The document describes a proposed heads-up display project that would show real-time navigation and traffic conditions on a car's windshield. It would use a transparent OLED display mounted on the windshield and connected wirelessly to the internet. A camera mounted on the front of the car would take real-time images that a processor would analyze to display navigation directions, speed limits, and the speed of vehicles ahead, helping to prevent accidents. The display technology allows it to take the shape of the windshield and is more efficient than LED or LCD displays.
The head-up display (HUD) creates a new form of presenting information by enabling a user to simultaneously view a real scene and superimposed information without large movements of the head or eye scans.
This project represents a way of developing an
interface to detect driver drowsiness based on continuously
monitoring eyes and DIP algorithms. Micro sleeps that are short
period of sleeps lasting 2 to 3 seconds are good indicator of
fatigue state. Thus by continuously monitoring the eyes of the
driver by using camera one can detect the sleepy state of driver
and timely warning is issued.
Aim of the project is to develop the hardware which is very
advanced product related to driver safety on the roads using
controller and image processing. This product detects driver
drowsiness and gives warning in form of alarm and as well as
decreases the speed of vehicle.Along with the drowsiness
detection process there is continuous monitoring of the distance
done by the Ultrasonic sensor. The ultrasonic sensor detects the
obstacle and accordingly warns the driver as well as decreases
speed of vehicle.
Google Self Driving Cars
The Google Self-Driving Car is a project by Google that involves developing technology for autonomous cars. The software powering Google's cars is called Google Chauffeur. Lettering on the side of each car identifies it as a "self-driving car". The project is currently being led by Google engineer Sebastian Thrun, former director of the Stanford Artificial Intelligence Laboratory and co-inventor of Google Street View. Thrun's team at Stanford created the robotic vehicle Stanley which won the 2005 DARPA Grand Challenge and its US$2 million prize from the United States Department of Defense. The team developing the system consisted of 15 engineers working for Google, including Chris Urmson, Mike Montemerlo, and Anthony Levandowski who had worked on the DARPA Grand and Urban Challenges.
Legislation has been passed in four states and the District of Columbia allowing driverless cars. The U.S. state of Nevada passed a law on June 29, 2011, permitting the operation of autonomous cars in Nevada, after Google had been lobbying in that state for robotic car laws. The Nevada law went into effect on March 1, 2012, and the Nevada Department of Motor Vehicles issued the first license for an autonomous car in May 2012, to a Toyota Prius modified with Google's experimental driverless technology. In April 2012, Florida became the second state to allow the testing of autonomous cars on public roads, and California became the third when Governor Jerry Brown signed the bill into law at Google HQ in Mountain View. In July 2014, the city of Coeur d'Alene, Idaho adopted a robotics ordinance that includes provisions to allow for self-driving cars.
Videos
https://www.youtube.com/channel/UCCLyNDhxwpqNe3UeEmGHl8g
The head-up display (HUD) creates a new form of presenting information by enabling a user to simultaneously view a real scene and superimposed information without large movements of the head or eye scans.
This project represents a way of developing an
interface to detect driver drowsiness based on continuously
monitoring eyes and DIP algorithms. Micro sleeps that are short
period of sleeps lasting 2 to 3 seconds are good indicator of
fatigue state. Thus by continuously monitoring the eyes of the
driver by using camera one can detect the sleepy state of driver
and timely warning is issued.
Aim of the project is to develop the hardware which is very
advanced product related to driver safety on the roads using
controller and image processing. This product detects driver
drowsiness and gives warning in form of alarm and as well as
decreases the speed of vehicle.Along with the drowsiness
detection process there is continuous monitoring of the distance
done by the Ultrasonic sensor. The ultrasonic sensor detects the
obstacle and accordingly warns the driver as well as decreases
speed of vehicle.
Google Self Driving Cars
The Google Self-Driving Car is a project by Google that involves developing technology for autonomous cars. The software powering Google's cars is called Google Chauffeur. Lettering on the side of each car identifies it as a "self-driving car". The project is currently being led by Google engineer Sebastian Thrun, former director of the Stanford Artificial Intelligence Laboratory and co-inventor of Google Street View. Thrun's team at Stanford created the robotic vehicle Stanley which won the 2005 DARPA Grand Challenge and its US$2 million prize from the United States Department of Defense. The team developing the system consisted of 15 engineers working for Google, including Chris Urmson, Mike Montemerlo, and Anthony Levandowski who had worked on the DARPA Grand and Urban Challenges.
Legislation has been passed in four states and the District of Columbia allowing driverless cars. The U.S. state of Nevada passed a law on June 29, 2011, permitting the operation of autonomous cars in Nevada, after Google had been lobbying in that state for robotic car laws. The Nevada law went into effect on March 1, 2012, and the Nevada Department of Motor Vehicles issued the first license for an autonomous car in May 2012, to a Toyota Prius modified with Google's experimental driverless technology. In April 2012, Florida became the second state to allow the testing of autonomous cars on public roads, and California became the third when Governor Jerry Brown signed the bill into law at Google HQ in Mountain View. In July 2014, the city of Coeur d'Alene, Idaho adopted a robotics ordinance that includes provisions to allow for self-driving cars.
Videos
https://www.youtube.com/channel/UCCLyNDhxwpqNe3UeEmGHl8g
the recent trends in embedded systems in automobiles and also about the basic bus of communication have been given space, and for better understanding of BUS channel,i had compared BUS to MINIMILITIA , where we play it in a hotspot network (a channel of communication to communicate among diff palyers in the same game ) similar to a BUS
and at the end a fabulous drawing distinguishing about the present days automobiles
After decades of anticipation, practical self-driving cars are here. Drive.ai will deploy a self-driving car service for public use in Texas starting in July.
We can continue pushing self-driving forward by focusing on three key elements: industry-leading AI technology, local partnerships, and people-centric safety.
An autonomous car is a vehicle capable of sensing its environment and operating without human involvement. A human passenger is not required to take control of the vehicle at any time, nor is a human passenger required to be present in the vehicle at all. An autonomous car can go anywhere traditional cargoes and do everything that an experienced human driver does.
The Society of Automotive Engineers (SAE) currently defines 6 levels of driving automation ranging from Level 0 (fully manual) to Level 5 (fully autonomous). These levels have been adopted by the U.S. Department of Transportation.
Autonomous vs. Automated vs. Self-Driving: What’s the difference?
The SAE uses the term automated instead of autonomous. One reason is that the word autonomy has implications beyond the electromechanical. A fully autonomous car would be self-aware and capable of making its own choices. For example, you say “drive me to work” but the car decides to take you to the beach instead. A fully automated car, however, would follow orders and then drive itself.
The term self-driving is often used interchangeably with autonomy. However, it’s a slightly different thing. A self-driving car can drive itself in some or even all situations, but a human passenger must always be present and ready to take control. Self-driving cars would fall under Level 3 (conditional driving automation) or Level 4 (high driving automation). They are subject to geofencing, unlike a fully autonomous Level 5 car that could go anywhere.
it is a presentation based on image processing used in the field of fatigue detection while driving which can save many life as well as prevent accident.
This was a short talk exploring some newer studies in HUD design. It is a basic overview of different types of HUD, player types and some principles of game design.
the recent trends in embedded systems in automobiles and also about the basic bus of communication have been given space, and for better understanding of BUS channel,i had compared BUS to MINIMILITIA , where we play it in a hotspot network (a channel of communication to communicate among diff palyers in the same game ) similar to a BUS
and at the end a fabulous drawing distinguishing about the present days automobiles
After decades of anticipation, practical self-driving cars are here. Drive.ai will deploy a self-driving car service for public use in Texas starting in July.
We can continue pushing self-driving forward by focusing on three key elements: industry-leading AI technology, local partnerships, and people-centric safety.
An autonomous car is a vehicle capable of sensing its environment and operating without human involvement. A human passenger is not required to take control of the vehicle at any time, nor is a human passenger required to be present in the vehicle at all. An autonomous car can go anywhere traditional cargoes and do everything that an experienced human driver does.
The Society of Automotive Engineers (SAE) currently defines 6 levels of driving automation ranging from Level 0 (fully manual) to Level 5 (fully autonomous). These levels have been adopted by the U.S. Department of Transportation.
Autonomous vs. Automated vs. Self-Driving: What’s the difference?
The SAE uses the term automated instead of autonomous. One reason is that the word autonomy has implications beyond the electromechanical. A fully autonomous car would be self-aware and capable of making its own choices. For example, you say “drive me to work” but the car decides to take you to the beach instead. A fully automated car, however, would follow orders and then drive itself.
The term self-driving is often used interchangeably with autonomy. However, it’s a slightly different thing. A self-driving car can drive itself in some or even all situations, but a human passenger must always be present and ready to take control. Self-driving cars would fall under Level 3 (conditional driving automation) or Level 4 (high driving automation). They are subject to geofencing, unlike a fully autonomous Level 5 car that could go anywhere.
it is a presentation based on image processing used in the field of fatigue detection while driving which can save many life as well as prevent accident.
This was a short talk exploring some newer studies in HUD design. It is a basic overview of different types of HUD, player types and some principles of game design.
Modern advances in car technology have come a long way. A Head-up Display, or HUD, first appeared in military aircraft. Around 1994, I played a flight combat simulator named Strike Commander. It allowed flying F-16s in mercenary fashion.
Blue LED as we all know is the discovery of the century. Its applications spans most of our needs in day to day life and it is one of the greatest innovations in the history of mankind for which it was given nobel.
Cambridge Realty Capital Companies presents:
HUD 232 LEAN Financing – A Primer
HUD Nursing Home and Assisted Living
Financing…Answers To All Your
Questions…And Many Questions You Never
Thought To Ask!
The term hyper car has been used to describe the highest-performing supercars. This presentation attributes some characteristics of hyper cars, the concept behind it in details and some extra features that improve vehicle efficiency and performance. Also find out which type of fuel it uses and some of its safety features. Let’s have a look.
Acknowledgement
Introduction
What Is A Self-driving Car?
Reason Behind The Making?
Self-driving Car Technology: How Do Driverless Cars Work?
How Fast Is 5G?
Basic Physical Ecosystem Of An Autonomous Vehicle
Key Components Of Self-driving Vehicles
Impacts Of Self-driving Vehicles
Potential Concerns
Major Applications
Conclusion
References
New tools and resources for io t development from prototype to productionIntel® Software
Explore how IoT can improve the current driving experience, this includes anti-snoozer, smarter bumper sticker, vehicle rare vision and other tools which can be added to make cars safer and smarter until self-driving car arrives.
NVIDIA Testimony at Senate Commerce, Science, and Transportation Committee He...NVIDIA
Rob Csongor, VP and General Manager of NVIDIA's automotive business, provides his testimony on the important subject of self-driving vehicle technology.
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.
In this presentation, Ankit introduces SMAC and associated trends. Ankit's interest area lies in Big Data Analysis which he wants to in interesting applications in the healthcare space, one of the interesting examples he suggests is to find the correlation between treatment and cure.
In this presentation, Sumit introduces IoT and associated trends. Sumit's interest area lies in enabking physical-digital communication that is independent of physical location
In this presentation, Pawan discusses approaches for home automation and smart grid. His interest areas lie in implementing cloud server systems to monitor appliances and providing security for the same.
In this presentation, Ayush introduces IoT and associated trends. Ayush wants to work on the standardization part of IoT and as an example he talks about Constrained Application Protocol (CoAP).
In this presentation, Sairaju introduces SMAC and associated trends. Sai is currently working on a project on encryption of data in cloud and his interest area is in the related field of securing cloud infrastructure.
In this presentation, Melissa introduces IoT and associated trends. In Melissa's own words, "I would like to work on networking related to Ipv6 and designing network architecture for IPv6 and IPv6 Dual Stack for Broadband Edge"
In this presentation, Kushagra introduces IoT and associated trends. Kushagra wants to use his programming and mobile application development skills to intgrate AI to IoT and develop healthcare applications.
In this presentation, Shivani introduces IoT and associated trends. Shivani describes what seems like a very interesting future to have with mobile as the gateway to a smart home.
In this presentation, Sravani introduces SMAC and associated trends. Having already developed mobile applications using IBM’s BlueMix, Sravani's interest areas lie in the same domain along with Big Data Analytics.
In this presentation, Prateek introduces what he calls "Internet of Everything" and talks about building IoT applications that aid in water/energy conservation.
In this presentation, Sushmitha introduces IoT and associated trends. Sushmitha is interested in cloud computing which is one of the enablers of IoT. She also talks about fog computing which uses challenge questions for access control.
In this presentation, Surbhi introduces IoT and associated trends. Surbhi is interested in IoT applications in the health monitoring space where health is monitored real time using sensors and data is transmitted to doctors.
In this presentation, Vijaya introduces IoT and associated trends. Vijaya is interested in sensors and their applications in the home automation space.
In this presentation, Smriti introduces IoT and associated trends. Smriti talks about an innovative ides that uses IoT services and cloud application to check the health of laptop and automates messages to both the service centres and the owner.
In this presentation, Praneeth introduces IoT and associated trends. Praneeth is interested in IoT applications in home automation space and he also has several ideas WRT to water management and transport management using IoT applications.
In this presentation, Harmish introduces SMAC and associated trends. Harmish is interested in enterprise mobile applications where his focus area is the user experience.
In this presentation, Anil introduces automation and associated trends. Having attended workshops in automation testing space, his interest area lies in that domain.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
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Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 4
Heads Up Display : A smart navigation system
1.
2. Introduction
Internet of things :
A lot of connected devices working together
without the interruption of human. Like home
automation where the user in summers need not
switch on ac manually when he arrives home it will be
switched on as soon as he opens the door.
My project : Heads up display
A display connected wirelessly to the internet
showing navigation and traffic conditions on the
windshield of a car in real time while driving.
4. Heads Up Display
We have transparent
oled based display which
shows the real time
navigation and with
speed limits and speed
of the car ahead.
There is camera which
will be mounted on
front of the car which
will take images and
processor will process
them in real time and
the final display in
shown on the display of
the windshield.
5. Transparent OLED
The substrate is transparent.
When its off its up to 85
percent transparent. The oled
technology helps us to make
the display take the shape of
the windshield. Its transparent
behavior makes it he best
choice for the project.
Also it is environment friendly
and most efficient than LEDs
and LCDs. It has efficiency max
up to 131lm/W. Which makes it
a low powered device.
6. Trends
Skully an intelligent helmet making company is
making smart helmets for riders. It was founded in
2013. But it has major drawbacks which didn’t make it a
big success.
8. Difference that I would like to make it that, through
real time image processing technique we not only give
the user a proper direction to travel but also optimize
the travel by letting the driver know the speed of the
vehicle in front of it. Also give the user notification of
his speed with fuel indication.
The new display will prevent the accidents which is a
big case in my country. Many people face accidents
and some even loose their life. This display will help
prevent such cases. Also in case of some fault or
accident the Module will notify the nearby hospital
and send an SMS through GSM module to the relatives
of the driver.
Helping the driver get maximum service needed.
9. Interest Areas
My interest areas are intelligent navigation system, IoT, Smart
Cars etc.
After the accident of my parents, I’m working hard regularly to
make projects to prevent such things in future to anyone.
Accidents are most unavoidable and uncontrolled thing that
happens mostly because of the blind spot of the driver or the
unawareness of the driver. This display will prevent such thing to
happen in future.
I’m an electronic enthusiast working hard in the field of digital
electronics.
10. If I have been provided internship in this area I would
like to work on image processing, real time operating
system, working with API’s of GPS navigation (like
here maps and google maps) and also on OLED
display.
I would like to work on Intel Atom Processor (Intel
Galileo Board) with Wifi shield and an OLED display.
11. I have also participated in the Intel Embedded Design
challenge 2014 in the field of IoT and have qualified
till the semi finals.
I have experience on working with Arduino, ARM
processors, Atmel’s AVR, Cypress’s PSoC board and
Xilinx Spartan 3E FPGA board.