Google Self Driving Car System
•Download as PPTX, PDF•
1 like•463 views
Google's self-driving cars use 10 key technologies including laser range finders, radars, cameras, and aerials to safely navigate roads. Laser range finders and cameras allow the car to detect objects like pedestrians and interpret road signs. Radars mounted on the front and rear bumpers enable the car to maintain a safe distance from other vehicles. An aerial receives precise location information from GPS satellites, although GPS signals can sometimes be off by several meters.
Report
Share
Report
Share
Recommended
Driverless car
Driverless cars use sensors and technology to navigate roadways without human assistance. They work by sensing their surroundings, processing sensory information to determine the appropriate path while avoiding obstacles and obeying traffic laws. Key technologies that enable autonomous driving include anti-lock brakes, electronic stability control, cruise control, lane departure warning, self-parking systems, LIDAR, radar and GPS. While driverless cars could improve safety and reduce emissions, issues around performance in poor weather, legal liability in crashes, and potential job losses remain challenges.
Self driving car
Driverless cars use various sensors and technologies to navigate roadways without human assistance. Sensors allow the car to detect traffic lights and other vehicles. Technologies like ABS, cruise control, and lane departure warning systems help the car stay centered and maintain speed. While driverless cars could help reduce accidents caused by human error and increase road capacity, they also present security risks if hackers are able to access vehicle controls.
Google car (self driving car )
The document discusses self-driving cars, known as Google Cars. It describes the technologies and components that enable autonomous driving, including sensors like LIDAR, radar, cameras and ultrasonic sensors. These sensors gather data about the vehicle's environment that is processed by the car's CPU to navigate safely without human assistance. Some challenges for self-driving cars are legal restrictions, security issues, difficulty driving in heavy rain or differentiating objects. The document concludes that with further development, self-driving cars could be in use by 2020 to reduce accidents by following traffic rules efficiently.
GOOGLE CAR(autonomous car)
The document discusses Google's driverless car project. It provides an introduction to autonomous vehicles and describes some of the key technologies used in Google's cars, including laser range finders, cameras, radars, ultrasonic sensors, and GPS. The technologies work together to map the vehicle's environment, plan a safe route, and navigate while avoiding obstacles. Some advantages are fewer accidents and a smoother ride, though limitations include an inability to detect all hazards and potential security issues from hackers. In conclusion, autonomous vehicles may increase safety and improve traffic conditions by removing human error.
Google Self Driving Car
The document discusses self-driving cars and how they work. It explains that self-driving cars, also known as autonomous cars or driverless cars, can drive themselves from one destination to another without human assistance using sensors, artificial intelligence software, and Google Maps. The car detects traffic lights and other objects using LIDAR, video cameras, radar, and other distance and position sensors to navigate autonomously.
Autonomous car
An autonomous car uses sensors like LIDAR, RADAR, cameras and ultrasonic sensors to navigate without human input. It has two seats and drives at the speed limit while maintaining a safe distance from other vehicles. LIDAR uses lasers to generate 3D maps of the environment while RADAR detects objects' speeds and positions using radio waves. Autonomous cars aim to minimize accidents by removing human error from driving and allow disabled people to drive. However, they have disadvantages like inability to handle heavy weather, slow speeds at intersections, high costs, and potential for system failures.
Autonomous car
As per the growth of population, every company lunch their products with new technology and features. Automobile industry also lunch new cars with new technology and features.
Presentation on driverless cars by shahin hussan
This document discusses driverless car technologies including how cars will detect traffic lights using light sensors, technologies that enable fully autonomous systems like ABS and electronic stability control, and how vehicles will be controlled. It also covers cruise control, night vision, lane departure warning, adaptive high beams, self-parking, rear cameras, and automated guided vehicle systems. The goal of driverless cars is to reduce accidents by taking on driving tasks and allowing occupants to rest or focus on other things.
Recommended
Driverless car
Driverless cars use sensors and technology to navigate roadways without human assistance. They work by sensing their surroundings, processing sensory information to determine the appropriate path while avoiding obstacles and obeying traffic laws. Key technologies that enable autonomous driving include anti-lock brakes, electronic stability control, cruise control, lane departure warning, self-parking systems, LIDAR, radar and GPS. While driverless cars could improve safety and reduce emissions, issues around performance in poor weather, legal liability in crashes, and potential job losses remain challenges.
Self driving car
Driverless cars use various sensors and technologies to navigate roadways without human assistance. Sensors allow the car to detect traffic lights and other vehicles. Technologies like ABS, cruise control, and lane departure warning systems help the car stay centered and maintain speed. While driverless cars could help reduce accidents caused by human error and increase road capacity, they also present security risks if hackers are able to access vehicle controls.
Google car (self driving car )
The document discusses self-driving cars, known as Google Cars. It describes the technologies and components that enable autonomous driving, including sensors like LIDAR, radar, cameras and ultrasonic sensors. These sensors gather data about the vehicle's environment that is processed by the car's CPU to navigate safely without human assistance. Some challenges for self-driving cars are legal restrictions, security issues, difficulty driving in heavy rain or differentiating objects. The document concludes that with further development, self-driving cars could be in use by 2020 to reduce accidents by following traffic rules efficiently.
GOOGLE CAR(autonomous car)
The document discusses Google's driverless car project. It provides an introduction to autonomous vehicles and describes some of the key technologies used in Google's cars, including laser range finders, cameras, radars, ultrasonic sensors, and GPS. The technologies work together to map the vehicle's environment, plan a safe route, and navigate while avoiding obstacles. Some advantages are fewer accidents and a smoother ride, though limitations include an inability to detect all hazards and potential security issues from hackers. In conclusion, autonomous vehicles may increase safety and improve traffic conditions by removing human error.
Google Self Driving Car
The document discusses self-driving cars and how they work. It explains that self-driving cars, also known as autonomous cars or driverless cars, can drive themselves from one destination to another without human assistance using sensors, artificial intelligence software, and Google Maps. The car detects traffic lights and other objects using LIDAR, video cameras, radar, and other distance and position sensors to navigate autonomously.
Autonomous car
An autonomous car uses sensors like LIDAR, RADAR, cameras and ultrasonic sensors to navigate without human input. It has two seats and drives at the speed limit while maintaining a safe distance from other vehicles. LIDAR uses lasers to generate 3D maps of the environment while RADAR detects objects' speeds and positions using radio waves. Autonomous cars aim to minimize accidents by removing human error from driving and allow disabled people to drive. However, they have disadvantages like inability to handle heavy weather, slow speeds at intersections, high costs, and potential for system failures.
Autonomous car
As per the growth of population, every company lunch their products with new technology and features. Automobile industry also lunch new cars with new technology and features.
Presentation on driverless cars by shahin hussan
This document discusses driverless car technologies including how cars will detect traffic lights using light sensors, technologies that enable fully autonomous systems like ABS and electronic stability control, and how vehicles will be controlled. It also covers cruise control, night vision, lane departure warning, adaptive high beams, self-parking, rear cameras, and automated guided vehicle systems. The goal of driverless cars is to reduce accidents by taking on driving tasks and allowing occupants to rest or focus on other things.
Driverless car
This document presents information on driverless cars. It discusses how driverless cars will use sensors to detect objects and traffic lights to slow or stop, reducing accidents. Technologies that enable fully autonomous vehicles are described, including ABS, ESC, cruise control, lane departure warning, self-parking. Automated guided vehicle systems are controlled by computers and GPS to determine location and manage traffic flow. While driverless cars could increase road safety, they may also introduce security risks if hackers are able to access vehicle controls remotely.
Google Driverless Car
Google driver less car is also known as autonomous car. It can travel from one point to another without any assistance from driver. It uses hardware sensors like LiDAR, position estimator, distance sensor, GPS, etc and Artificial Intelligence. Google map and Google street view are used for proper navigation. This technology reduces the traffic accidents and will make navigation more efficient.
Self Driving Autopilot Car
This document discusses self-driving or autonomous vehicles. It provides an introduction to autonomous cars and their ability to sense surroundings using sensors and computer vision. The document outlines some of the technologies used in autonomous vehicles, including radar, lidar, GPS, cameras, ultrasonic sensors and more. It describes how components like ABS, electronic stability control, adaptive high beams, night vision and parking sensors contribute to autonomous functionality. The document discusses advantages such as reduced accidents and improved mobility for disabled/elderly, as well as disadvantages including job loss and hacking risks. It concludes that autonomous vehicles could significantly reduce traffic and avoid accidents by 2020.
Real time Driverless vehicles
The document discusses driverless vehicle technologies, including how they detect traffic lights and sense their surroundings. It describes sensors like radar, lidar, cameras and GPS that provide input to control systems. The control systems analyze sensor data to identify paths and obstacles. Technologies like automatic braking, electronic stability control and cruise control help control the vehicle. The processor makes sense of sensor data to guide actuators that control the vehicle without driver assistance.
FULLY AUTONOMOUS DRIVERLESS CARS : GOOGLE CAR
My Seminar on Google Car: Prepared from another slide in Slideshare : Thank You Bro( creator of that slide)
Self driving vehicle
Google is developing self-driving vehicles that use advanced sensors like LIDAR and cameras, as well as software, to navigate roads safely without human intervention. They have tested prototypes like the Toyota Prius and Lexus RX450h on over 700,000 miles of public roads in California and Nevada. Google's fully autonomous prototype vehicle unveiled in 2014 has no steering wheel or pedals and is being built with partners to further develop the technology. While self-driving vehicles could significantly reduce accidents, regulatory and technology challenges remain before they are ready for commercial use.
Self driving car
Self-driving cars use sensors like radar, GPS, and computer vision to detect their environment without human input. Advanced control systems interpret sensory data to identify paths and obstacles. Technologies used include anti-lock brakes, adaptive cruise control, and lidar systems. Algorithms like edge detection are used to locate intensity contrasts and track objects over image sequences. Self-driving cars aim to increase road capacity, relieve drivers, avoid accidents, and minimize loss of control compared to human drivers.
Autonomous car(driver less car) (self driving car)
brief seminar on the driverless car , with full information about the sensers used for making the car as a driverless car or self driving car
Robotic car seminar report
Google's autonomous cars use sensors like radar and LIDAR to take in information, process it quickly, make decisions, and drive better than humans. Autonomous driving is challenging but progressing, with advances in technologies like adaptive cruise control. While fully driverless cars are still being developed, some companies plan to test or integrate more autonomous features in coming years. Legal and safety issues still need to be addressed before widespread adoption of autonomous vehicles.
Autonomous car
The document discusses autonomous cars, including their history from early experiments in the 1920s to working prototypes in the 1980s. It describes the key components of autonomous cars like LIDAR, radar, cameras and GPS that work together to navigate and drive the vehicle without human assistance. The document also outlines some advantages like increased safety and productivity, as well as challenges to widespread adoption like sensor limitations in heavy weather and high manufacturing costs.
Driver-less cars by avaneesh shuka
Driverless cars use automatic control systems to navigate roadways without human assistance. Sensors detect road conditions and obstacles while navigation systems plot routes. Motion planning software controls acceleration, braking, and steering to maneuver safely through traffic. Early technologies like ABS, cruise control, and automated guided vehicles demonstrated autonomous vehicle components. The 2007 DARPA Urban Challenge advanced driverless car capabilities by having vehicles navigate a 96km urban course obeying all traffic laws. While autonomous vehicles can increase road safety and capacity, cybersecurity risks and sensor failures present disadvantages requiring further development.
Autonomous car
An autonomous car, also known as a self-driving car, uses sensors and computer vision to navigate and drive with little to no human input. Autonomous cars use radar, lidar, sonar, GPS and computer vision to perceive their surroundings and an advanced control system to identify navigation paths and obstacles. There are six levels of vehicle automation from fully manual to fully autonomous without human intervention. Autonomous vehicles have advantages like reducing accidents, easing traffic, and stress-free parking, but also disadvantages like high costs, safety and security concerns, and sensors being prone to failure or hacking.
Autonomous-cars / Self Driving Cars
Under this topic i have described about the autonomous cars, on which worlds top automobile and tech giants are working like google, ford, BMW, audi etc.
Driverless car - Rahul Gosai
The document discusses driverless cars, providing a history, reasons for their development, how they work, current status, and advantages/disadvantages. It notes that driverless cars can drive autonomously using sensors and GPS, major companies have been developing prototypes since the 1980s, and they may be ready for markets in 3-4 years. Driverless cars could help reduce accidents caused by human error and be useful for disabled and elderly people.
Autonomous car
This document discusses driverless cars, including their benefits, components, examples like Google's driverless car project, positive and negative aspects, and future developments. It notes that driverless cars can provide more efficient driving, help the elderly and disabled, manage traffic, and reduce accidents. Key components include sensors, artificial intelligence, and backup systems. While driverless cars may reduce accidents, concerns include credibility, security issues, inability to handle certain conditions, and job losses. The future adoption of autonomous vehicles is expected to grow significantly in the next few years across many auto manufacturers.
AUTO PILOT TECHNOLOGY IN VEHICLES
This presentation discusses auto pilot technology for vehicles. It introduces auto pilot technology as a way to enable self-driving vehicles that can steer, park and drive themselves on highways without human control. The key components that enable auto pilot include display units, radars, sensors and advanced GPS mapping systems. Radars detect objects up to 180 feet away while sensors monitor road conditions and angles to help the control unit navigate safely. Auto pilot technology aims to reduce accidents by taking over driving tasks but hackers changing routes and sensor failures present risks. The presentation concludes that fully implementing auto pilot could significantly reduce accidents and work towards an accident-free world.
Waymo ppt
Waymo is an autonomous vehicle company that was spun out of Google in 2016. It took over Google's self-driving car project which began in 2009. Waymo cars use LIDAR, radar, orientation sensors, wheel hub sensors and high-resolution maps to navigate without human input. The technology allows the cars to generate 3D maps of their environment to safely drive on roads. However, as of 2014 the cars could only navigate about 1% of US roads and had safety issues in heavy rain or snow. Waymo is working to address current limitations by 2020.
Advanced driver assistance systems
Advanced driver assistance systems are designed to increase car safety and road safety overall. They help the driver in the driving process to enable safe and relaxed driving. Some examples of driver assistance systems that maximize safety include antilock braking systems, adaptive cruise control, blind spot detection, driver drowsiness detection, electronic stability control, emergency braking systems, hill descent control, intelligent speed assistance, lane departure warning systems, pedestrian detection, rear cross traffic alert, and traffic sign recognition. These systems alert drivers to hazards, help maintain safe distances and speeds, and in some cases automatically apply brakes to avoid collisions.
Google self driving car technology
The Google driverless car is a project by Google that involves developing technology for autonomous cars.
The Google Driverless Car is like any car, but:
It can steer itself while looking out for obstacles.
It can accelerate itself to the correct speed limit.
It can stop and go itself based on any traffic
The software powering Google's cars is called Google Chauffeur.
It can take its passengers anywhere it wants to go safely, legally, and comfortably.
Currently being led by Sebastian Thrun ,former director of Stanford Artificial Intelligence Laboratory and co-inventor of Google’s Street View.
Best Driver less cars Ppt by-dinesh kumar from jaipur
The document discusses autonomous vehicles and their components. It provides an overview of the history and development of autonomous vehicles. It describes the various sensors like GPS, lidar, and radar that autonomous vehicles use to navigate environments and detect objects. It explains how autonomous vehicles work through components like sensors, navigation, motion planning and actuation. It discusses advantages like increased road capacity and safety, as well as potential disadvantages like security issues if the vehicle is hacked.
Google Self-Driving Car: A Long And Winding Road to Success
Google unveiled a brand new self-driving car prototype; the first company to build a car with no a steering wheel, accelerator or brake pedal.
Autonomous Vehicles
Autonomous vehicles use various sensors like ultrasonic sensors, RADAR, LIDAR, image sensors, GPS, and wheel speed sensors to navigate without human input. They rely on sensor integration and technologies like computer vision, V2X communication, and electronic control units to process sensor data. While self-driving cars offer benefits like safety and efficiency, there are also challenges to overcome like unpredictable humans, bad weather, and needing detailed digital maps. Fully autonomous vehicles may become common by 2040 if these issues can be addressed.
More Related Content
What's hot
Driverless car
This document presents information on driverless cars. It discusses how driverless cars will use sensors to detect objects and traffic lights to slow or stop, reducing accidents. Technologies that enable fully autonomous vehicles are described, including ABS, ESC, cruise control, lane departure warning, self-parking. Automated guided vehicle systems are controlled by computers and GPS to determine location and manage traffic flow. While driverless cars could increase road safety, they may also introduce security risks if hackers are able to access vehicle controls remotely.
Google Driverless Car
Google driver less car is also known as autonomous car. It can travel from one point to another without any assistance from driver. It uses hardware sensors like LiDAR, position estimator, distance sensor, GPS, etc and Artificial Intelligence. Google map and Google street view are used for proper navigation. This technology reduces the traffic accidents and will make navigation more efficient.
Self Driving Autopilot Car
This document discusses self-driving or autonomous vehicles. It provides an introduction to autonomous cars and their ability to sense surroundings using sensors and computer vision. The document outlines some of the technologies used in autonomous vehicles, including radar, lidar, GPS, cameras, ultrasonic sensors and more. It describes how components like ABS, electronic stability control, adaptive high beams, night vision and parking sensors contribute to autonomous functionality. The document discusses advantages such as reduced accidents and improved mobility for disabled/elderly, as well as disadvantages including job loss and hacking risks. It concludes that autonomous vehicles could significantly reduce traffic and avoid accidents by 2020.
Real time Driverless vehicles
The document discusses driverless vehicle technologies, including how they detect traffic lights and sense their surroundings. It describes sensors like radar, lidar, cameras and GPS that provide input to control systems. The control systems analyze sensor data to identify paths and obstacles. Technologies like automatic braking, electronic stability control and cruise control help control the vehicle. The processor makes sense of sensor data to guide actuators that control the vehicle without driver assistance.
FULLY AUTONOMOUS DRIVERLESS CARS : GOOGLE CAR
My Seminar on Google Car: Prepared from another slide in Slideshare : Thank You Bro( creator of that slide)
Self driving vehicle
Google is developing self-driving vehicles that use advanced sensors like LIDAR and cameras, as well as software, to navigate roads safely without human intervention. They have tested prototypes like the Toyota Prius and Lexus RX450h on over 700,000 miles of public roads in California and Nevada. Google's fully autonomous prototype vehicle unveiled in 2014 has no steering wheel or pedals and is being built with partners to further develop the technology. While self-driving vehicles could significantly reduce accidents, regulatory and technology challenges remain before they are ready for commercial use.
Self driving car
Self-driving cars use sensors like radar, GPS, and computer vision to detect their environment without human input. Advanced control systems interpret sensory data to identify paths and obstacles. Technologies used include anti-lock brakes, adaptive cruise control, and lidar systems. Algorithms like edge detection are used to locate intensity contrasts and track objects over image sequences. Self-driving cars aim to increase road capacity, relieve drivers, avoid accidents, and minimize loss of control compared to human drivers.
Autonomous car(driver less car) (self driving car)
brief seminar on the driverless car , with full information about the sensers used for making the car as a driverless car or self driving car
Robotic car seminar report
Google's autonomous cars use sensors like radar and LIDAR to take in information, process it quickly, make decisions, and drive better than humans. Autonomous driving is challenging but progressing, with advances in technologies like adaptive cruise control. While fully driverless cars are still being developed, some companies plan to test or integrate more autonomous features in coming years. Legal and safety issues still need to be addressed before widespread adoption of autonomous vehicles.
Autonomous car
The document discusses autonomous cars, including their history from early experiments in the 1920s to working prototypes in the 1980s. It describes the key components of autonomous cars like LIDAR, radar, cameras and GPS that work together to navigate and drive the vehicle without human assistance. The document also outlines some advantages like increased safety and productivity, as well as challenges to widespread adoption like sensor limitations in heavy weather and high manufacturing costs.
Driver-less cars by avaneesh shuka
Driverless cars use automatic control systems to navigate roadways without human assistance. Sensors detect road conditions and obstacles while navigation systems plot routes. Motion planning software controls acceleration, braking, and steering to maneuver safely through traffic. Early technologies like ABS, cruise control, and automated guided vehicles demonstrated autonomous vehicle components. The 2007 DARPA Urban Challenge advanced driverless car capabilities by having vehicles navigate a 96km urban course obeying all traffic laws. While autonomous vehicles can increase road safety and capacity, cybersecurity risks and sensor failures present disadvantages requiring further development.
Autonomous car
An autonomous car, also known as a self-driving car, uses sensors and computer vision to navigate and drive with little to no human input. Autonomous cars use radar, lidar, sonar, GPS and computer vision to perceive their surroundings and an advanced control system to identify navigation paths and obstacles. There are six levels of vehicle automation from fully manual to fully autonomous without human intervention. Autonomous vehicles have advantages like reducing accidents, easing traffic, and stress-free parking, but also disadvantages like high costs, safety and security concerns, and sensors being prone to failure or hacking.
Autonomous-cars / Self Driving Cars
Under this topic i have described about the autonomous cars, on which worlds top automobile and tech giants are working like google, ford, BMW, audi etc.
Driverless car - Rahul Gosai
The document discusses driverless cars, providing a history, reasons for their development, how they work, current status, and advantages/disadvantages. It notes that driverless cars can drive autonomously using sensors and GPS, major companies have been developing prototypes since the 1980s, and they may be ready for markets in 3-4 years. Driverless cars could help reduce accidents caused by human error and be useful for disabled and elderly people.
Autonomous car
This document discusses driverless cars, including their benefits, components, examples like Google's driverless car project, positive and negative aspects, and future developments. It notes that driverless cars can provide more efficient driving, help the elderly and disabled, manage traffic, and reduce accidents. Key components include sensors, artificial intelligence, and backup systems. While driverless cars may reduce accidents, concerns include credibility, security issues, inability to handle certain conditions, and job losses. The future adoption of autonomous vehicles is expected to grow significantly in the next few years across many auto manufacturers.
AUTO PILOT TECHNOLOGY IN VEHICLES
This presentation discusses auto pilot technology for vehicles. It introduces auto pilot technology as a way to enable self-driving vehicles that can steer, park and drive themselves on highways without human control. The key components that enable auto pilot include display units, radars, sensors and advanced GPS mapping systems. Radars detect objects up to 180 feet away while sensors monitor road conditions and angles to help the control unit navigate safely. Auto pilot technology aims to reduce accidents by taking over driving tasks but hackers changing routes and sensor failures present risks. The presentation concludes that fully implementing auto pilot could significantly reduce accidents and work towards an accident-free world.
Waymo ppt
Waymo is an autonomous vehicle company that was spun out of Google in 2016. It took over Google's self-driving car project which began in 2009. Waymo cars use LIDAR, radar, orientation sensors, wheel hub sensors and high-resolution maps to navigate without human input. The technology allows the cars to generate 3D maps of their environment to safely drive on roads. However, as of 2014 the cars could only navigate about 1% of US roads and had safety issues in heavy rain or snow. Waymo is working to address current limitations by 2020.
Advanced driver assistance systems
Advanced driver assistance systems are designed to increase car safety and road safety overall. They help the driver in the driving process to enable safe and relaxed driving. Some examples of driver assistance systems that maximize safety include antilock braking systems, adaptive cruise control, blind spot detection, driver drowsiness detection, electronic stability control, emergency braking systems, hill descent control, intelligent speed assistance, lane departure warning systems, pedestrian detection, rear cross traffic alert, and traffic sign recognition. These systems alert drivers to hazards, help maintain safe distances and speeds, and in some cases automatically apply brakes to avoid collisions.
Google self driving car technology
The Google driverless car is a project by Google that involves developing technology for autonomous cars.
The Google Driverless Car is like any car, but:
It can steer itself while looking out for obstacles.
It can accelerate itself to the correct speed limit.
It can stop and go itself based on any traffic
The software powering Google's cars is called Google Chauffeur.
It can take its passengers anywhere it wants to go safely, legally, and comfortably.
Currently being led by Sebastian Thrun ,former director of Stanford Artificial Intelligence Laboratory and co-inventor of Google’s Street View.
Best Driver less cars Ppt by-dinesh kumar from jaipur
The document discusses autonomous vehicles and their components. It provides an overview of the history and development of autonomous vehicles. It describes the various sensors like GPS, lidar, and radar that autonomous vehicles use to navigate environments and detect objects. It explains how autonomous vehicles work through components like sensors, navigation, motion planning and actuation. It discusses advantages like increased road capacity and safety, as well as potential disadvantages like security issues if the vehicle is hacked.
What's hot (20)
Autonomous car(driver less car) (self driving car)
Autonomous car(driver less car) (self driving car)
Best Driver less cars Ppt by-dinesh kumar from jaipur
Best Driver less cars Ppt by-dinesh kumar from jaipur
Viewers also liked
Google Self-Driving Car: A Long And Winding Road to Success
Google unveiled a brand new self-driving car prototype; the first company to build a car with no a steering wheel, accelerator or brake pedal.
Autonomous Vehicles
Autonomous vehicles use various sensors like ultrasonic sensors, RADAR, LIDAR, image sensors, GPS, and wheel speed sensors to navigate without human input. They rely on sensor integration and technologies like computer vision, V2X communication, and electronic control units to process sensor data. While self-driving cars offer benefits like safety and efficiency, there are also challenges to overcome like unpredictable humans, bad weather, and needing detailed digital maps. Fully autonomous vehicles may become common by 2040 if these issues can be addressed.
2016- A Year in Review of the Development of Autonomous vehicles
A lot has changed over the last 12 months in self-driving cars and driver assist technologies. Accidents, policies, and new developments in technology may make get these vehicles on roads near you sooner than previously estimated.
(The google car) Presentation
Google began developing self-driving car technology in 2009. Their self-driving cars use sensors like video cameras, radar, and laser rangefinders along with detailed maps to navigate roads without human intervention. The software processes sensor data in real-time to detect objects and safely maneuver the vehicle. Google's cars have driven over 200,000 miles with only one minor accident caused by a human driver. While self-driving cars could significantly reduce accidents, challenges remain regarding costs, regulations, and educating people.
NXP presentation at PLUS-Forum 2016
Presentation describes evolution of standards and use cases for contactless transactions - starting from MIFARE, followed by ISO14443, NFC and fast range of IoT application. Announcement of WILDCARD platform from http://tedipay.com/ and demonstration on 1st contactless transaction of MIR payment card on a wearable device.
How and When to apply for OPT - F1 Visa Students
International students after completing college degree in USA are eligible to apply for OPT - Optional Practical Training. Which will give them work authorization to work in USA.
There are various timeline and rules to be followed while applying for OPT. This presentation from Stanford University shows step by step process of how and when to apply for OPT.
Self driving cars.pptx
Self-driving cars can navigate without human input using sensors like radar and computer vision. Experiments with autonomous vehicles began in the 1920s, and the first truly self-driving car appeared in 1980. At CES this month, 10 exhibitors showcased self-driving technologies including Navya's electric shuttle bus and Rinspeed's luxury living room-inspired vehicle. Waymo has been developing self-driving systems since 2009 and has logged over 3 million autonomous miles. Ethical challenges for autonomous vehicles include how to program responses in emergency situations.
Leben 4.0: Künstliche Intelligenz und der Weg in die Datengesellschaft. Vortr...
Daten und Algorithmen bestimmen bereits heute schon unseren Alltag, oft ohne dass wir dies bemerken. Dieser Trend dürfte in der nahen Zukunft noch deutlich zunehmen. Die Digitalisierung des Menschen einerseits und der Einsatz Künstlicher Intelligenz andererseits werden unser Leben maßgeblich bestimmen und verändern. Werden Maschinen, Roboter und Computer die Oberhand gewinnen oder leiten sich daraus neue, nie dagewesene Chancen für den Menschen ab?
Self Driving Cars V11
This document provides an overview of self-driving cars, autonomous vehicles, and shared mobility. It discusses the major players in this emerging field such as Google, Tesla, Uber, and automotive manufacturers. The vision for autonomous vehicles is described as mobility over ownership where people will summon driverless vehicles via smartphone apps for on-demand transportation. Significant benefits include reduced traffic, increased road safety, and mobility for all groups. Currently, Google leads in developing fully autonomous vehicles while automakers focus on incremental self-driving features and plan to introduce them first in luxury models.
NVIDIA CES 2016 Highlights
At CES 2016, we made a series of announcements highlighting our work to advance the biggest trends in the industry — self-driving cars, artificial intelligence and
virtual reality. The focus of our news was NVIDIA DRIVE, an end-to-end deep learning platform for self-driving cars.
Autonomous or self driving cars
The document discusses several technologies expected to be implemented in autonomous vehicles by 2020, including vehicle-to-vehicle communication allowing cars to share information to avoid accidents, augmented reality windshields displaying information about surrounding locations, energy-storing body panels to improve battery efficiency, and personalized presets tailored to individual drivers. While autonomous vehicles may reduce accidents and traffic and increase accessibility, challenges include liability issues, reluctance to give up control, software reliability, and the need to establish legal frameworks for regulation. Public opinion surveys show growing acceptance of self-driving car technology, with some major automakers expecting to offer fully autonomous vehicles by 2020.
NVIDIA CES 2016 Press Conference
At a press event kicking off CES 2016, we unveiled artificial intelligence technology that will let cars sense the world around them and pilot a safe route forward.
Dressed in his trademark black leather jacket, speaking to a crowd of some 400 automakers, media and analysts, NVIDIA CEO Jen-Hsun Huang revealed DRIVE PX 2, an automotive supercomputing platform that processes 24 trillion deep learning operations a second. That’s 10 times the performance of the first-generation DRIVE PX, now being used by more than 50 companies in the automotive world.
The new DRIVE PX 2 delivers 8 teraflops of processing power. It has the processing power of 150 MacBook Pros. And it’s the size of a lunchbox in contrast to other autonomous-driving technology being used today, which takes up the entire trunk of a mid-sized sedan.
“Self-driving cars will revolutionize society,” Huang said at the beginning of his talk. “And NVIDIA’s vision is to enable them.”
Google self driving car technology
The Google driverless car project involves developing technology for autonomous vehicles. The Google cars can steer, accelerate, brake and obey traffic laws without human input using sensors and software. Over 1 million miles have been driven accident-free. While driverless cars promise benefits like increased safety, traffic and environmental issues remain regarding regulations, liability, public acceptance, and infrastructure changes needed for full adoption of the technology.
Future Retail - Wie die digitale Revolution den Handel verändert
Future Retail - Wie sieht die Zukunft des stationären Handels aus? In meiner Keynote auf dem 22. IHK-Stadtmarketingforum geht es um den richtigen Umgang mit den üblichen Zukunftsprognosen zwischen "Verödung der Innenstädte" bis zum "Das geht auch wieder vorbei" und eine differenzierte Perspektive.
Beispiele in den Charts beschäftigen sich u.a. mit:
#Social Robots
#Mobile Commerce
#Amazon Prime
#Social Commerce
und vor allem die Rolle von Erlebnissen für die Zukunftsperspektiven des Handels.
Google Driverless Car
The document discusses Google's driverless car project. It describes how the car can steer, accelerate, and stop itself using sensors like LIDAR and cameras to detect obstacles and traffic conditions. The car's artificial intelligence analyzes data from Google Maps and sensors to determine how to drive safely. As of 2012, Google had 6 driverless cars that had traveled over 140,000 miles on public roads in Nevada with only occasional human intervention needed. Benefits include reduced accidents, easier traffic management, and increased road capacity. Potential risks include hacking and sensor failures.
Driving Disrupted: Driverless Cars Change Everything
The autonomous vehicle, driverless or self-driving car will be one of the greatest technological developments of the next decade (if not all time).
It will profoundly change life on earth.
For the past century our car-centric culture has shaped infrastructure and ideals, landscape and lifestyle, ethics and enterprise. We rely on the mobility that cars provide us more than ever, but the car’s purpose and meaning changes as the driver fades out.
When the car drives itself, what we do in our cars and with our cars is exponentially different. When the car is intelligent, intuitive and adaptive, our relationship to the car alters. When the car builds itself, environments and economies are reshaped.
This report looks at the players, technologies and trends in the autonomous vehicle space and paints a picture of probable futures for citizens, businesses and marketers.
Buckle up. Bumpy roads ahead.
Viewers also liked (18)
Google Self-Driving Car: A Long And Winding Road to Success
Google Self-Driving Car: A Long And Winding Road to Success
Wirtschaftlichkeitsberechnung von RFID-Projekten mit RFID-Cab
Wirtschaftlichkeitsberechnung von RFID-Projekten mit RFID-Cab
2016- A Year in Review of the Development of Autonomous vehicles
2016- A Year in Review of the Development of Autonomous vehicles
Leben 4.0: Künstliche Intelligenz und der Weg in die Datengesellschaft. Vortr...
Leben 4.0: Künstliche Intelligenz und der Weg in die Datengesellschaft. Vortr...
Future Retail - Wie die digitale Revolution den Handel verändert
Future Retail - Wie die digitale Revolution den Handel verändert
Driving Disrupted: Driverless Cars Change Everything
Driving Disrupted: Driverless Cars Change Everything
Similar to Google Self Driving Car System
Googlecar 150915202230-lva1-app6892
This document discusses Google's driverless car technology. It describes the key components of Google's driverless cars, including Lidar, radar, cameras, and ultrasonic sensors that allow the cars to navigate roads autonomously. The document also outlines some of the major challenges facing driverless car technology, such as difficulties operating in heavy rain or differentiating between objects. The goal of Google's driverless car is to reduce accidents caused by human error by developing fully autonomous vehicles.
Google Driverless Car Final
The document discusses Google's driverless car project, including its history starting in 2009, the key components like sensors and artificial intelligence that allow it to drive autonomously, and some of the technologies that enable functions like cruise control, parking assistance and collision avoidance. It provides details on how the car uses sensors and AI to navigate roads safely and get passengers to their destinations, as well as potential advantages like increased road capacity and safety and disadvantages around security issues.
GOOGLE DRIVERLESS CAR
From the invention of the car there is a great relation between human and car. Because by the invention of the car the automobile industry was established, by this car the traveling time from one place to another place is reduced. The car brings royalty from the invention. As cars are coming on roads at that time there are so many accidents are occurring due to lack of driving knowledge & drink driving and soon, In that view only the Google took a great project, i.e. Google Driverless Car in these the Google puts the technology in the car, that technology was Artificial Intelligence with Google map view. The input video camera was fixed beside the front mirror inside the car, A LIDAR sensor was fixed on the top of the vehicle, RADAR sensor on the front of the vehicle and a position sensor attached to one of the rear wheels that helps locate the cars position on the map, The Computer, Router, Switch, Fan, Inverter, rear Monitor, Topcon, Velodyne, Applanix and Battery are kept inside the car.
These all components are connected to computer’s CPU and the monitor is fixed on beside of the driver seat, these we can observe in that monitor and can operate all the operations.
Google driver less car presentation (ppt) 2017 Hemant pratap singh
The document discusses autonomous vehicles and provides their history and components. It notes that autonomous vehicles can drive themselves from one point to another with driver assistance. The first license for an autonomous vehicle was issued in 2012 to a modified Toyota Prius. Autonomous vehicles use sensors like radar, LIDAR, cameras and GPS along with artificial intelligence to navigate roads safely without human intervention. While they can increase road capacity and help people with disabilities, challenges include potential job losses for drivers and security issues if the systems are hacked.
Tendencias: Cómo nos va a afectar el Internet de las cosas - Self Driving Car...
Tendencias: Cómo nos va a afectar el Internet de las cosas - Self Driving Car...Ditrendia - Digital Marketing Trends
Ponencia de D. Miguel Cruz, Director Marketing y Estrategia Clientes, REALE - Tendencias: Cómo nos va a afectar el Internet de las cosas - Self Driving Car in the Insurance market - en el 11º Foro Profesional de Marketing y Ventas para Entidades Financieras y Aseguradoras #MKTefa organizado por ditrendia Autonomouscar
The document provides an overview of driverless or autonomous vehicles. It discusses the history and components of these vehicles, including sensors like LIDAR, radar and cameras. The document explains how artificial intelligence analyzes sensor data to navigate autonomously. Potential advantages are reduced accidents and increased road capacity, while obstacles include handling various weather conditions and temporary construction zones. Several companies aim to release autonomous vehicle technologies between 2014 and 2020.
Autonomous car presentation
autonomous car, self driving car, presentation on google driving car, sensor used in car , future car, four wheeler car , colloquium, mechanical engineering, engineering technology ,b.tech, automotive engineering, california based car, self control car
Google self Driving Car
This document presents information on Google's self-driving car project. It discusses the various technologies used in the car, such as laser range finders, front cameras, radar sensors, and ultrasonic sensors to detect surroundings. It explains how the car uses sensors to detect traffic lights and navigate roads autonomously. The advantages are increased safety and efficiency, while the disadvantages include high costs and potential job losses for drivers. In conclusion, the technology could significantly change transportation if challenges are addressed.
Datacommunication presentation
The document discusses self-driving cars, including their history beginning with Google's driverless car project led by 15 engineers. It describes the vehicular hardware used such as radar, video cameras, LIDAR, GPS, and processors. The hardware collects sensor data that is processed by AI to determine how the car should accelerate, brake, and steer to safely reach the destination. While self-driving cars may provide benefits, challenges remain around handling heavy weather and differentiating objects. The document predicts autonomous vehicles could be ready for market in 4-5 years.
Smart automotive solutions-Faststream Technologies
The Faststream Technologies Smart Automotive Solution is enabled with IoT platform. The Connected Vehicle Solution aims to help the digital transformation of car manufacturers. To create the Connected Vehicle, Automobile manufacturing companies, telecommunication service providers and Faststream Technologies are working together. We’ve leveraged our mobile and compute platforms to support automotive trends in telematics, infotainment, ADAS, and cloud management mobile solutions. The Connected car services and applications along with our IoT solutions in the Automotive sector are presented here.
Oner gps tracker catalog
The document provides contact and company information for Jia Decoration Materials, a GPS tracker manufacturer located in Guangzhou, China. It includes the company address, websites, phone/fax numbers, and describes their mission to provide real-time tracking products and solutions to over 100 countries. The company has over 11 years of experience in the industry and produces a line of GPS trackers that help with issues like fleet management, safety monitoring, and speed limitation.
Satish prasad_presentation on hybrid cars
The document discusses the features and technologies of hybrid cars. Hybrid cars can use vision systems to detect other vehicles, traffic signals, pedestrians and obstacles. They can also monitor the driver's physiology, road and weather conditions. Key features of hybrid cars mentioned include collision avoidance, adaptive cruise control, imaging technologies and navigational aids that provide safety and convenience. The document outlines some challenges in further developing and adopting intelligent vehicle systems and envisions future vehicles having improved in-vehicle systems and communication abilities.
Satish prasad bangalore india_satmd410
The document discusses the features and technologies of hybrid cars. Hybrid cars can use vision systems to detect other vehicles, traffic signals, pedestrians and obstacles. They can also monitor the driver's physiology, road and weather conditions. Key features include collision avoidance systems, adaptive cruise control, imaging technologies and navigation aids to improve safety. The hybrid cars of the future are expected to have more advanced autonomous capabilities and communication between vehicles and infrastructure to further reduce accidents.
Autonomous_car_self_driving_cars_upload.ppt
This presentation provides an overview of autonomous vehicles. It defines autonomous vehicles as vehicles capable of sensing their environment and navigating without human assistance. The presentation then briefly discusses the history of autonomous vehicle experiments dating back to the 1920s. It outlines the five levels of vehicle automation from no automation to full automation. The key sensors and systems that enable autonomous vehicles are described, including LIDAR, radar, cameras, sonar and GPS/software. Potential advantages like safety and mobility benefits are highlighted, along with challenges like technology limitations and consumer acceptance. The conclusion is that autonomous vehicles may revolutionize transportation if deployed safely at scale.
Telsa auto pilot
Tesla Autopilot is an advanced driver-assistance system feature offered by Tesla .That has lane centring, adaptive cruise control, self-parking, ability to automatically change lanes without requiring driver steering, and enables the car to be summoned to and from a garage or parking spot.
Sazz
The document discusses autonomous or self-driving cars. It describes how autonomous cars use sensors like LIDAR, radar, cameras and ultrasonic sensors along with GPS and an inertial measurement unit to navigate without human intervention. The central computer combines data from these sensors to construct a 3D map of the vehicle's surroundings and control systems like steering and braking. Major companies developing autonomous vehicle technology include Google, Audi, BMW, Ford and General Motors.
autonomous_car From VNS Institute of technology Bhopal
The document presents information on autonomous vehicles. It begins with definitions of autonomous cars and a brief history of experiments dating back to the 1920s. It then describes how autonomous cars work using sensors like LIDAR, radar, cameras and GPS to navigate environments. The major hurdles to autonomous vehicles are also outlined, such as technology, regulations, and consumer acceptance. Potential advantages include safety and increased road capacity, while disadvantages include costs, job losses, and reliance on technology. In conclusion, autonomous vehicles may revolutionize transportation but challenges remain regarding their adoption.
Driverless car
Driver error is the leading cause of traffic accidents. Technologies like anti-lock brakes, electronic stability control, and automatic emergency braking are enabling fully autonomous vehicles. Driverless cars use sensors to detect traffic lights and stay in the proper lane. While autonomous vehicles promise safety benefits and increased road capacity, issues around hacking, sensor failures, and job disruption remain challenges. Overall, computer control of vehicles could help minimize accidents by reducing human error.
Driverless car
Driverless vehicles use sensors, navigation, motion planning, and actuation to operate without human assistance. Sensors like cameras and lasers detect surroundings, navigation software guides the vehicle along a plotted route, motion planning algorithms determine safe movements around other objects, and actuation systems like brakes and steering execute the vehicle's movements. While the technology provides benefits like safety and increased road capacity, security issues around hacking pose risks if not properly addressed.
Similar to Google Self Driving Car System (20)
Google driver less car presentation (ppt) 2017 Hemant pratap singh
Google driver less car presentation (ppt) 2017 Hemant pratap singh
Tendencias: Cómo nos va a afectar el Internet de las cosas - Self Driving Car...
Tendencias: Cómo nos va a afectar el Internet de las cosas - Self Driving Car...
Smart automotive solutions-Faststream Technologies
Smart automotive solutions-Faststream Technologies
autonomous_car From VNS Institute of technology Bhopal
autonomous_car From VNS Institute of technology Bhopal
Recently uploaded
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
Digital Marketing Trends in 2024 | Guide for Staying Ahead
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays, June 2024 with Maria Copot 20
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
OpenID AuthZEN Interop Read Out - Authorization
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Webinar: Designing a schema for a Data Warehouse
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Project Management Semester Long Project - Acuity
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Recently uploaded (20)
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
Google Self Driving Car System
- 2. Google self driving car technology Google
- 3. TECHNOLOGY USED So what powers these driverless cars? Let’s take a look at 10 awesome technologies making this happen.
- 4. 1. LASER RANGE FINDER
- 5. A camera mounted on the windshield takes care of helping the car ‘see’ objects right in front of it. These include the usual suspects- pedestrians, and other motorists. This camera also detects and records information about road signs and traffic lights, which is intelligently interpreted by the car’s in built software.
- 6. 4 radars mounted on the car’s front and rear bumpers enable the car to be aware of vehicles in front of it and behind it. Most of us are familiar with this technology as it is the same as the adaptive cruise control systems our cars are based. The radar sensor on the car’s bumpers keeps a ‘digital eye’ on the car ahead. The software is programmed to (at all times) maintain a distance of 2-4 seconds (it could even be higher) vis-a-vis the car ahead of it. So with this technology the car will automatically speed up or slow down depending on the behaviour of the car/driver ahead.
- 7. 4.AERIAL THAT READS PRECISE GEO-LOCATION An aerial on the rear of the car receives information about the precise location of the car, thanks to GPS satellites. The car’s GPS inertial navigation unit works with the sensors to help the car ocalise itself. But GPS estimates may be off by several metres due to signal disturbances and other interferences from the atmosphere