor Fault Detection in IoT System Using Machine LearningIRJET Journal
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This document discusses the design and development of a firefighting robot based on an Arduino microcontroller. The robot is equipped with sensors to detect fires and obstacles. It can navigate manually through an environment and extinguish fires using a water pump and nozzle. The robot also has wireless communication via Bluetooth to allow for remote control. Computer vision algorithms using OpenCV are used for the primary fire detection system, while additional sensors provide secondary verification of fires. Testing showed the robot could accurately detect and localize fires. The conclusion discusses how such robots could assist firefighters by making firefighting safer and more effective.
Virtual Yoga System Using Kinect SensorIRJET Journal
The document describes a virtual yoga system using the Microsoft Kinect sensor. The system aims to make yoga exercises more engaging and motivating for patients by tracking their poses in real-time and providing feedback. It recognizes skeleton joints and yoga postures using the Kinect's depth sensing capabilities. Voice instructions guide users through different poses. The system is intended to address issues with traditional physiotherapy being tedious and repetitive. It allows customizing exercises to individual needs and challenges. Recognizing poses accurately in real-time could help patients perform exercises correctly and consistently at home without direct supervision.
The document describes a gesture recognition system that uses computer vision techniques. It discusses different approaches to hand gesture recognition including vision-based, glove-based, and depth-based techniques. The proposed system uses computer vision and media pipe libraries to track hand landmarks and recognize gestures in real-time. It then uses those gestures to control functions like a virtual mouse, change volume, and zoom in/out. The system aims to provide natural human-computer interaction through contactless hand gesture recognition.
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TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
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.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
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.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.