The document describes a proposed system to automatically detect traffic rule violations and stolen vehicles using deep learning techniques. Video from CCTV cameras placed around the city would be input to the system. It would use YOLOv5 and CNN models to detect vehicles, identify violations like speeding or wrong lane use, and detect stolen vehicles by recognizing license plates. If a violation or stolen vehicle is detected, the system would extract the license plate number and notify the nearby police station so further action can be taken. The goal is to help control traffic and reduce accidents through automatic monitoring that does not require much human resources or involvement.
The document proposes a traffic rules violation detection system using machine learning. It would use image processing technologies like object detection and optical character recognition to detect violations like speeding, lack of helmet, and license plate identification. A camera would take photos, detect objects like motorcycles, identify if helmets are worn, and recognize license plates. If violations are found, an SMS would be sent to the owner. The system aims to more efficiently manage traffic by automatically detecting violations. It analyzed literature on similar systems and proposed a methodology and working model with steps like preprocessing, segmentation, character recognition and saving results. An application was created with 93% accuracy for motorcycle detection, 85% for helmet identification and 51% for license plate recognition, providing overall
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This document presents a traffic sign detection, recognition, and notification system using Faster R-CNN. The system takes video input containing traffic signs and converts it to frames. Faster R-CNN with ROI pooling and a classifier is used to detect traffic signs. Color and shape information are then used to refine detections. A CNN classifier recognizes the signs. The system notifies drivers of detected signs via audio messages, helping drivers comply with signs even if ignored visually. The proposed detector detects all sign categories, and recognition accuracy on the German Traffic Sign Detection Benchmark dataset exceeds 90% for 42 sign classes.
Smart Parking Solution using Camera Networks and Real-time Computer VisionIRJET Journal
This document proposes a smart parking solution using computer vision and AI techniques applied to existing surveillance camera footage. The system would detect vacant parking spots, identify vehicle license plates, detect collisions, and track parking durations to calculate fees. It would provide real-time parking information and status updates to drivers via a mobile app. The system would use deep learning models like YOLOv5 trained on labeled camera images to perform tasks like license plate recognition and space availability detection without additional hardware. This could help optimize urban parking infrastructure and reduce traffic compared to alternative IoT-based approaches.
IRJET- Advenced Traffic Management System using Automatic Number Plate Recogn...IRJET Journal
This document describes an advanced traffic management system using automatic number plate recognition (ANPR). It discusses how current vehicle tracking systems have limitations in identifying fake number plates. The proposed system uses image processing and computer vision techniques to identify the number plate and type of vehicle from images or video. It extracts the number plate using edge detection and morphological operations. Optical character recognition and template matching are then used to recognize the characters. A convolutional neural network classifies the vehicle type. The system can check if a number plate is fake by comparing with an RTO database, and alert police if a match is found to a wanted vehicle number. It aims to help police track vehicles of interest and improve traffic management.
IRJET- Number Plate Extraction from Vehicle Front View Image using Image ...IRJET Journal
This document summarizes a research paper on extracting vehicle number plates from front-facing images using image processing techniques. The paper proposes a system that uses a camera to capture vehicle images, processes the images to isolate and extract the number plate, recognizes the characters on the plate, and displays the plate text. The system works by first converting the color image to grayscale. Edge detection, morphological operations and binary thresholding are then used to segment and extract the number plate region. Bounding box techniques isolate individual characters which are converted to text using OCR. The method achieved accurate number plate extraction on vehicle images taken in different lighting conditions and resolutions. The system has applications in traffic monitoring, law enforcement and vehicle identification.
Automatic And Fast Vehicle Number Plate Detection with Owner Identification U...IRJET Journal
This document discusses a proposed system for automatic vehicle number plate detection and owner identification using neural networks. The system aims to detect license plates from images, extract the plate region, segment characters, recognize the characters using OCR, and check owner details in a database by matching the recognized plate number. The system is designed to address issues with existing manual tracking systems and proprietary ALPR systems, using open-source technologies and real-time processing. Key stages of the proposed system include license plate detection using YOLOv3, plate segmentation, character recognition with OCR, and displaying owner details by matching the plate number to a database.
Implementation of Lane Line Detection using HoughTransformation and Gaussian ...IRJET Journal
This document summarizes a research paper that implements lane line detection in images and videos using the Hough transform and Gaussian smoothing. The methodology section outlines the steps taken, which include converting the image to grayscale, applying Gaussian smoothing for noise reduction, using Canny edge detection to extract edges, and applying the Hough transform to detect lane lines. Key algorithms discussed are Gaussian smoothing, Canny edge detection, Hough transformation, grayscale conversion, and defining a region of interest. The implementation section demonstrates applying these techniques to detect lane lines, including masking the image, edge detection, and identifying the lane lines.
Automatic Detection of Unexpected Accidents Monitoring Conditions in TunnelsIRJET Journal
The document describes a proposed system to automatically detect accidents and unexpected events in road tunnels using video footage from CCTV cameras. The system would use object detection and tracking technology, along with a Faster R-CNN deep learning model, to identify objects like vehicles, fires, and people in tunnel videos. It would monitor the movement and position of detected objects over time to identify accidents or other irregular events. If an accident is detected, a signal would be sent to alert authorities so they can respond quickly. The system aims to address the challenges of limited visibility and low-quality images from tunnel CCTV cameras.
The document proposes a traffic rules violation detection system using machine learning. It would use image processing technologies like object detection and optical character recognition to detect violations like speeding, lack of helmet, and license plate identification. A camera would take photos, detect objects like motorcycles, identify if helmets are worn, and recognize license plates. If violations are found, an SMS would be sent to the owner. The system aims to more efficiently manage traffic by automatically detecting violations. It analyzed literature on similar systems and proposed a methodology and working model with steps like preprocessing, segmentation, character recognition and saving results. An application was created with 93% accuracy for motorcycle detection, 85% for helmet identification and 51% for license plate recognition, providing overall
IRJET- Traffic Sign Detection, Recognition and Notification System using ...IRJET Journal
This document presents a traffic sign detection, recognition, and notification system using Faster R-CNN. The system takes video input containing traffic signs and converts it to frames. Faster R-CNN with ROI pooling and a classifier is used to detect traffic signs. Color and shape information are then used to refine detections. A CNN classifier recognizes the signs. The system notifies drivers of detected signs via audio messages, helping drivers comply with signs even if ignored visually. The proposed detector detects all sign categories, and recognition accuracy on the German Traffic Sign Detection Benchmark dataset exceeds 90% for 42 sign classes.
Smart Parking Solution using Camera Networks and Real-time Computer VisionIRJET Journal
This document proposes a smart parking solution using computer vision and AI techniques applied to existing surveillance camera footage. The system would detect vacant parking spots, identify vehicle license plates, detect collisions, and track parking durations to calculate fees. It would provide real-time parking information and status updates to drivers via a mobile app. The system would use deep learning models like YOLOv5 trained on labeled camera images to perform tasks like license plate recognition and space availability detection without additional hardware. This could help optimize urban parking infrastructure and reduce traffic compared to alternative IoT-based approaches.
IRJET- Advenced Traffic Management System using Automatic Number Plate Recogn...IRJET Journal
This document describes an advanced traffic management system using automatic number plate recognition (ANPR). It discusses how current vehicle tracking systems have limitations in identifying fake number plates. The proposed system uses image processing and computer vision techniques to identify the number plate and type of vehicle from images or video. It extracts the number plate using edge detection and morphological operations. Optical character recognition and template matching are then used to recognize the characters. A convolutional neural network classifies the vehicle type. The system can check if a number plate is fake by comparing with an RTO database, and alert police if a match is found to a wanted vehicle number. It aims to help police track vehicles of interest and improve traffic management.
IRJET- Number Plate Extraction from Vehicle Front View Image using Image ...IRJET Journal
This document summarizes a research paper on extracting vehicle number plates from front-facing images using image processing techniques. The paper proposes a system that uses a camera to capture vehicle images, processes the images to isolate and extract the number plate, recognizes the characters on the plate, and displays the plate text. The system works by first converting the color image to grayscale. Edge detection, morphological operations and binary thresholding are then used to segment and extract the number plate region. Bounding box techniques isolate individual characters which are converted to text using OCR. The method achieved accurate number plate extraction on vehicle images taken in different lighting conditions and resolutions. The system has applications in traffic monitoring, law enforcement and vehicle identification.
Automatic And Fast Vehicle Number Plate Detection with Owner Identification U...IRJET Journal
This document discusses a proposed system for automatic vehicle number plate detection and owner identification using neural networks. The system aims to detect license plates from images, extract the plate region, segment characters, recognize the characters using OCR, and check owner details in a database by matching the recognized plate number. The system is designed to address issues with existing manual tracking systems and proprietary ALPR systems, using open-source technologies and real-time processing. Key stages of the proposed system include license plate detection using YOLOv3, plate segmentation, character recognition with OCR, and displaying owner details by matching the plate number to a database.
Implementation of Lane Line Detection using HoughTransformation and Gaussian ...IRJET Journal
This document summarizes a research paper that implements lane line detection in images and videos using the Hough transform and Gaussian smoothing. The methodology section outlines the steps taken, which include converting the image to grayscale, applying Gaussian smoothing for noise reduction, using Canny edge detection to extract edges, and applying the Hough transform to detect lane lines. Key algorithms discussed are Gaussian smoothing, Canny edge detection, Hough transformation, grayscale conversion, and defining a region of interest. The implementation section demonstrates applying these techniques to detect lane lines, including masking the image, edge detection, and identifying the lane lines.
Automatic Detection of Unexpected Accidents Monitoring Conditions in TunnelsIRJET Journal
The document describes a proposed system to automatically detect accidents and unexpected events in road tunnels using video footage from CCTV cameras. The system would use object detection and tracking technology, along with a Faster R-CNN deep learning model, to identify objects like vehicles, fires, and people in tunnel videos. It would monitor the movement and position of detected objects over time to identify accidents or other irregular events. If an accident is detected, a signal would be sent to alert authorities so they can respond quickly. The system aims to address the challenges of limited visibility and low-quality images from tunnel CCTV cameras.
Vision-Based Motorcycle Crash Detection and Reporting Using Deep LearningIRJET Journal
This document discusses developing a vision-based system to detect motorcycle crashes in real-time using deep learning. The researchers created a custom dataset of 398 images containing motorcycle accidents and used YOLOv4 for object detection. YOLOv4 was trained on the dataset and achieved 74% mAP and 60% precision, outperforming Faster R-CNN and YOLOv4-Tiny in accuracy and speed tests. The trained YOLOv4 model was then used to detect accidents in video streams and send alerts when crashes were identified. The system provides a potential real-time solution to detect motorcycle accidents using only vision.
Congestion Control System Using Machine LearningIRJET Journal
This document proposes a machine learning-based system to address road congestion problems. It uses ML algorithms programmed in Python to develop automated traffic management solutions that can handle large volumes of traffic and ensure emergency vehicles like ambulances can move through congested roads quickly. The system detects vehicles like ambulances and motorcycles without helmets using object detection algorithms like YOLOv4. It recognizes license plates and sends violation notices to motorcycle riders detected without helmets. The system aims to provide priority to emergency vehicles at traffic lights using a Compact Prediction Tree algorithm based on deep learning. It analyzes previous research on dynamic traffic light control systems and proposes developing a continuous surveillance system and automated priority system for emergency vehicles.
IRJET - Unmanned Traffic Signal Monitoring SystemIRJET Journal
This document describes a proposed unmanned traffic signal monitoring system that uses image processing and computer vision techniques. A camera would be installed alongside traffic lights to capture images of the road. Image processing would be used to calculate traffic density in real-time based on the images in order to dynamically switch the traffic light signals according to vehicle congestion. The system aims to reduce traffic congestion by minimizing the time green lights are on for empty roads. It would also detect ambulances using ZigBee transmission and switch all traffic lights to green to clear a path for emergency vehicles.
This document describes a proposed smart traffic management system that uses RFID technology to automatically generate e-challans for vehicles that jump red lights. The system involves fitting vehicles with RFID tags and placing RFID readers at traffic signals linked to a NodeMCU. When a vehicle crosses the signal during a red light, the reader will detect the RFID tag and send the vehicle information to the NodeMCU to automatically generate an e-challan for the offender without human intervention. The proposed system aims to reduce traffic violations and accidents by automating the challan process compared to existing methods that rely on traffic police or CCTV cameras.
Vehicle Related Prevention Techniques: Pothole/Speedbreaker Detection and Ant...IRJET Journal
The document describes techniques for detecting potholes and speed breakers in real-time using a smartphone camera and algorithms like YOLOv4, YOLOv5, EfficientDet and ResNet. It discusses how the smartphone camera continuously captures video frames which are fed into a trained object detection model. When potholes or speed breakers are detected, the user is alerted with a sound notification. The document outlines the dataset creation process involving collection of over 20,000 images of potholes and speed breakers with annotations. It also discusses the training of models on this dataset using Google Collab and achieving highest accuracy of 96.9% using EfficientDet. The trained models are able to detect different types
IRJET- Smart Parking System using Facial Recognition, Optical Character Recog...IRJET Journal
The document proposes a smart parking system using facial recognition, optical character recognition (OCR), and the Internet of Things (IoT). The system uses facial recognition to identify drivers and OCR to extract text from vehicle license plates to verify if the driver and vehicle match database records. An IoT device is integrated with parking gates to automatically open them if verification is successful. The system aims to optimize parking space usage, enhance security, reduce congestion and emissions, and make the parking process more convenient. It analyzes previous research on smart parking and aims to implement an accurate and cost-effective solution.
IRJET - Smart Car Parking System using ArduinoIRJET Journal
This document describes a smart car parking system using Arduino that detects available parking spots using IR sensors and updates the information online. The system uses an RFID reader to identify vehicles and a microcontroller to operate the IR sensors and update a webpage displaying available spots to users. When a user scans their RFID tag, it displays their information on the webpage and opens the gate. IR sensors detect when a spot is occupied and update the webpage. The system aims to help users find available parking more efficiently to reduce congestion and pollution from vehicles driving around searching for spots.
A hierarchical RCNN for vehicle and vehicle license plate detection and recog...IJECEIAES
Vehicle and vehicle license detection obtained incredible achievements during recent years that are also popularly used in real traffic scenarios, such as intelligent traffic monitoring systems, auto parking systems, and vehicle services. Computer vision attracted much attention in vehicle and vehicle license detection, benefit from image processing and machine learning technologies. However, the existing methods still have some issues with vehicle and vehicle license plate recognition, especially in a complex environment. In this paper, we propose a multivehicle detection and license plate recognition system based on a hierarchical region convolutional neural network (RCNN). Firstly, a higher level of RCNN is employed to extract vehicles from the original images or video frames. Secondly, the regions of the detected vehicles are input to a lower level (smaller) RCNN to detect the license plate. Thirdly, the detected license plate is split into single numbers. Finally, the individual numbers are recognized by an even smaller RCNN. The experiments on the real traffic database validated the proposed method. Compared with the commonly used all-in-one deep learning structure, the proposed hierarchical method deals with the license plate recognition task in multiple levels for sub-tasks, which enables the modification of network size and structure according to the complexity of sub-tasks. Therefore, the computation load is reduced.
Drowsy Driving Detection System using IoTIRJET Journal
This document describes a proposed drowsy driving detection system using Internet of Things (IoT) technology. The system uses a Raspberry Pi camera and modules to monitor a driver's eyes for signs of drowsiness like blinking rate and eye aspect ratio. If drowsiness is detected, the system sends a warning message using IoT along with location data from a GPS module. It can also detect collisions and send alerts with location information to emergency responders. The proposed system aims to help prevent accidents caused by drowsy driving using computer vision and IoT connectivity.
SURVEY ON ARTIFICIAL INTELLIGENCE POWERED POTHOLE DETECTION, REPORTING AND MA...IRJET Journal
This document discusses a survey of artificial intelligence powered pothole detection, reporting, and management solutions. It begins with an abstract that outlines using a smartphone camera and GPS to detect potholes using the YOLO object detection technique. Users can submit photos of potholes which are verified using YOLO and mapped. The document then reviews existing pothole detection techniques and their limitations before concluding that the proposed system provides a low-cost, long-term solution for pothole detection and assessment of road conditions using a smartphone.
Deep Learning Based Vehicle Rules Violation Detection and Accident AssistanceIRJET Journal
This document presents a deep learning based system for detecting traffic violations and assisting with accidents. The system uses techniques like YOLO, CNNs, and Image AI to detect violations like signal jumping, triple riding, helmet detection, no parking from video feeds. It can also detect accidents and provide swift assistance. When a violation is detected, the system recognizes the vehicle license plate using OCR and sends an SMS alert to the owner. The system is meant to assist traffic police by automatically detecting violations and accidents from video monitoring systems in real-time. It aims to help regulate traffic and reduce inconvenience to the public.
This document describes a proposed 3M secure transportation system that provides security for people (drivers), vehicles, and cargo. The system uses several technologies including face recognition, fingerprint verification, vehicle tracking via GPS and GSM, and QR scanning of cargo. An Android application would be developed to integrate these security features and monitor them. The system is intended for mid-sized transportation businesses to help prevent theft of vehicles and cargo.
IRJET - Efficient Approach for Number Plaque Accreditation System using W...IRJET Journal
This document presents a proposed efficient approach for number plaque recognition system using Android devices. It discusses using optical character recognition and image processing techniques to extract vehicle number plates from images and recognize the characters. The system is designed to identify vehicles for applications like toll plazas, parking areas, and secure areas by automatically recognizing license plates from moving vehicles. It compares different methods like template matching and neural networks for the character recognition component. The proposed system aims to provide a user-friendly Android application to enable contactless verification of vehicle documents using Aadhaar card numbers, reducing the need to manually carry documents. It is intended to improve security, identify vehicles violating traffic rules, and reduce the complexity and time of existing systems.
IRJET - Vehicle Signal Breaking Alert SystemIRJET Journal
This document summarizes a research paper on a vehicle signal breaking alert system. The proposed system uses RFID tags situated on vehicles and sensors to automatically detect when a vehicle breaks a traffic signal. When a signal is broken, the system captures the vehicle's number plate using its RFID tag. It then compares the vehicle ID and number plate to records in a database to obtain owner details. If the ID and number plate match database records, a message is displayed saying "authorized person", otherwise "unauthorized person". For unauthorized vehicles that break signals, the system has the ability to send fine details directly to the registered owner's address on file with the RTO (Regional Transport Office). The goal is to help reduce traffic violations and accidents by
VEHICLE DETECTION USING YOLO V3 FOR COUNTING THE VEHICLES AND TRAFFIC ANALYSISIRJET Journal
This document discusses using YOLOv3 for vehicle detection and counting from video to analyze traffic. Video frames are used to identify moving vehicles and background extraction is applied to each frame to detect and count vehicles. YOLOv3 with a pre-trained model is used for object detection and classification of vehicles into classes like car, bus, motorcycle. Classification is shown for vehicles and individual types to analyze traffic levels. The analysis of vehicle levels is displayed using a pie chart.
IRJET- Reckoning the Vehicle using MATLABIRJET Journal
This document discusses a method for vehicle detection and counting using MATLAB. It begins with an introduction describing the need for automated vehicle counting systems. It then reviews existing vehicle detection methods and their limitations. The proposed method uses background subtraction to detect vehicles in video frames. Vehicles are tracked across frames, segmented from other objects, and counted. The algorithm involves taking the first frame as the background, subtracting subsequent frames to find differences (moving vehicles), processing and segmenting images, tuning vehicle boundaries, and incrementing a count when new vehicles are detected. Pseudocode and data flow diagrams illustrate the process. Test video input and output showing detected vehicles in bounding boxes is presented. The method provides an efficient way to automatically count vehicles for
IRJET- A Deep Learning based Approach for Automatic Detection of Bike Rid...IRJET Journal
1) The document presents a deep learning approach for automatically detecting motorcycle riders without helmets using video surveillance.
2) It involves preprocessing video frames, extracting features from images using CNNs, and classifying whether individuals are wearing helmets or not.
3) If a person is classified as not wearing a helmet, the system will capture their license plate number and send an SMS fine notification. The goal is to help enforce traffic safety rules and prevent accidents.
HELMET DETECTION USING ARTIFICIAL INTELLIGENCEIRJET Journal
This document summarizes a research paper that proposes using a YOLOv3 deep learning algorithm to detect whether motorcyclists are wearing helmets using video surveillance footage. The algorithm would first detect motorcycles, then determine the number of riders and whether each is wearing a helmet. This could help enforce helmet laws more efficiently. The paper reviews previous research on helmet detection methods and the YOLOv3 algorithm. It presents the proposed system architecture and algorithm workflow, and concludes the approach is generally very accurate based on testing with real-world video data containing various challenges.
Smart Algorithm for Traffic Congestion and ControlIRJET Journal
This document presents a smart algorithm for traffic congestion control using video processing and RFID sensors. A camera installed at an intersection records live traffic density and counts vehicles in video frames. When the traffic density reaches a threshold, the traffic light signals are adjusted accordingly. RFID sensors and a reader are also used to identify vehicles that break traffic rules and go through red lights. The system aims to more intelligently control traffic lights based on real-time traffic conditions compared to traditional fixed-time systems, in order to reduce congestion and wasted time. It analyzes the literature on existing traffic management systems and the advantages of the proposed smart algorithm approach.
SMART SOLUTION FOR RESOLVING HEAVY TRAFFIC USING IOTIRJET Journal
The document proposes a smart solution using IoT technology to reduce heavy traffic jams. The system uses camera sensors to detect traffic density and transmits this data to a Raspberry Pi. The Raspberry Pi processes the images to determine traffic density and displays this information on an LCD screen. The system is also connected to the cloud to store and analyze traffic data. The results show the system can accurately detect traffic density and provide real-time updates to help reduce congestion.
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 using YOLOv3 for vehicle detection and counting from video to analyze traffic. Video frames are used to identify moving vehicles and background extraction is applied to each frame to detect and count vehicles. YOLOv3 with a pre-trained model is used for object detection and classification of vehicles into classes like car, bus, motorcycle. Classification is shown for vehicles and individual types to analyze traffic levels. The analysis of vehicle levels is displayed using a pie chart.
IRJET- Reckoning the Vehicle using MATLABIRJET Journal
This document discusses a method for vehicle detection and counting using MATLAB. It begins with an introduction describing the need for automated vehicle counting systems. It then reviews existing vehicle detection methods and their limitations. The proposed method uses background subtraction to detect vehicles in video frames. Vehicles are tracked across frames, segmented from other objects, and counted. The algorithm involves taking the first frame as the background, subtracting subsequent frames to find differences (moving vehicles), processing and segmenting images, tuning vehicle boundaries, and incrementing a count when new vehicles are detected. Pseudocode and data flow diagrams illustrate the process. Test video input and output showing detected vehicles in bounding boxes is presented. The method provides an efficient way to automatically count vehicles for
IRJET- A Deep Learning based Approach for Automatic Detection of Bike Rid...IRJET Journal
1) The document presents a deep learning approach for automatically detecting motorcycle riders without helmets using video surveillance.
2) It involves preprocessing video frames, extracting features from images using CNNs, and classifying whether individuals are wearing helmets or not.
3) If a person is classified as not wearing a helmet, the system will capture their license plate number and send an SMS fine notification. The goal is to help enforce traffic safety rules and prevent accidents.
HELMET DETECTION USING ARTIFICIAL INTELLIGENCEIRJET Journal
This document summarizes a research paper that proposes using a YOLOv3 deep learning algorithm to detect whether motorcyclists are wearing helmets using video surveillance footage. The algorithm would first detect motorcycles, then determine the number of riders and whether each is wearing a helmet. This could help enforce helmet laws more efficiently. The paper reviews previous research on helmet detection methods and the YOLOv3 algorithm. It presents the proposed system architecture and algorithm workflow, and concludes the approach is generally very accurate based on testing with real-world video data containing various challenges.
Smart Algorithm for Traffic Congestion and ControlIRJET Journal
This document presents a smart algorithm for traffic congestion control using video processing and RFID sensors. A camera installed at an intersection records live traffic density and counts vehicles in video frames. When the traffic density reaches a threshold, the traffic light signals are adjusted accordingly. RFID sensors and a reader are also used to identify vehicles that break traffic rules and go through red lights. The system aims to more intelligently control traffic lights based on real-time traffic conditions compared to traditional fixed-time systems, in order to reduce congestion and wasted time. It analyzes the literature on existing traffic management systems and the advantages of the proposed smart algorithm approach.
SMART SOLUTION FOR RESOLVING HEAVY TRAFFIC USING IOTIRJET Journal
The document proposes a smart solution using IoT technology to reduce heavy traffic jams. The system uses camera sensors to detect traffic density and transmits this data to a Raspberry Pi. The Raspberry Pi processes the images to determine traffic density and displays this information on an LCD screen. The system is also connected to the cloud to store and analyze traffic data. The results show the system can accurately detect traffic density and provide real-time updates to help reduce congestion.
Similar to Automatic Traffic Rules Violation Control and Vehicle Theft Detection Using Deep Learning Approach (20)
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.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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.
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.
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.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.