This project report summarizes the design and working of a line follower robot. It discusses the components used including an LM324 comparator IC, AT89C51 microprocessor, L293D H-bridge motor driver, and IR transmitter and receiver. It explains how the IR sensors detect the line and the microprocessor controls the motors to follow the line by turning when sensors detect line edges. The working principle section describes the robot's line detection and movement logic in detail. Applications mentioned include industrial transport, automated vehicles, and museum tour guides.
The document describes the components, working, and applications of a line following robot. It consists of the following key components: IR sensors to detect the line, an Arduino UNO microcontroller, an L293D motor driver IC, and two geared motors. The IR sensors detect the visual line on the floor and send signals to the Arduino, which uses the motor driver IC to control the direction of the two motors accordingly. The line following robot is able to follow the line path, make turns when detecting breaks in the line, and has applications in industrial automation.
This document describes the components, working, circuit, source code, and scope of an obstacle avoidance robot powered by an Arduino. The main components are a chassis, Arduino UNO microcontroller, DC motor, motor driver, ultrasonic sensor, and servo motor. The robot uses the ultrasonic sensor to calculate distances and detects obstacles. It then controls the DC motor and servo motor using the motor driver and Arduino to avoid obstacles and navigate autonomously. The source code contains functions for movement, distance calculation, and sensor control. Potential applications discussed for further development include using it as a firefighting, mining, driverless vehicle, or cleaning robot.
The line follower robot detects and follows a black line on a white surface using infrared sensors. It continuously corrects itself to stay on the track without human help. The sensors detect light reflected from the surface to determine if the line is centered, left, or right of the robot and signal the motors to move forward or turn accordingly. Potential applications include transport in factories, hospitals, museums, and more.
This document provides an introduction to programming the ESP8266 WiFi chip. It outlines ESP8266 basics, including an overview of the ESP-01 and ESP-12 models. It then demonstrates how to connect an ESP8266 to an Arduino and use the Blynk app and library to control an LED over WiFi. Wiring diagrams and code examples are provided to showcase setting up and programming the ESP8266 for basic WiFi functionality and Blynk integration.
This is a presentation of OBSTACLE AVOIDANCE ROBOT. which has the details on making an obstacle avoider using arduino uno, ultrasonic sensor. This presentation has the detailed description of all the components that are being used in making. And also circuit diagram and flow chart of the robot.
The document outlines requirements for a line following robot and discusses methods for line detection. It lists key requirements as being able to follow and take turns along a line, while being insensitive to lighting and noise. It also notes the line color does not matter as long as it is darker or lighter than the surroundings. The document further explains that infrared sensors produce analog outputs that need to be converted to digital signals, which can be done using analog to digital converters or comparators. It also provides an overview of features of the 8051 microcontroller, including memory, serial communication ports, timers, I/O pins, interrupts and clock speed.
The document discusses the components, working principle, and programming of a line following robot. It contains the following key points:
1. A line following robot uses IR sensors to sense a black line on a white surface and maneuvers itself to stay on the line by constantly correcting its position.
2. The main components are an Arduino microcontroller, IR sensors to detect the line, and motors controlled by an L298N motor driver.
3. The IR sensors detect the line and send signals to the Arduino, which determines if the robot needs to turn left, right, or go straight to stay centered on the line.
RS-232 is a popular communications interface for connecting modems and data acquisition devices (i.e. GPS receivers, electronic balances, data loggers, ...) to computers.
Obstacle Avoiding Robot
Robotics is a branch of science that deals with Mechanical, Electrical and Software fields. Robots are the machines that are used in our day-to-day to life to reduce men power and work accurately without any distortions. Robots can be classified into two different sections basing upon their skills as Automated and Manual. Obstacle detector is a Automated robot which itself recognizes the obstacle in its path and moves in free direction. Robot detects the obstacle by using two IR Sensors placed in front.
The IR sensors are placed on left and right side of the robot through which continuous Infrared radiation is emitted for detection of obstacles in the path. These IR Sensors are connected to a controlling element AT89c51 µc. When a obstacle is placed in the path of robot IR beam is reflected to the sensor from the obstacle. On detecting obstacle in the path sensor sends 0 volts to µc. This 0 voltage is detected by Microcontroller which avoids the obstacle by taking left or right turn. Similarly if the sensor sends +5v to Microcontroller, the Microcontroller assumes it as clear path and makes the robot to move in straight.
Two motors namely right motor and left motor are connected to Motor driver IC (L293D). L293D is interface with Microcontroller. Microcontroller sends logic 0 & logic 1 as per the programming to driver IC which makes motors to rotate in clockwise and anticlockwise direction. Wheels attached to the motors rotate accordingly with the motor shaft causing in the moment of the robot by wheels. In front portion of the robot a free wheel is attached to move the robot easily in any direction as per the requirement.
A 12Volts DC battery is attached to the circuit. As the microcontroller and sensors requires only 5v, set of resistors and capacitors are used to supply 5v DC to them. Power Management System is not maintained in the circuit as the battery can be removed after the usage of robot. So it does not cause any loss in the power of battery.
This type of robots has multiple applications in various fields. They can be used to know the strength of the opposite army in defense system. They can be used as floor and wall cleaners. They are used in automated GPS vehicles to calculate the moment of the vehicle overhead. These robots are easy to construct and cheaper in cost with long durability.
This project report describes an obstacle avoiding robot created by a student group. The robot uses an ultrasonic sensor to detect obstacles in its path and a microcontroller to control two motors to navigate around obstacles. When the sensor detects an obstacle within 20cm, the microcontroller directs the robot to turn left. Otherwise, it moves straight. The report provides details on the robot's design, components, circuit diagram, algorithm, and testing process. It also discusses potential applications and future improvements.
This document describes an automatic street light control circuit using an LDR (light dependent resistor). The circuit uses an LDR, resistors, capacitors, diodes, a transistor and relay to automatically turn on LED street lights when it gets dark. When the LDR detects a drop in light levels, it causes the transistor to switch on, powering the relay and turning on the lights. The circuit requires few components, consumes little power and provides an efficient automatic method for controlling street lights without manual operation.
Powerpoint Presentation On Obstacle Avoidance Robot
Download the ppt file from the following link::
https://adf.ly/rdC2Z
Embedded system for traffic light controlMadhu Prasad
This document describes an embedded systems project for traffic light control. It presents the background and motivation for optimizing traffic light control using wireless sensors. The proposed system uses an ARM7 microcontroller programmed in embedded C to process real-time data from wireless sensors and control LED traffic lights accordingly. The goal is to study different traffic density situations and optimize traffic flow.
Obstacle Avoidance Robot Summer training Presentation Wasi Abbas
i did an extremely hard work on it. I believe that you all my friends will surely get the benefit of this presentation. As a student of B.tech I just wish to assist those who always ready to assist another one. thanks for reading......
The document discusses the Arduino, an open-source electronics prototyping platform. It provides a brief history of how Arduino was created in 2005 to provide an affordable platform for interactive design projects. It describes the key features of the Arduino Uno board and the Arduino programming environment. Finally, it outlines some common applications of Arduino in fields like home automation, robotics, and sensor prototyping.
This document describes the design and development of an obstacle avoiding robot. The robot uses infrared sensors and a microcontroller to detect and avoid obstacles in its path. When an obstacle is detected, the microcontroller stops one motor and moves the other, causing the robot to turn away from the obstacle. The robot was designed using software like DipTrace and programmed using Keil uVision. It was tested to ensure proper functioning and avoids obstacles as intended. Potential applications and future improvements are also discussed.
This document describes an obstacle avoiding car project created by Utkarsh Bingewar, Shubham Thakur, and Rupesh Rote, with guidance from their assistant professor Mrs. Varsha Nanaware. The car uses an ultrasonic sensor and Arduino board to detect obstacles and navigate around them. When an obstacle is detected, the Arduino controls the motors to turn the car left or right to avoid the obstacle. The obstacle avoiding car has applications in areas like surveillance, hazardous environments, and unmanned vehicle navigation.
Obstacle detection Robot using Ultrasonic Sensor and Arduino UNOSanjay Kumar
This document describes how to build an obstacle detection robot using an Arduino UNO, ultrasonic sensor, and motor driver module. It explains the components used, including the Arduino, ultrasonic sensor to detect obstacles from 2-400cm away, and an L298N motor driver module to control DC motors. It provides details on connecting the components, programming the ultrasonic sensor to trigger and receive echo signals to determine distances, and controlling the motor's direction depending on detected obstacles to help the robot navigate. Code and more details are available at the provided GitHub link.
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.
The document describes an obstacle avoiding robot created by four group members using an Arduino UNO, ultrasonic sensor, DC motor driver, and connecting wires. The robot senses obstacles in its path using the ultrasonic sensor, avoids obstacles by reversing or turning, and resumes moving forward once the path is clear. The robot's program uses the ultrasonic sensor readings to determine its speed and maneuvering.
Difference Between Impatt Diode and Trapatt Diode and Baritt DiodeAL- AMIN
This 3 sentence document discusses different types of diodes. It mentions Impatt diode, Trapatt diode, and Baritt diode but does not provide any details about the differences between them. The document references a photo but does not include the photo or provide any other context.
This document is an obstacle avoiding car project report submitted by three students - Utkarsh Bingewar, Shubham Thakur, and Rupesh Rote - to partially fulfill their project requirements for a bachelor's degree in electronics and telecommunications engineering. The report describes the design and implementation of a robotic vehicle that uses an ultrasonic sensor and microcontroller to detect and avoid obstacles in its path by controlling two DC motors through a motor driver. Experimental results show the car is able to successfully detect and navigate around obstacles.
Vechicle accident prevention using eye bilnk sensor pptsatish 486
This document describes a vehicle accident prevention system using an eye blink sensor. The system uses an IR sensor to detect a driver's eye blinks and a microcontroller to process the sensor data. If no eye blinks are detected for a period of time, indicating potential drowsiness, the system will stop the vehicle and trigger an alarm to prevent accidents. The system could also be expanded in the future to detect alcohol and stop the vehicle if the driver is intoxicated.
The document describes a line follower robot that uses infrared sensors to detect and follow a black line on a white surface. It uses an L293d motor driver IC to control two DC motors and drive the wheels. An LM324 comparator IC compares the output of the IR sensors to a reference voltage to determine if the sensor is over the black line or white surface. The robot also uses an L7805 voltage regulator to maintain a constant voltage supply for the components. The robot is able to navigate tight curves by sensing the line with the IR sensors and maneuvering accordingly using the closed-loop control system.
This document discusses the components, working principle, and programming of a line following robot. It contains the following key points:
1) The main components of the line following robot are an Arduino, IR sensors, an L293D motor driver, motors, and a chassis. The IR sensors detect a dark line on a light surface and signal the motors to move via the Arduino.
2) The working principle involves the IR sensors detecting the line and signaling the appropriate motors to run or stop via the Arduino, causing the robot to follow the line. Turning is achieved by stopping one motor and running the other.
3) Programming on the Arduino involves setting the motors and sensors as inputs/
This document describes a line following robot project built using an Arduino microcontroller. It lists the components used, which include the Arduino UNO, IR sensors, an L298N motor driver, DC motors, and a chassis. It explains the working principle of how the IR sensors detect a line and the motor driver is used to control the DC motors to follow the line. Diagrams of the circuit, programming code, potential applications, and advantages/disadvantages of the line following robot are also provided.
The document outlines requirements for a line following robot and discusses methods for line detection. It lists key requirements as being able to follow and take turns along a line, while being insensitive to lighting and noise. It also notes the line color does not matter as long as it is darker or lighter than the surroundings. The document further explains that infrared sensors produce analog outputs that need to be converted to digital signals, which can be done using analog to digital converters or comparators. It also provides an overview of features of the 8051 microcontroller, including memory, serial communication ports, timers, I/O pins, interrupts and clock speed.
The document discusses the components, working principle, and programming of a line following robot. It contains the following key points:
1. A line following robot uses IR sensors to sense a black line on a white surface and maneuvers itself to stay on the line by constantly correcting its position.
2. The main components are an Arduino microcontroller, IR sensors to detect the line, and motors controlled by an L298N motor driver.
3. The IR sensors detect the line and send signals to the Arduino, which determines if the robot needs to turn left, right, or go straight to stay centered on the line.
RS-232 is a popular communications interface for connecting modems and data acquisition devices (i.e. GPS receivers, electronic balances, data loggers, ...) to computers.
Obstacle Avoiding Robot
Robotics is a branch of science that deals with Mechanical, Electrical and Software fields. Robots are the machines that are used in our day-to-day to life to reduce men power and work accurately without any distortions. Robots can be classified into two different sections basing upon their skills as Automated and Manual. Obstacle detector is a Automated robot which itself recognizes the obstacle in its path and moves in free direction. Robot detects the obstacle by using two IR Sensors placed in front.
The IR sensors are placed on left and right side of the robot through which continuous Infrared radiation is emitted for detection of obstacles in the path. These IR Sensors are connected to a controlling element AT89c51 µc. When a obstacle is placed in the path of robot IR beam is reflected to the sensor from the obstacle. On detecting obstacle in the path sensor sends 0 volts to µc. This 0 voltage is detected by Microcontroller which avoids the obstacle by taking left or right turn. Similarly if the sensor sends +5v to Microcontroller, the Microcontroller assumes it as clear path and makes the robot to move in straight.
Two motors namely right motor and left motor are connected to Motor driver IC (L293D). L293D is interface with Microcontroller. Microcontroller sends logic 0 & logic 1 as per the programming to driver IC which makes motors to rotate in clockwise and anticlockwise direction. Wheels attached to the motors rotate accordingly with the motor shaft causing in the moment of the robot by wheels. In front portion of the robot a free wheel is attached to move the robot easily in any direction as per the requirement.
A 12Volts DC battery is attached to the circuit. As the microcontroller and sensors requires only 5v, set of resistors and capacitors are used to supply 5v DC to them. Power Management System is not maintained in the circuit as the battery can be removed after the usage of robot. So it does not cause any loss in the power of battery.
This type of robots has multiple applications in various fields. They can be used to know the strength of the opposite army in defense system. They can be used as floor and wall cleaners. They are used in automated GPS vehicles to calculate the moment of the vehicle overhead. These robots are easy to construct and cheaper in cost with long durability.
This project report describes an obstacle avoiding robot created by a student group. The robot uses an ultrasonic sensor to detect obstacles in its path and a microcontroller to control two motors to navigate around obstacles. When the sensor detects an obstacle within 20cm, the microcontroller directs the robot to turn left. Otherwise, it moves straight. The report provides details on the robot's design, components, circuit diagram, algorithm, and testing process. It also discusses potential applications and future improvements.
This document describes an automatic street light control circuit using an LDR (light dependent resistor). The circuit uses an LDR, resistors, capacitors, diodes, a transistor and relay to automatically turn on LED street lights when it gets dark. When the LDR detects a drop in light levels, it causes the transistor to switch on, powering the relay and turning on the lights. The circuit requires few components, consumes little power and provides an efficient automatic method for controlling street lights without manual operation.
Powerpoint Presentation On Obstacle Avoidance Robot
Download the ppt file from the following link::
https://adf.ly/rdC2Z
Embedded system for traffic light controlMadhu Prasad
This document describes an embedded systems project for traffic light control. It presents the background and motivation for optimizing traffic light control using wireless sensors. The proposed system uses an ARM7 microcontroller programmed in embedded C to process real-time data from wireless sensors and control LED traffic lights accordingly. The goal is to study different traffic density situations and optimize traffic flow.
Obstacle Avoidance Robot Summer training Presentation Wasi Abbas
i did an extremely hard work on it. I believe that you all my friends will surely get the benefit of this presentation. As a student of B.tech I just wish to assist those who always ready to assist another one. thanks for reading......
The document discusses the Arduino, an open-source electronics prototyping platform. It provides a brief history of how Arduino was created in 2005 to provide an affordable platform for interactive design projects. It describes the key features of the Arduino Uno board and the Arduino programming environment. Finally, it outlines some common applications of Arduino in fields like home automation, robotics, and sensor prototyping.
This document describes the design and development of an obstacle avoiding robot. The robot uses infrared sensors and a microcontroller to detect and avoid obstacles in its path. When an obstacle is detected, the microcontroller stops one motor and moves the other, causing the robot to turn away from the obstacle. The robot was designed using software like DipTrace and programmed using Keil uVision. It was tested to ensure proper functioning and avoids obstacles as intended. Potential applications and future improvements are also discussed.
This document describes an obstacle avoiding car project created by Utkarsh Bingewar, Shubham Thakur, and Rupesh Rote, with guidance from their assistant professor Mrs. Varsha Nanaware. The car uses an ultrasonic sensor and Arduino board to detect obstacles and navigate around them. When an obstacle is detected, the Arduino controls the motors to turn the car left or right to avoid the obstacle. The obstacle avoiding car has applications in areas like surveillance, hazardous environments, and unmanned vehicle navigation.
Obstacle detection Robot using Ultrasonic Sensor and Arduino UNOSanjay Kumar
This document describes how to build an obstacle detection robot using an Arduino UNO, ultrasonic sensor, and motor driver module. It explains the components used, including the Arduino, ultrasonic sensor to detect obstacles from 2-400cm away, and an L298N motor driver module to control DC motors. It provides details on connecting the components, programming the ultrasonic sensor to trigger and receive echo signals to determine distances, and controlling the motor's direction depending on detected obstacles to help the robot navigate. Code and more details are available at the provided GitHub link.
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.
The document describes an obstacle avoiding robot created by four group members using an Arduino UNO, ultrasonic sensor, DC motor driver, and connecting wires. The robot senses obstacles in its path using the ultrasonic sensor, avoids obstacles by reversing or turning, and resumes moving forward once the path is clear. The robot's program uses the ultrasonic sensor readings to determine its speed and maneuvering.
Difference Between Impatt Diode and Trapatt Diode and Baritt DiodeAL- AMIN
This 3 sentence document discusses different types of diodes. It mentions Impatt diode, Trapatt diode, and Baritt diode but does not provide any details about the differences between them. The document references a photo but does not include the photo or provide any other context.
This document is an obstacle avoiding car project report submitted by three students - Utkarsh Bingewar, Shubham Thakur, and Rupesh Rote - to partially fulfill their project requirements for a bachelor's degree in electronics and telecommunications engineering. The report describes the design and implementation of a robotic vehicle that uses an ultrasonic sensor and microcontroller to detect and avoid obstacles in its path by controlling two DC motors through a motor driver. Experimental results show the car is able to successfully detect and navigate around obstacles.
Vechicle accident prevention using eye bilnk sensor pptsatish 486
This document describes a vehicle accident prevention system using an eye blink sensor. The system uses an IR sensor to detect a driver's eye blinks and a microcontroller to process the sensor data. If no eye blinks are detected for a period of time, indicating potential drowsiness, the system will stop the vehicle and trigger an alarm to prevent accidents. The system could also be expanded in the future to detect alcohol and stop the vehicle if the driver is intoxicated.
The document describes a line follower robot that uses infrared sensors to detect and follow a black line on a white surface. It uses an L293d motor driver IC to control two DC motors and drive the wheels. An LM324 comparator IC compares the output of the IR sensors to a reference voltage to determine if the sensor is over the black line or white surface. The robot also uses an L7805 voltage regulator to maintain a constant voltage supply for the components. The robot is able to navigate tight curves by sensing the line with the IR sensors and maneuvering accordingly using the closed-loop control system.
This document discusses the components, working principle, and programming of a line following robot. It contains the following key points:
1) The main components of the line following robot are an Arduino, IR sensors, an L293D motor driver, motors, and a chassis. The IR sensors detect a dark line on a light surface and signal the motors to move via the Arduino.
2) The working principle involves the IR sensors detecting the line and signaling the appropriate motors to run or stop via the Arduino, causing the robot to follow the line. Turning is achieved by stopping one motor and running the other.
3) Programming on the Arduino involves setting the motors and sensors as inputs/
This document describes a line following robot project built using an Arduino microcontroller. It lists the components used, which include the Arduino UNO, IR sensors, an L298N motor driver, DC motors, and a chassis. It explains the working principle of how the IR sensors detect a line and the motor driver is used to control the DC motors to follow the line. Diagrams of the circuit, programming code, potential applications, and advantages/disadvantages of the line following robot are also provided.
The document presents a line following robot project that uses an Arduino UNO microcontroller board. The robot follows a black line on a white floor using an array of infrared transmitters and receivers. The Arduino UNO controls two motor drivers that power the robot's motors to move forward when on the line based on sensor feedback. Potential applications of this type of line following robot include industrial material transport, automated vehicles, floor cleaning, and path guidance. The project aims to create a simple robot that can autonomously navigate using a line on the ground as a guide.
The line following robot uses two IR sensors to detect a black line on a white surface. It moves forward when both sensors detect white, turns left when the left sensor detects black, and turns right when the right sensor detects black. The robot stops when both sensors detect black. It is built using an Arduino UNO, two DC motors controlled by an L293D motor driver IC, two IR sensors, a robot chassis, and a black electrical tape line on a white surface.
Line following is one of the most important aspects of Robotics. A Line Follower Robot is an autonomous robot which is able to follow either a black or white line that is drawn on the surface consisting of a contrasting color. It is designed to move automatically and follow the made plot line. The path can be visible like a black line on a white surface or it can be invisible like a magnetic field. It will move in a particular direction Specified by the user and avoids the obstacle which is coming in the path. Autonomous Intelligent Robots are robot that can perform desired tasks in unstructured environments without continuous human guidance. It is an integrated design from the knowledge of Mechanical, Electrical, and Computer Engineering. LDR sensors based line follower robot design and Fabrication procedure which always direct along the black mark on the white surface. The robot uses several sensors to identify the line thus assisting the bot to stay on the track. The robot is driven by DC motors to control the movements of the wheels.
Obstacle Avoiding robot is a self thinking robot which can take decisions itself using programmed brain without any guidance from human beings. In our Project we use Infrared to sense obstacles and take movements accordingly. Our Project
mainly used in military application, small toys and also used in mines by increasing IR sensors.
Robotics is a branch of science that deals with Mechanical, Electrical and Software fields. Robots are the machines that are used in our day-to-day to life to reduce men power and work accurately without any distortions. Robots can be classified into two different sections basing upon their skills as Automated and Manual. Obstacle detector is a Automated robot which itself recognizes the obstacle in its path and moves in free direction. Robot detects the obstacle by using two IR Sensors placed in front.
The IR sensors are placed on left and right side of the robot through which continuous Infrared radiation is emitted for detection of obstacles in the path. These IR Sensors are connected to a controlling element AT89c51 µc. When a obstacle is placed in the path of robot IR beam is reflected to the sensor from the obstacle. On detecting obstacle in the path sensor sends 0 volts to µc. This 0 voltage is detected by Microcontroller which avoids the obstacle by taking left or right turn. Similarly if the sensor sends +5v to Microcontroller, the Microcontroller assumes it as clear path and makes the robot to move in straight.
Two motors namely right motor and left motor are connected to Motor driver IC (L293D). L293D is interface with Microcontroller. Microcontroller sends logic 0 & logic 1 as per the programming to driver IC which makes motors to rotate in clockwise and anticlockwise direction. Wheels attached to the motors rotate accordingly with the motor shaft causing in the moment of the robot by wheels. In front portion of the robot a free wheel is attached to move the robot easily in any direction as per the requirement.
A 12Volts DC battery is attached to the circuit. As the microcontroller and sensors requires only 5v, set of resistors and capacitors are used to supply 5v DC to them. Power Management System is not maintained in the circuit as the battery can be removed after the usage of robot. So it does not cause any loss in the power of battery.
This type of robots has multiple applications in various fields. They can be used to know the strength of the opposite army in defense system. They can be used as floor and wall cleaners. They are used in automated GPS vehicles to calculate the moment of the vehicle overhead. These robots are easy to construct and cheaper in cost with long durability.
The document describes a path following robot project created by engineering students. It uses IR sensors to detect a black path on a white surface and a PIC microcontroller to process sensor inputs and control motors to follow the path. It provides a block diagram of the robot's components and architecture. It also details the algorithm used by the microcontroller to determine motor movements based on sensor readings to navigate straight paths and turns.
This document describes a line tracking robot project created by two students. The robot uses infrared sensors to follow a black line on a white surface. It is powered by an Arduino UNO microcontroller and uses an L298N motor driver and DC motors. The future plans are to add a GSM module to monitor the robot's functions remotely. The conclusion states that line tracking robots have applications in industries for transporting goods automatically and accurately.
The document describes an obstacle observing robot that uses infrared sensors to detect obstacles and avoid them. It consists of an ATmega8 microcontroller, infrared sensors, a motor driver, and motors. The infrared sensors transmit and receive signals to detect obstacles. When an obstacle is detected, the robot diverts itself to move around the obstacle without human guidance. It is designed to autonomously navigate an area while avoiding obstacles.
The document describes the design of a line follower robot using an Arduino kit. The robot uses IR sensors mounted on the front left and right to detect a black line on a light surface. When both sensors detect white, the robot moves forward. When one sensor detects black, the microcontroller stops the associated motor, causing the robot to turn in the direction of the line. Potential applications include use in industrial equipment transport, as automated vehicles, for domestic tasks like cleaning, and for guidance in public spaces.
This project aims to build an autonomous obstacle avoidance vehicle using ultrasonic sensors. The vehicle is controlled by a microcontroller and can sense obstacles, avoid them, and find an obstacle-free path on its own. Ultrasonic sensors detect surroundings in real-time and allow the vehicle to move toward its target area while avoiding obstacles. The vehicle is designed using an Arduino Uno microcontroller, ultrasonic sensors, a motor driver, DC motors, and other hardware components to achieve autonomous navigation.
The document describes an edge-avoiding robot that uses infrared (IR) sensors to detect edges and avoid falling off surfaces. It works by emitting IR rays from sensor modules and detecting the reflected rays. If both sensors receive rays, it continues forward. If one sensor detects an edge and stops receiving rays while the other still does, the robot turns away from the edge. The robot's hardware components include an Arduino, motor driver, DC motors, IR sensors, and other parts. It also explains how the ultrasonic sensor, servo motor, and motor driver circuit work.
This document describes the design and implementation of an obstacle avoiding robot using an Arduino microcontroller. It includes a list of hardware components like the Arduino Uno, ultrasonic sensor, motor driver IC, servo motor and chassis. The circuit diagram and code are provided to explain how the Arduino controls the ultrasonic sensor, servo motor and motors to enable the robot to detect obstacles within 15cm and navigate around them. Applications of such robots include automated vacuuming, navigation in hazardous environments, and more.
1) The document describes an obstacle avoiding robot project built using an Arduino Uno, ultrasonic sensor, motor driver IC, servo motor, geared motors, and chassis.
2) The robot is programmed to continuously measure the distance to obstacles using the ultrasonic sensor and avoid obstacles by rotating or backing up when distances are less than 15cm.
3) Potential applications of obstacle avoiding robots include household vacuuming, dangerous environments where human access is unsafe, and mobile robot navigation systems.
This document summarizes key aspects of robotics and a line following robot project. It discusses that robotics involves designing and building intelligent mechanical agents to perform tasks autonomously or with guidance. It then describes a line following robot that uses infrared sensors to detect and follow a black line on a white surface without human control. The robot is able to correct itself to stay on the track and uses different motor speeds to enable turns. Microcontrollers like the ATmega8L are used as the processing system to generate outputs from sensor inputs.
A line follower robot is designed to follow a predetermined path marked by a physical line or other markers. Various sensing schemes can detect these markers, ranging from simple low-cost line sensors to complex vision systems. Line follower robots are commonly used in manufacturing plants to move along specified paths and pick up and place components. They work by using sensors to detect the line path and feedback mechanisms to stay on course while correcting deviations.
This document describes a line following robot project created by students at the Shri Govindram Seksaria Institute of Technology and Science Indore. The robot uses 3 IR sensor pairs and 2 motors to follow a black line on a white surface. It works by using the IR sensors to detect the line and send signals to the motor control circuitry, which instructs the motors to move the robot forward or turn as needed to stay on the line. The document discusses the components, working model, block diagram, applications and conclusions of the project. It proposes areas for future work, such as using a microcontroller and color sensors to add obstacle avoidance and other capabilities to the robot.
Electrical and Electronics Engineering: An International Journal (ELELIJ)elelijjournal653
Call For Papers...!!!
Electrical and Electronics Engineering: An International Journal (ELELIJ)
Web page link: https://wireilla.com/engg/eeeij/index.html
Submission Deadline: June 08, 2025
Submission link: [email protected]
Contact Us: [email protected]
The development of smart cities holds immense significance in shaping a nation's urban fabric and effectively addressing urban challenges that profoundly impact the economy. Among these challenges, road accidents pose a significant obstacle to urban progress, affecting lives, supply chain efficiency, and socioeconomic well-being. To address this issue effectively, accurate forecasting of road accidents is crucial for policy formulation and enhancing safety measures. Time series forecasting of road accidents provides invaluable insights for devising strategies, enabling swift actions in the short term to reduce accident rates, and informing well-informed road design and safety management policies for the long term, including the implementation of flyovers, and the enhancement of road quality to withstand all weather conditions. Deep Learning's exceptional pattern recognition capabilities have made it a favored approach for accident forecasting. The study comprehensively evaluates deep learning models, such as RNN, LSTM, CNN+LSTM, GRU, Transformer, and MLP, using a ten-year dataset from the esteemed Smart Road Accident Database in Hubballi-Dharwad. The findings unequivocally underscore LSTM's superiority, exhibiting lower errors in both yearly (RMSE: 0.291, MAE: 0.271, MAPE: 6.674%) and monthly (RMSE: 0.186, MAE: 0.176, MAPE: 5.850%) variations. Based on these compelling findings, the study provides strategic recommendations to urban development authorities, emphasizing comprehensive policy frameworks encompassing short-term and long-term measures to reduce accident rates alongside meticulous safety measures and infrastructure planning. By leveraging insights from deep learning models, urban development authorities can adeptly shape the urban landscape, fostering safer environments and contributing to global safety and prosperity.
Rearchitecturing a 9-year-old legacy Laravel application.pdfTakumi Amitani
An initiative to re-architect a Laravel legacy application that had been running for 9 years using the following approaches, with the goal of improving the system’s modifiability:
・Event Storming
・Use Case Driven Object Modeling
・Domain Driven Design
・Modular Monolith
・Clean Architecture
This slide was used in PHPxTKY June 2025.
https://phpxtky.connpass.com/event/352685/
PREDICTION OF ROOM TEMPERATURE SIDEEFFECT DUE TOFAST DEMAND RESPONSEFOR BUILD...ijccmsjournal
In order to evaluate side-effect of power limitation due to the Fast Automated Demand Response
(FastADR) for building air-conditioning facilities, a prediction model on short time change of average
room temperature has been developed. A room temperature indexis defined as a weighted average of the
entire building for room temperature deviations from the setpoints. The index is assumed to be used to
divide total FastADRrequest to distribute power limitation commands to each building.In order to predict
five-minute-change of the index, our combined mathematical model of an auto regression (AR) and a
neural network (NN) is proposed.In the experimental results, the combined model showedthe root mean
square error (RMSE) of 0.23 degrees, in comparison with 0.37 and 0.26 for conventional single NN and AR
models, respectively. This result is satisfactory prediction for required comfort of approximately 1 degree
Celsius allowance.
This study will provide the audience with an understanding of the capabilities of soft tools such as Artificial Neural Networks (ANN), Support Vector Regression (SVR), Model Trees (MT), and Multi-Gene Genetic Programming (MGGP) as a statistical downscaling tool. Many projects are underway around the world to downscale the data from Global Climate Models (GCM). The majority of the statistical tools have a lengthy downscaling pipeline to follow. To improve its accuracy, the GCM data is re-gridded according to the grid points of the observed data, standardized, and, sometimes, bias-removal is required. The current work suggests that future precipitation can be predicted by using precipitation data from the nearest four grid points as input to soft tools and observed precipitation as output. This research aims to estimate precipitation trends in the near future (2021-2050), using 5 GCMs, for Pune, in the state of Maharashtra, India. The findings indicate that each one of the soft tools can model the precipitation with excellent accuracy as compared to the traditional method of Distribution Based Scaling (DBS). The results show that ANN models appear to give the best results, followed by MT, then MGGP, and finally SVR. This work is one of a kind in that it provides insights into the changing monsoon season in Pune. The anticipated average precipitation levels depict a rise of 300–500% in January, along with increases of 200-300% in February and March, and a 100-150% increase for April and December. In contrast, rainfall appears to be decreasing by 20-30% between June and September.
First Review PPT gfinal gyft ftu liu yrfut goSowndarya6
CyberShieldX provides end-to-end security solutions, including vulnerability assessment, penetration testing, and real-time threat detection for business websites. It ensures that organizations can identify and mitigate security risks before exploitation.
Unlike traditional security tools, CyberShieldX integrates AI models to automate vulnerability detection, minimize false positives, and enhance threat intelligence. This reduces manual effort and improves security accuracy.
Many small and medium businesses lack dedicated cybersecurity teams. CyberShieldX provides an easy-to-use platform with AI-powered insights to assist non-experts in securing their websites.
Traditional enterprise security solutions are often expensive. CyberShieldX, as a SaaS platform, offers cost-effective security solutions with flexible pricing for businesses of all sizes.
Businesses must comply with security regulations, and failure to do so can result in fines or data breaches. CyberShieldX helps organizations meet compliance requirements efficiently.
Third Review PPT that consists of the project d etails like abstract.Sowndarya6
CyberShieldX is an AI-driven cybersecurity SaaS web application designed to provide automated security analysis and proactive threat mitigation for business websites. As cyber threats continue to evolve, traditional security tools like OpenVAS and Nessus require manual configurations and lack real-time automation. CyberShieldX addresses these limitations by integrating AI-powered vulnerability assessment, intrusion detection, and security maintenance services. Users can analyze their websites by simply submitting a URL, after which CyberShieldX conducts an in-depth vulnerability scan using advanced security tools such as OpenVAS, Nessus, and Metasploit. The system then generates a detailed report highlighting security risks, potential exploits, and recommended fixes. Premium users receive continuous security monitoring, automatic patching, and expert assistance to fortify their digital infrastructure against emerging threats. Built on a robust cloud infrastructure using AWS, Docker, and Kubernetes, CyberShieldX ensures scalability, high availability, and efficient security enforcement. Its AI-driven approach enhances detection accuracy, minimizes false positives, and provides real-time security insights. This project will cover the system's architecture, implementation, and its advantages over existing security solutions, demonstrating how CyberShieldX revolutionizes cybersecurity by offering businesses a smarter, automated, and proactive defense mechanism against ever-evolving cyber threats.
This document provides information about the Fifth 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.
本資料「To CoT or not to CoT?」では、大規模言語モデルにおけるChain of Thought(CoT)プロンプトの効果について詳しく解説しています。
CoTはあらゆるタスクに効く万能な手法ではなく、特に数学的・論理的・アルゴリズム的な推論を伴う課題で高い効果を発揮することが実験から示されています。
一方で、常識や一般知識を問う問題に対しては効果が限定的であることも明らかになりました。
複雑な問題を段階的に分解・実行する「計画と実行」のプロセスにおいて、CoTの強みが活かされる点も注目ポイントです。
This presentation explores when Chain of Thought (CoT) prompting is truly effective in large language models.
The findings show that CoT significantly improves performance on tasks involving mathematical or logical reasoning, while its impact is limited on general knowledge or commonsense tasks.
May 2025: Top 10 Cited Articles in Software Engineering & Applications Intern...sebastianku31
The International Journal of Software Engineering & Applications (IJSEA) is a bi-monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Software Engineering & Applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts & establishing new collaborations in these areas.
En esta presentación se encuentra la explicación sobre la tomografía Axial Computarizada, se habla sobre su historia, partes, operación general y especifica del equipo, tipos de densidades y sus aplicaciones más comunes y las innovadoras.
2. Index
• Introduction
• Components
• Working Principle
• Block Diagram
• Application
• Advantages and Disadvantages
• Programming on Arduino
Let’s Discuss
3. Introduction
What is a Robot
A Robot is a
machine capable of
carrying out a complex
series of actions
automatically,
especially one
programmable by a
computer.
4. Line Following Robot
What is a Line
Following Robot
Line following Robot
is a machine that
can follow a path.
The path can be
visible like a black
line on a white
surface or it can be
invisible like a
magnetic field.
5. What is the
need to build
line following
Robot?
Sensing a line and
maneuvering the
robot to stay on
course, while
constantly correcting
wrong moves using
feedback mechanism
forms a simple yet
effective closed loop
system.
7. Arduino
Arduino is an open-
source computer hardware
and software company,
project and user community
that designs and
manufactures microcontroller
-based kits for building digital
devices and interactive
objects that can sense and
control objects in the physical
world.
8. IR Sensor
A passive infrared
sensor (PIR sensor) is
an
electronic sensor that
measures infrared (IR)
light radiating from
objects in its field of
view. They are most
often used in PIR-based
motion detectors.
9. L293D(H-Bridge)
• Motors are arranged in a fashion
called H-Bridge.
• H-Bridge-It is an electronic circuit
which enables a voltage to be applied
across a load in either direction.
• It allows a circuit full control over a
standard electric DC motor. That is,
with an H-bridge, a microcontroller,
logic chip, or remote control can
electronically command the motor to
go forward, reverse, brake, and coast.
10. Motors
The motors rotate
clockwise and anti-
clockwise based on
the program. In the
motor electrical
energy is converted
into mechanical
energy.
11. Working Principle
The IR sensor detects the light emitted by the
transmitter, if the receiver receives light, the wheel
of that side will keep on moving, as soon as the
receiver stops receiving the light (black colour
absorbs the light and thus no light is reflected so
receiver cannot receive any light) the wheel of that
side will stop.
For turning ,the robot stops 1 motor and runs the
second to make the turn possible.
For eg:
If the robot has to turn right then the motor on
right side will stop and left motor will keep on
running and thus allowing the robot to turn.
12. Left IR Sensor Right IR Sensor Motion
1 1 Forward
1 0 Right
0 1 Left
0 0 Reverse
Motor Logic
15. Applications
• Industrial automated equipment carriers.
• Automated cars.
• Tour guides in museums and other similar
applications.
• Deliver the mail within the office building
• Deliver medications in a hospital.
Where is
this used?
16. Advantages
• The robot must be capable of following a line.
• Insensitive to environment factors like noise
and lightning.
• It should be capable of taking various degrees
of turns.
• The color of the line must not be a factor as
long as it is darker than the surroundings.
What are
the
advantages
17. Disadvantages
• LFR can move on a fixed track or path.
• It requires power supply.
• Lack of speed control makes the robot
unstable at times.
• Choice of line is made in the hardware
abstraction and cannot be changed by
software.
What are the
disadvantages
?