The document describes a parking space counter project developed by a team of 4 students under the guidance of Mrs. Sujakumari N R. The project utilizes Python and OpenCV to create an automated system for counting available parking spaces in real-time by analyzing video feeds and detecting vehicles. The system is intended to improve parking management and enhance user experience by providing accurate information on parking availability. Key modules included video acquisition, vehicle detection and tracking, occupancy analysis and counting, and a user interface to display results.
Identifying Parking Spots from Surveillance Cameras using CNNIRJET Journal
This document describes a study that uses convolutional neural networks (CNNs) to detect empty parking spots from surveillance camera images. The researchers aim to investigate the potential of using CNNs for parking spot detection and evaluate their performance compared to other approaches. The document provides details on the CNN-based parking spot detection system's methodology, which involves collecting and labeling a dataset of parking spot images, preprocessing the data, defining the CNN architecture, and training the CNN. It also reviews related work on parking spot detection using traditional computer vision techniques, machine learning algorithms, and deep learning methods.
This document provides an overview of the humanoid robot ASIMO created by Honda. It discusses the history and purpose of humanoid robots. ASIMO was designed to be helpful, harmless, and honest. It can recognize faces, gestures, sounds and its environment. Though not as fast or efficient as humans, ASIMO demonstrates human-like abilities such as walking, grasping objects, responding to voices, and interacting with people.
This document proposes a smart vehicle security system using IoT that allows users to remotely monitor and control their vehicles via a mobile app. It cites statistics on vehicle theft in India to motivate the need for such a system. The system would use sensors and cameras on the vehicle to detect motion and stream live video to authenticated users. It provides an overview of the hardware, software, and mobile app design, including features like geofencing, remote locking/unlocking, and notification of abnormal activity. Future work is mentioned to incorporate machine learning and blockchain technology.
This document describes the design and implementation of an eye movement controlled wheelchair. It uses a webcam to capture eye movements which are then processed using MATLAB to detect the direction of movement. Based on the detected movement, MATLAB sends a signal over a serial port to a microcontroller which controls the motors to move the wheelchair in the intended direction. The system was tested for accuracy and safety features were incorporated like speed control and halt functions. While the performance was around 70-90% accuracy, further work is needed to improve reliability for commercial use.
This document describes a proposed smart parking system with the following key elements:
- The system uses ultrasonic sensors in each parking space to detect vehicles and coordinate payments and check in/out functions.
- Users can check in by entering their phone number, then pay automatically using RFID or by entering their card details. They can check out using their phone number.
- The spaces communicate information to a central coordinator, and a mobile app allows remote check in, payment and check out.
- Future improvements could include GPS location tracking, additional sensors for better detection, and integrating payments with bank accounts or existing systems.
Vehicle-to-vehicle communication can help reduce traffic accidents and increase road safety. The document discusses a vehicle-to-vehicle communication protocol for cooperative collision warning. It proposes that abnormal vehicles generate and transmit emergency warning messages to surrounding vehicles. The protocol aims to deliver these messages with low latency while supporting multiple abnormal vehicles. It uses a rate decreasing transmission algorithm and state transitions to prioritize warnings and eliminate redundant messages. The approach seeks to warn endangered vehicles in milliseconds while enabling communication from many abnormal vehicles.
Vehicle To Vehicle Communication SystemMonaco Motors
Vehicle to vehicle communication system enables vehicles to communicate with each other. Watch our slide to know the benefits of this system and what type of information we can share through it. Also keep track of some potential benefits of this system and the natural evolution in automotive safety development.
Identifying Parking Spots from Surveillance Cameras using CNNIRJET Journal
This document describes a study that uses convolutional neural networks (CNNs) to detect empty parking spots from surveillance camera images. The researchers aim to investigate the potential of using CNNs for parking spot detection and evaluate their performance compared to other approaches. The document provides details on the CNN-based parking spot detection system's methodology, which involves collecting and labeling a dataset of parking spot images, preprocessing the data, defining the CNN architecture, and training the CNN. It also reviews related work on parking spot detection using traditional computer vision techniques, machine learning algorithms, and deep learning methods.
This document provides an overview of the humanoid robot ASIMO created by Honda. It discusses the history and purpose of humanoid robots. ASIMO was designed to be helpful, harmless, and honest. It can recognize faces, gestures, sounds and its environment. Though not as fast or efficient as humans, ASIMO demonstrates human-like abilities such as walking, grasping objects, responding to voices, and interacting with people.
This document proposes a smart vehicle security system using IoT that allows users to remotely monitor and control their vehicles via a mobile app. It cites statistics on vehicle theft in India to motivate the need for such a system. The system would use sensors and cameras on the vehicle to detect motion and stream live video to authenticated users. It provides an overview of the hardware, software, and mobile app design, including features like geofencing, remote locking/unlocking, and notification of abnormal activity. Future work is mentioned to incorporate machine learning and blockchain technology.
This document describes the design and implementation of an eye movement controlled wheelchair. It uses a webcam to capture eye movements which are then processed using MATLAB to detect the direction of movement. Based on the detected movement, MATLAB sends a signal over a serial port to a microcontroller which controls the motors to move the wheelchair in the intended direction. The system was tested for accuracy and safety features were incorporated like speed control and halt functions. While the performance was around 70-90% accuracy, further work is needed to improve reliability for commercial use.
This document describes a proposed smart parking system with the following key elements:
- The system uses ultrasonic sensors in each parking space to detect vehicles and coordinate payments and check in/out functions.
- Users can check in by entering their phone number, then pay automatically using RFID or by entering their card details. They can check out using their phone number.
- The spaces communicate information to a central coordinator, and a mobile app allows remote check in, payment and check out.
- Future improvements could include GPS location tracking, additional sensors for better detection, and integrating payments with bank accounts or existing systems.
Vehicle-to-vehicle communication can help reduce traffic accidents and increase road safety. The document discusses a vehicle-to-vehicle communication protocol for cooperative collision warning. It proposes that abnormal vehicles generate and transmit emergency warning messages to surrounding vehicles. The protocol aims to deliver these messages with low latency while supporting multiple abnormal vehicles. It uses a rate decreasing transmission algorithm and state transitions to prioritize warnings and eliminate redundant messages. The approach seeks to warn endangered vehicles in milliseconds while enabling communication from many abnormal vehicles.
Vehicle To Vehicle Communication SystemMonaco Motors
Vehicle to vehicle communication system enables vehicles to communicate with each other. Watch our slide to know the benefits of this system and what type of information we can share through it. Also keep track of some potential benefits of this system and the natural evolution in automotive safety development.
India's greatest threat is the safety of its women. Women do not feel safe in a variety of situations. This needs to be addressed as quickly as feasible. Technology evolves and develops on a daily basis, affecting how people live. As a result, the focus of this article is on modernising the technological framework in order to strengthen women's safety mechanisms. We introduce a new security method in this study to protect women during unusual behaviours. A new security technique based on a patrolling robot using the Raspberry Pi has been proposed. In this case, a night vision camera can be employed to secure any location. Various machine learning methods are applied to improve the classifier's accuracy. The findings suggest that the suggested method outperforms existing methods.
An autonomous emergency braking system can help reduce accidents by intervening to brake independently of the driver when critical situations are detected. The system uses ultrasonic sensors and a camera to measure the speed of vehicles ahead and activate the brakes if a collision is likely to occur due to the driver braking too late or unexpectedly. While this can help avoid accidents and reduce injury, some disadvantages are the increased cost and loss of total vehicle control. The system works by sensors detecting obstacles, a microprocessor calculating braking needs, and activating the brakes if needed to avoid a collision.
advanced raiway security system based on zigbee communication for track fault SHIVA PRASAD
This document describes a proposed crack detection robot system for railway tracks. It would use sensors to detect cracks in the rails and send alert messages using Zigbee communication. The system aims to address safety issues caused by undetected rail cracks. It proposes using a microcontroller and sensors to detect cracks, and Zigbee to wirelessly transmit warnings to nearby stations. The document discusses related work on visual, vibration, and gauge inspection methods, and outlines the components and advantages of the proposed robotic crack detection system.
The document discusses autonomous vehicles and their potential benefits and challenges. It defines autonomous vehicles as vehicles that can travel from one point to another without human supervision. It notes that human error causes over 90% of automobile accidents and that autonomous vehicles could help reduce accidents by taking human error out of driving. The document outlines some of the key technologies used in autonomous vehicles, such as LIDAR, GPS, radar, ultrasonic sensors, video cameras, and a central computer. It discusses companies working on autonomous vehicle technologies like Google, Mercedes Benz, and Tesla. It also discusses some of the pros and cons of autonomous vehicles.
The document proposes an IOT based smart bus tracking system that uses sensors like cell tower signals and audio recordings instead of GPS to predict bus locations with high accuracy. A prototype was tested on campus shuttle buses and public buses in Singapore and London, achieving better prediction than GPS-based solutions. The system is generally available, energy efficient, and easy to deploy across cities.
This document describes a smart car parking system using IoT. The system uses sensors to detect available parking spots and sends the information to a display and mobile app. Cars enter and exit the parking area through automated gates controlled by IR sensors. Users can check the app to see available spots and navigate to empty ones indicated by green LED lights, while occupied spots have red lights. This optimized system reduces traffic and pollution compared to traditional parking methods.
Automatic number plate recognition (ANPR) uses optical character recognition on images to read vehicle registration plates. It has seven elements: cameras, illumination, frame grabbers, computers, software, hardware, and databases. ANPR detects vehicles, captures plate images, and processes the images to recognize plates. It has advantages like improving safety and reducing crime. Applications include parking, access control, tolling, border control, and traffic monitoring.
Inter-vehicle communication allows vehicles to communicate important safety and traffic information with each other. It has the potential to help avoid many vehicle collisions. However, securing vehicle communications presents challenges regarding privacy, real-time communication needs, and the large scale of vehicle networks. Effective inter-vehicle communication architectures require addressing issues such as secure routing, resilience to denial of service attacks, and balancing privacy and accountability. With further research and development, inter-vehicle communication could support applications like cooperative driving, hazard warnings, and traffic optimization to improve road safety and efficiency.
The document discusses an artificial passenger system developed by IBM to prevent driver sleepiness on long solo car rides. The system holds conversations with drivers to check their alertness level. It uses sensors, cameras and voice recognition to detect signs of fatigue. If a driver seems drowsy, the system engages them in games or changes the conversation topic to increase alertness. It can also activate alarms by opening windows or spraying water if needed to prevent an accident caused by an asleep driver. The system aims to make long solo drives safer through continuous monitoring of driver vigilance.
This document discusses automatic car parking systems. It provides an introduction and overview of basic components like stepper motors and sensors. It describes the hardware workings of using a microcontroller and sensors to control an automatic parking system. The document outlines different types of automatic parking systems and notes their advantages in requiring less space and reducing pollution compared to traditional parking. It also discusses some disadvantages like potential contamination in parking lots.
Drive-by-wire technology replaces traditional mechanical systems with electronic systems controlled by electronic control units (ECUs). ECUs consist of microcontrollers, sensors, power switches, drivers, and voltage regulators. They connect sensors and actuators to a central ECU. Modern cars contain up to 100 ECUs communicating over automotive bus protocols like CAN, LIN, and FlexRay. This allows for advanced driver assistance systems like anti-lock braking systems and electronic stability control.
Automatic vehicle accident detection and messaging system using gsm and gps m...mahesh_rman
This document summarizes an automatic vehicle accident detection and messaging system using GSM and GPS technology. The system uses a microcontroller, GSM modem, and GPS modem to detect if an accident occurs and send an SMS message with the vehicle's location to alert contacts. Some key advantages are providing security while traveling by detecting accident locations and notifying others. The system could also be expanded to track stolen vehicles or interface with other vehicle security systems.
Human Computer Interaction, Gesture provides a way for computers to understand human body language, Deals with the goal of interpreting hand gestures via mathematical algorithms, Enables humans to interface with the machine (HMI) and interact naturally without any mechanical devices
1. The document lists over 100 potential seminar topics in computer science and information technology, ranging from embedded systems and extreme programming to biometrics, quantum computing, and more.
2. Some examples include elastic quotas, electronic ink, gesture recognition, graphics processing units, grid computing, and honeypots.
3. The broad range of topics provide many options for students or professionals to explore emerging technologies and issues in computing.
The project is developed to avoid the human errors while taking a reverse extensively used for parking the vehicle. In this project we use ultrasonic sensors which can efficiently detect the obstacles and the solenoid valve perfectly controls the braking system by using Arduino programming.
This project has reduced the tension of the driver and also reduced the cost involved in the concern. The project has been designed to perform the required task by taking minimum time.
This document reviews a student project on an automatic rain sensing car wiper system. It includes sections on the objective, abstract, introduction, existing and proposed systems, block diagram, components, circuit diagram and working, advantages and disadvantages, applications, results and conclusion, and references. The objective is to develop an effective and environmentally friendly automatic wiper mechanism. The proposed system uses a rain sensor and microcontroller to automatically turn the wipers on when rain is detected and off when rain stops without manual intervention. The circuit diagram and working demonstrate how the system operates based on rain sensor input. The conclusions are that the prototype demonstrates the working of automatic wipers that display status messages on an LCD.
Working Concept of Fire Fighting Robot: The main brain of this project is the Arduino, but in-order to sense fire we use the Fire sensor module (flame sensor) that is shown below. As you can see these sensors have an IR Receiver (Photodiode) which is used to detect the fire.
it is a smart wheelchair which uses voice and bluetooth commands . Also consists of temperature and heartbeat sensors for continuous monitoring by the doctor.
soldier tracking and health monitoring systemJoshpin Bala.B
This document describes a project to track soldiers and monitor their health status during war using sensors, GPS, and GSM. The system includes sensors to monitor a soldier's pulse rate and temperature, along with a GPS module to track location. If the soldier's pulse drops below 60 or their coordinates exceed a certain range, the system will automatically make an emergency call through the GSM module to alert others. The goal is to allow army personnel to plan strategies based on real-time soldier location and health data. The system uses an ARM7 microcontroller to process data from the sensors and GPS and communicate through GSM when needed.
The document describes a smart car parking system using IoT. The system uses sensors like IR sensors and a wifi module connected to an Arduino board to detect available parking spots. This information is sent to a mobile app to guide drivers to empty spots, reducing congestion and emissions. The system's advantages include shorter wait times, fuel savings, and directing users to open spaces. It has applications in malls, restaurants, and theaters to more efficiently manage parking.
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 - Automatic License Plate Detection using Image ProcessingIRJET Journal
This document describes a system for automatic license plate detection using image processing. The system uses a camera to capture images of vehicles, extracts the license plate from each image using preprocessing techniques, recognizes the characters on the plate using optical character recognition (OCR), and matches the characters to a database to identify the vehicle. The key steps are detection of the vehicle, extraction of the license plate image, application of OCR techniques like template matching to recognize characters, and matching the results to a database to output the identification information. The system is designed to help identify vehicles automatically for applications like traffic monitoring and law enforcement.
India's greatest threat is the safety of its women. Women do not feel safe in a variety of situations. This needs to be addressed as quickly as feasible. Technology evolves and develops on a daily basis, affecting how people live. As a result, the focus of this article is on modernising the technological framework in order to strengthen women's safety mechanisms. We introduce a new security method in this study to protect women during unusual behaviours. A new security technique based on a patrolling robot using the Raspberry Pi has been proposed. In this case, a night vision camera can be employed to secure any location. Various machine learning methods are applied to improve the classifier's accuracy. The findings suggest that the suggested method outperforms existing methods.
An autonomous emergency braking system can help reduce accidents by intervening to brake independently of the driver when critical situations are detected. The system uses ultrasonic sensors and a camera to measure the speed of vehicles ahead and activate the brakes if a collision is likely to occur due to the driver braking too late or unexpectedly. While this can help avoid accidents and reduce injury, some disadvantages are the increased cost and loss of total vehicle control. The system works by sensors detecting obstacles, a microprocessor calculating braking needs, and activating the brakes if needed to avoid a collision.
advanced raiway security system based on zigbee communication for track fault SHIVA PRASAD
This document describes a proposed crack detection robot system for railway tracks. It would use sensors to detect cracks in the rails and send alert messages using Zigbee communication. The system aims to address safety issues caused by undetected rail cracks. It proposes using a microcontroller and sensors to detect cracks, and Zigbee to wirelessly transmit warnings to nearby stations. The document discusses related work on visual, vibration, and gauge inspection methods, and outlines the components and advantages of the proposed robotic crack detection system.
The document discusses autonomous vehicles and their potential benefits and challenges. It defines autonomous vehicles as vehicles that can travel from one point to another without human supervision. It notes that human error causes over 90% of automobile accidents and that autonomous vehicles could help reduce accidents by taking human error out of driving. The document outlines some of the key technologies used in autonomous vehicles, such as LIDAR, GPS, radar, ultrasonic sensors, video cameras, and a central computer. It discusses companies working on autonomous vehicle technologies like Google, Mercedes Benz, and Tesla. It also discusses some of the pros and cons of autonomous vehicles.
The document proposes an IOT based smart bus tracking system that uses sensors like cell tower signals and audio recordings instead of GPS to predict bus locations with high accuracy. A prototype was tested on campus shuttle buses and public buses in Singapore and London, achieving better prediction than GPS-based solutions. The system is generally available, energy efficient, and easy to deploy across cities.
This document describes a smart car parking system using IoT. The system uses sensors to detect available parking spots and sends the information to a display and mobile app. Cars enter and exit the parking area through automated gates controlled by IR sensors. Users can check the app to see available spots and navigate to empty ones indicated by green LED lights, while occupied spots have red lights. This optimized system reduces traffic and pollution compared to traditional parking methods.
Automatic number plate recognition (ANPR) uses optical character recognition on images to read vehicle registration plates. It has seven elements: cameras, illumination, frame grabbers, computers, software, hardware, and databases. ANPR detects vehicles, captures plate images, and processes the images to recognize plates. It has advantages like improving safety and reducing crime. Applications include parking, access control, tolling, border control, and traffic monitoring.
Inter-vehicle communication allows vehicles to communicate important safety and traffic information with each other. It has the potential to help avoid many vehicle collisions. However, securing vehicle communications presents challenges regarding privacy, real-time communication needs, and the large scale of vehicle networks. Effective inter-vehicle communication architectures require addressing issues such as secure routing, resilience to denial of service attacks, and balancing privacy and accountability. With further research and development, inter-vehicle communication could support applications like cooperative driving, hazard warnings, and traffic optimization to improve road safety and efficiency.
The document discusses an artificial passenger system developed by IBM to prevent driver sleepiness on long solo car rides. The system holds conversations with drivers to check their alertness level. It uses sensors, cameras and voice recognition to detect signs of fatigue. If a driver seems drowsy, the system engages them in games or changes the conversation topic to increase alertness. It can also activate alarms by opening windows or spraying water if needed to prevent an accident caused by an asleep driver. The system aims to make long solo drives safer through continuous monitoring of driver vigilance.
This document discusses automatic car parking systems. It provides an introduction and overview of basic components like stepper motors and sensors. It describes the hardware workings of using a microcontroller and sensors to control an automatic parking system. The document outlines different types of automatic parking systems and notes their advantages in requiring less space and reducing pollution compared to traditional parking. It also discusses some disadvantages like potential contamination in parking lots.
Drive-by-wire technology replaces traditional mechanical systems with electronic systems controlled by electronic control units (ECUs). ECUs consist of microcontrollers, sensors, power switches, drivers, and voltage regulators. They connect sensors and actuators to a central ECU. Modern cars contain up to 100 ECUs communicating over automotive bus protocols like CAN, LIN, and FlexRay. This allows for advanced driver assistance systems like anti-lock braking systems and electronic stability control.
Automatic vehicle accident detection and messaging system using gsm and gps m...mahesh_rman
This document summarizes an automatic vehicle accident detection and messaging system using GSM and GPS technology. The system uses a microcontroller, GSM modem, and GPS modem to detect if an accident occurs and send an SMS message with the vehicle's location to alert contacts. Some key advantages are providing security while traveling by detecting accident locations and notifying others. The system could also be expanded to track stolen vehicles or interface with other vehicle security systems.
Human Computer Interaction, Gesture provides a way for computers to understand human body language, Deals with the goal of interpreting hand gestures via mathematical algorithms, Enables humans to interface with the machine (HMI) and interact naturally without any mechanical devices
1. The document lists over 100 potential seminar topics in computer science and information technology, ranging from embedded systems and extreme programming to biometrics, quantum computing, and more.
2. Some examples include elastic quotas, electronic ink, gesture recognition, graphics processing units, grid computing, and honeypots.
3. The broad range of topics provide many options for students or professionals to explore emerging technologies and issues in computing.
The project is developed to avoid the human errors while taking a reverse extensively used for parking the vehicle. In this project we use ultrasonic sensors which can efficiently detect the obstacles and the solenoid valve perfectly controls the braking system by using Arduino programming.
This project has reduced the tension of the driver and also reduced the cost involved in the concern. The project has been designed to perform the required task by taking minimum time.
This document reviews a student project on an automatic rain sensing car wiper system. It includes sections on the objective, abstract, introduction, existing and proposed systems, block diagram, components, circuit diagram and working, advantages and disadvantages, applications, results and conclusion, and references. The objective is to develop an effective and environmentally friendly automatic wiper mechanism. The proposed system uses a rain sensor and microcontroller to automatically turn the wipers on when rain is detected and off when rain stops without manual intervention. The circuit diagram and working demonstrate how the system operates based on rain sensor input. The conclusions are that the prototype demonstrates the working of automatic wipers that display status messages on an LCD.
Working Concept of Fire Fighting Robot: The main brain of this project is the Arduino, but in-order to sense fire we use the Fire sensor module (flame sensor) that is shown below. As you can see these sensors have an IR Receiver (Photodiode) which is used to detect the fire.
it is a smart wheelchair which uses voice and bluetooth commands . Also consists of temperature and heartbeat sensors for continuous monitoring by the doctor.
soldier tracking and health monitoring systemJoshpin Bala.B
This document describes a project to track soldiers and monitor their health status during war using sensors, GPS, and GSM. The system includes sensors to monitor a soldier's pulse rate and temperature, along with a GPS module to track location. If the soldier's pulse drops below 60 or their coordinates exceed a certain range, the system will automatically make an emergency call through the GSM module to alert others. The goal is to allow army personnel to plan strategies based on real-time soldier location and health data. The system uses an ARM7 microcontroller to process data from the sensors and GPS and communicate through GSM when needed.
The document describes a smart car parking system using IoT. The system uses sensors like IR sensors and a wifi module connected to an Arduino board to detect available parking spots. This information is sent to a mobile app to guide drivers to empty spots, reducing congestion and emissions. The system's advantages include shorter wait times, fuel savings, and directing users to open spaces. It has applications in malls, restaurants, and theaters to more efficiently manage parking.
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 - Automatic License Plate Detection using Image ProcessingIRJET Journal
This document describes a system for automatic license plate detection using image processing. The system uses a camera to capture images of vehicles, extracts the license plate from each image using preprocessing techniques, recognizes the characters on the plate using optical character recognition (OCR), and matches the characters to a database to identify the vehicle. The key steps are detection of the vehicle, extraction of the license plate image, application of OCR techniques like template matching to recognize characters, and matching the results to a database to output the identification information. The system is designed to help identify vehicles automatically for applications like traffic monitoring and law enforcement.
IRJET- Intelligent Car Parking System commanded by Android ApplicationIRJET Journal
This document proposes an intelligent car parking system using a Raspberry Pi, QR codes, and an Android application. The system aims to automate the parking and unparking of cars to reduce human intervention and the time required for finding empty slots. Users can check parking availability in real-time using the mobile app and reserve slots. Infrared sensors connected to the Raspberry Pi detect occupied/empty slots, and the information is periodically updated to the server database and mobile app. The system is designed to provide more efficient parking operations and enhance the user experience.
Smart Car Parking system using GSM Technologydbpublications
In this paper, we present PGS, a Parking Guidance System based on wireless sensor network(WSN) which guides a driver to an available parking lot. The system consists of a WSN based VDS (vehicle detection sub-system) and a management subsystem. The WSN based VDS gathers information on the availability of each parking lot and the management sub-system processes the information and refines them and guides the driver to the available parking lot by controlling a VMS (Variable Messaging System). The paper describes the overall system architecture of PGS from the hardware platform to the application software in the view point of a WSN. We implemented the WSN based VDS of PGS and experimented on the system with several kinds of cars.
A Smart Image Processing-Based System For Parking Space Vacancy ManagementMary Calkins
This document describes a smart parking management system that uses image processing to detect vacant parking spots. The system works as follows:
1. Aerial cameras capture images of the parking lot and send them to a base station.
2. The base station processes the images using techniques like edge detection and morphological dilation to identify parking spots. It compares pixel counts in spots to detect occupied vs vacant spots.
3. The base station sends occupancy information to displays near the parking lot, helping drivers locate empty spots.
The system was tested on images of a parking lot. Image processing techniques accurately identified occupied spots based on increased pixel counts in bounding boxes around spots. This helps reduce time spent searching for parking.
IRJET- Smart Parking Assistance By Nameplate Recognition Using OCRIRJET Journal
This document proposes a smart parking system using number plate recognition and optical character recognition to identify vehicles and manage parking spaces. The system takes an image of a vehicle's number plate as it enters the parking lot, uses OCR to extract the characters, and verifies the number plate against an existing database. If verified, it assigns the vehicle to an available parking slot and stores the entry time. When the vehicle exits, it checks the database for the exit time and calculates the parking cost based on how long the vehicle was parked. This system aims to more efficiently manage parking spaces and resources compared to traditional human-managed lots.
Obstacle Detection and Collision Avoidance SystemIRJET Journal
This document summarizes an obstacle detection and collision avoidance system. It begins by introducing the topic of obstacle detection and how accidents can often be avoided. It then describes the design of an obstacle detector that can detect discontinuities in terrain and alert users of potential hazards. Key components discussed include using MATLAB, a camera, a PIC controller, and image processing techniques. The document reviews related literature on vision-based vehicle detection and classification methods. It also discusses adaptive cruise control systems using ultrasonic sensors and nonlinear coordinated control strategies for autonomous vehicles. Motion planning and trajectory planning frameworks are described for generating collision-free paths.
This document describes a smart parking system created by a group of students that uses cameras and artificial intelligence to manage a parking lot. The system recognizes vehicle numbers using embedded cameras, tracks which space a vehicle parks in, and updates parking information. It can also detect collisions. The system aims to introduce an intelligent parking management solution using technologies like sensors, IOT, and mobile applications to help drivers find available spaces and pay for parking remotely.
This document summarizes an article about developing an automatic smart parking system using Internet of Things technology. It describes a system that uses Raspberry Pi and cameras to detect available parking spaces and send that data to a server. Users can then check the server to see availability and get navigated to the nearest open spot, reducing time spent searching and traffic congestion. The system is designed to be low-cost compared to existing sensors-based parking solutions. It outlines the components, including centralized server, Raspberry Pi units with cameras, and user devices to access information.
Role of SunTec India's Data Annotation in Smart Parking Development.pdfSunTec India
SunTec India's data labeling helps build smart parking systems by training AI to recognize available spaces and objects in real-time, leading to smoother parking experiences.
Check it out here: https://www.suntecindia.com/data-annotation-support-for-smart-parking-app.html
The document discusses the development of a smart parking system using an Android and web application. The system aims to address issues with finding available parking spots by allowing drivers to check availability and pre-book spots. It consists of an Android app and web app that communicate with a backend PHP system hosted on a cloud server. The backend stores booking data and user authentication in a remote MySQL database. The system allows users to login, select an area to view available spots, book and pay for a spot in advance. This is intended to reduce traffic caused by drivers searching for parking.
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- Modern E-Parking System for Smart CitiesIRJET Journal
1. The document proposes a modern e-parking system for smart cities that uses IoT and an Android application to address issues with finding parking and traffic congestion.
2. It would allow drivers to reserve parking spaces and receive navigation guidance to the space. QR codes would also be used to securely manage entry and exit from parking areas.
3. The system is meant to reduce time spent searching for parking, lower fuel consumption and pollution from traffic jams, while providing a user-friendly reservation process.
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.
Design and Implementation of Vehicle Detection System for various Security Pu...nikhiljs1
As an essential task, vehicle detection aims to provide information assisting vehicle counting, vehicle speed measurement, identification of traffic accidents, traffic flow prediction, etc. There are various sensors used to collect continuously- generated traffic information.
SVM and Decision Tree algorithms were developed to detect and track vehicles in images and videos. Python was used to create and train these models. The goal was to automatically detect and track both static and moving vehicles. The paper compares the two algorithms on the same dataset and preprocessing to determine the best performing model for vehicle counting. Limitations include accuracy issues with varying lighting and camera angles, as well as the high costs and complexity of implementing such systems.
VEHICLES AND TOURIST FREQUENCY TRACKING USING OPENCVIRJET Journal
This document summarizes a research study that developed a system for detecting and tracking vehicles and tourists in real-time video using computer vision techniques with OpenCV. The system uses OpenCV algorithms like Haar cascades and deep learning models to detect vehicles and tourists, and then tracks them across video frames using algorithms like Kalman filtering and Mean-Shift. The system was evaluated and achieved high accuracy in detection and tracking. While the system showed potential for applications in traffic management and tourism analysis, limitations were identified that could be addressed in future work through techniques like advanced machine learning, multi-modal sensor fusion, and real-time decision making.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
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2. OUR TEAM
1. ABHAY A V
2. ADITHYAN P B
3. KRISHNARAJ R
4. AKSHAY S NAIR
UNDER THE GUIDANCE OF
MRS SUJAKUMARI N R
3. INTRODUCTION
The parking space counter project employs Python and OpenCV to create
an automated system for accurately counting available parking spots.
By analyzing video or images, the system utilizes image processing and
object detection techniques to identify vehicles and segment parking
spaces.
This real-time information on parking availability assists drivers in
efficiently locating open spots, reducing frustration and saving time in
crowded urban areas or busy parking lots.
4. PURPOSE
The purpose of the project is to develop a parking space counter using Python and OpenCV.
It aims to accurately detect and count the number of available parking spaces in real-time.
This system can help efficiently manage parking lots and provide users with up-to-date
information on parking availability.
5. SCOPE
Efficient parking management through real-time counting of available spaces.
Enhanced user experience by providing up-to-date parking availability information
Optimize resource allocation and improve revenue by analyzing parking occupancy data for
better planning and utilization of parking infrastructure.
6. ABSTRACT
This project aims to create a system that counts available parking spaces using Python and
OpenCV.
By analyzing video feeds, the system accurately tracks and detects vehicles in real-time,
providing up-to-date information on parking availability.
The project intends to improve parking management, enhance user experience, and optimize
resource allocation for efficient use of parking spaces..
7. Problem Statement
Inefficient utilization: Parking lots lack accurate information on availability, resulting in
wasted resources and frustrated drivers.
Manual counting errors: Human operators often make mistakes in counting parking
spaces, leading to inaccurate information and ineffective management.
Limitations of sensor-based systems: Expensive and maintenance-intensive sensor
installations can be unreliable and require extensive infrastructure modifications.
8. PROPOSED SYSTEM HIGHLIGHTS
Real-time and accurate parking space detection, leveraging advanced computer vision
algorithms and real-time video analysis to provide timely and precise identification of available
and occupied parking spaces.
High-precision occupancy counting, harnessing the power of Python and OpenCV to ensure
accurate counting of parking spaces, enabling users to efficiently locate vacant spots and
optimize their parking decisions.
User-friendly interface designed to deliver a seamless parking experience, presenting the
parking space occupancy information in an intuitive and visually appealing manner, simplifying
the process of finding available parking spaces for both drivers and parking lot operators.
9. EXISTING SYSTEMS
Ultrasonic Sensor-based Systems: Utilizing ultrasonic sensors installed in parking spaces, these
systems detect vehicle presence by measuring the distance to the nearest object. The sensors
determine if a parking space is occupied or vacant based on the detected distances.
Magnetic Loop Sensor Systems: Embedded in the ground of parking spaces, magnetic loop
sensors detect changes in the electromagnetic field caused by vehicles. By sensing these
disruptions, they accurately determine the occupancy status of parking spaces.
Infrared Sensor-based Systems: Infrared sensors are placed at entrance and exit points of
parking spaces. They emit infrared beams and detect interruptions in the beams caused by
vehicles. This allows the system to determine whether a parking space is available or occupied
based on the detected interruptions.
10. PROCESS SPECIFICATION
Video feed acquisition
Vehicle detection
Vehicle tracking
Occupancy analysis
Space counting
Real-time processing
Accuracy
User interface
Integration
Performance optimization
12. TITLE METHOD
Conventional
Automation Techniques
[1]
The conventional automation techniques used in the
project topic of "parking space counter using Python
and OpenCV" involve several key steps.
The process begins with image acquisition, where
images or video frames of the parking slot are
captured using cameras or imaging devices.
These acquired images undergo preprocessing
techniques such as resizing, noise reduction etc.
Object detection or segmentation algorithms are then
applied to identify parking spaces or vehicles.
Finally, a counting algorithm analyzes the tracked
objects' trajectories to determine the occupancy
status of each parking space.
13. TITLE METHOD
Detect and Segment
Parking Spaces[2]
Utilize edge detection techniques such as Canny
edge detection to extract the boundaries of parking
spaces from the input image or video feed.
Apply contour analysis algorithms to detect and
isolate individual parking spaces based on the
extracted edges, considering factors like size, shape,
and connectivity.
Implement region-based segmentation approaches
like GrabCut or watershed segmentation to refine the
detected parking spaces and generate accurate
segmentation masks for occupancy analysis and
counting.
14. TITLE METHOD
Count and Display Result
[3]
Counting: Utilize the detection and segmentation
techniques to identify occupied and vacant parking
spaces. Keep a count of the vacant spaces as vehicles
enter and exit the parking area.
Result Display: Develop a user-friendly interface
that presents the parking space count in real-time.
Real-time Updates: Implement a mechanism to
continuously update the displayed result as vehicles
occupy or vacate parking spaces. This ensures that
the parking space count is always up to date and
provides accurate information
15. TITLE METHOD
Performance Evaluation
[4]
Accuracy Assessment: The system's accuracy in
detecting and counting parking spaces will be
evaluated by comparing the results with ground
truth data obtained through manual inspection
or existing parking management systems.
Real-Time Processing: The system's
performance in processing video feeds and
providing real-time occupancy updates will be
measured in terms of latency, ensuring that the
information is delivered promptly to users.
Robustness and Scalability: The system will be
tested for robustness against various lighting
conditions, vehicle types, and parking lot
configurations.
16. TITLE METHOD
Computer Vision-Based
Techniques [5]
Object Detection: Computer vision algorithms are
employed to detect vehicles within the parking lot by
analyzing video feeds. This involves techniques like
Haar cascades, HOG (Histogram of Oriented
Gradients), or deep learning-based
Image Segmentation: Image segmentation
algorithms, such as contour detection or semantic
segmentation, are utilized to segment the parking
spaces from the video frames, distinguishing
between occupied and vacant areas.
Tracking and Counting: Vehicle tracking algorithms
are implemented to track the movement of vehicles
within the parking lot over time.
17. MODULE DESCRIPTION
Video Feed Acquisition Module: This module is responsible for capturing real-time video
feeds from cameras placed in the parking area. It establishes the connection with the
cameras, receives the video stream, and provides the frames for further processing.
Vehicle Detection and Tracking Module: This module employs computer vision algorithms
and techniques to detect and track vehicles within the video frames. It utilizes object
detection models and algorithms to identify vehicles accurately and track their movement
across frames.
18. Occupancy Analysis and Counting Module: This module analyzes the detected vehicles and
performs occupancy counting. It processes the tracked vehicles, determines their occupancy status
status (occupied or vacant), and updates the count of available parking spaces in real-time.
User Interface Module: This module is responsible for presenting the occupancy information to
the users through a user-friendly interface. It displays the parking space count, highlights the
available and occupied spaces, and provides visual feedback to aid users in finding vacant parking
spots.
Integration Module: The integration module combines the functionalities of the above modules,
ensuring seamless coordination and communication between them. It establishes the flow of data
and information, enabling the overall system to work cohesively in detecting, tracking, and
counting parking spaces.
27. HARDWARE REQUIREMENTS
Camera: Any camera compatible with your computer.
Computer:
Processor: Intel Core i5 or higher.
Memory: Minimum 8GB RAM.
Storage: Sufficient free disk space to store images and the application.
Display: Minimum resolution of 1280x720 pixels.
Graphics Card: Recommended for improved performance (e.g., NVIDIA GeForce or AMD
Radeon).
Operating System: Windows 10, macOS, or Linux.
Power: Reliable power supply to ensure uninterrupted operation.
Internet: Optional for accessing online resources or remote monitoring.
28. SOFTWARE REQUIREMENTS
Python
OpenCV
IDE (e.g., PyCharm, VS Code)
Operating System (Windows, macOS, Linux)
Python Packages (numpy, matplotlib, etc.)
Version Control System (Git)
Image Processing Libraries (Pillow, scikit-image)
Web Framework (Flask, Django)
Database (MySQL, PostgreSQL, SQLite)
Documentation Tools (Jupyter Notebook, Markdown)
Collaboration Tools (GitHub, GitLab)
29. FUNCTIONAL REQUIREMENTS
Capture live video feed from a camera.
Process the video frames using OpenCV for object detection.
Detect and track parking spaces within the video frames.
Count the number of available and occupied parking spaces.
Display the parking space count in real-time.
Generate alerts or notifications when parking spaces are occupied or become available.
Provide an option to adjust sensitivity or parameters for object detection.
38. WHAT WE LEARNT
Proficiency in Python programming and OpenCV library for image processing and analysis.
Understanding of computer vision techniques for object detection and tracking.
Ability to design and implement an automated system for counting and monitoring parking
space occupancy, enhancing skills in image processing, and real-time analysis.
39. FUTURE SCOPE
Integration with IoT: The project can be expanded to incorporate IoT technologies to enable
real-time monitoring and management of parking spaces, including features like occupancy
alerts and reservation systems.
Advanced Analytics: By leveraging machine learning algorithms and advanced analytics
techniques, the project can provide insights into parking patterns, trends, and optimization
strategies for efficient space utilization.
Mobile Application Development: Creating a mobile application that interfaces with the parking
space counter system would allow users to check real-time parking availability, receive
notifications, and navigate to available spaces..
40. CONCLUSION
In conclusion, the project topic "Parking Space Counter using Python and OpenCV"
demonstrates the power of computer vision and automation in efficiently managing parking
spaces. By combining Python programming and OpenCV, the project achieves real-time
occupancy counting and monitoring. With further advancements in IoT integration and data
analytics, it has the potential to revolutionize parking systems and enhance urban mobility
41. REFERENCES
1. Reference:
Authors: A. Amin, H. M. Mohd, A. M. Daud, M. A. Mahfuz, and S. S. R. Abu-Bakar
Title: Automatic Parking Space Detection System Using OpenCV
Published in: 2017 6th International Conference on Electrical Engineering and Informatics
(ICEEI)
Link: [IEEE Xplore](https://ieeexplore.ieee.org/abstract/document/8293170)
2. Reference:
Authors: P. Subbaraj and D. K. Kumar
Title: Vehicle Parking Slot Detection Using Image Processing
Published in: 2016 International Conference on Computer Communication and Informatics
(ICCCI)
Link: [IEEE Xplore](https://ieeexplore.ieee.org/abstract/document/7439502)