The aim of this project is to try and solve, improve, reduce and hopefully eliminate all accidents on the road due to driver drowsiness. Drowsy driving is a major problem all around the world. The risk, danger, and often tragic results of drowsy driving are alarming and increasing. Drowsy driving is the dangerous combination of driving and sleepiness or fatigue. This usually happens when a driver has not slept enough, but it can also happen due to untreated sleep disorders, medications, consumption of alcohol, or working the late shift at work. This problem at hand has claimed many innocent lives including children. The aim of creating this project is to be able to track driver drowsiness and hopefully prevent and drowsy drivers from driving and thus reduce the rate of accidents due to drowsy driving.
Driver drowsiness detection is a type of vehicle safety technology which can help in preventing accidents caused by the driver getting drowsy. There has been various studies that have suggested that around 20% of all road accidents are fatigue-related and up to 50% on certain types of roads such as unfamiliar roads, long stretches of highway. Our aim of this project is to hopefully try and solve, improve, reduce and hopefully eliminate all accidents on the road due to driver drowsiness. Fatigue and microsleep at the wheel are often the cause of serious accidents. However, the initial signs of fatigue can be detected before a critical situation arises. Although such technology has already existed in higher-end vehicles for the past few years, we aim to improve on this existing technology with the help of Artificial Intelligence and Machine Learning. The capabilities are endless with the help of Artificial Intelligence.
Vision: Drive Safe, Live Safe
Mission: To Accelerate the World to a Safer Future
The issue arises from one simple factor, which is, human error. In this modern and technologically sophisticated and advanced world, the usual error that persist is human error. As mentioned above, various studies that have suggested that around 20% of all road accidents are fatigue-related and up to 50% on certain types of roads such as unfamiliar roads, long stretches of highway. Drivers who are more likely to get drowsy behind the wheel are as such:
As it is very obvious that the main problem is due to human error, the aim of this project is to hopefully preventing accidents caused by the driver getting drowsy with the implementation of Artificial Intelligence and Machine Learning.
With the help of our proposed idea, we can hopefully reduce and eventually eliminate road accidents caused by the driver getting drowsy. As our Vision states, when a driver drives safe, it means that they will live a longer and safer life. Our Mission is to accelerate the technology of Driver Drowsiness Detection into the future with the help of Artificial Intelligence.
The application approach of our project is to look at an old problem in a new way. We aim to take an existing and deadly problem and draw up a new angle of attack to tackle the problem. We aim to use warning signs of drowsy driving to reduce the risk of accidents such as:
These are the few main factors we will be taking into consideration when creating this project.
This project is completely reliant on existing technologies such as facial recognition, satellite navigation, lane keep assist technology and steering-angle sensor found in modern vehicles and more. There has been several reputable companies that have implemented similar solutions as stated above but we aim to strive on their shortcomings and aim to perfect the system of Driver Drowsiness Detection.
Driver Condition Monitor and Driver Fatigue Alert will both be evaluated to detect for signs of driver fatigue. When the feature detects and determines that the driver is fatigued and getting drowsy, the message center on the dashboard will display a warning, TAKE A BREAK!, for 1 minute, accompanied by an audible chime with an icon on the message center that flashes amber to get the drivers attention. When driving continues for more than 15 minutes after the first warning has been chimed and without taking a break, a second warning is given, this time with a louder and more attentive chime. The warning will continue until the driver gives a physical input to stop the chime by pressing the OK button on the steering wheel menu control. This system is also linked to the vehicle’s navigation system, and by using that data, it can tell the driver where the next rest stop is located.
It can be said that the use of the artificial intelligence can be most efficient technology that can be used in order to enhance the process of driving. The artificial intelligence can easily access and properly analyse the informations of the drivers [3]. Also, as the technology now is a readily available, hence it can be said that the use of the technology is one of the most economically viable things that can be implemented. The use of the AI can mostly help in the sectors that directly use the data generated by the customers.
It can be said that although the use of the artificial intelligence in the present time is not a tough thing to find, using this in this concept is something new that is to be implemented. The use of the AI can be found in every sector of the world [5]. The AI systems are been used by many of the firms like the Google, Facebook and other organisation for the process of enhancing the technology they are using. It can be said that the use of Artificial Intelligence can be implemented in each and every sector of the world in the coming future.
The use of the AI for the process of implementing and ensuring proper driving conditions for a diver. The design that is presented in the paper can be said that it is using the logical chunks. Logical chunking can be explained as an approach which uses the effective use of the short-term memory by grouping information [1]. That is, it is breaking down the long strings of information into smaller chunks. In this case, it is using the information of the drivers’ actions in a fixed interval of time and producing results accordingly. When the driver is not in action, it uses the previous responses of the driver analyses the same and provides a result. When driving, continues for more than 15 minutes after the first warning has been chimed without taking a break, a second warning is given, this time with a louder and more attentive chime [4]. The warning continues until the driver gives a physical input to stop the chime by pressing the OK button on the steering wheel menu control. Thus it can be said that it is using short-term results for the process of analysing information.
Yes, the project is open and can be used for the process of the evolution. The process that is explained in the paper can be used for designing the process. Further, development can be easily done with the help of using the API and other systems [6]. This system can also be developed for other modes of the transports if developed in a proper manner.
In the process of developing, the monolithic application defines the single-tiered software in which the user interface and data access code are combined into a single program from a single platform [2]. Thus, it can be said the software can not only run using the API and it can download the SDKs or the user can enable it as and on when required. The system uses the software for the process of enhancing the process of development of the artificial intelligence.
In order to run this system in a proper manner, a huge number of modern technologies have been used. Initially, the major hardware components that are used are a camera, sensors, wireless chips and others. While in the software part the major concepts of the big data analytics, machine learning and programming languages like python [1]. In order to properly develop the solution, there are a number of modern technologies that have been used. All these technologies are used in order to develop the solution.
The system can be developed in the sectors like the automobile industry. AS the application is specifically designed for the drivers while they are driving hence the solution must be deployed in this platform only. This is the major platform can help in the process of enhancing the driving of the customers [3]. The aim of this project is to hopefully try and solve, improve, reduce and hopefully eliminate all accidents on the road due to driver drowsiness.
References
[1] Russell, Stuart J., and Peter Norvig. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited, 2016.
[2] Nilsson, Nils J. Principles of artificial intelligence. Morgan Kaufmann, 2014.
[3] Wenger, Etienne. Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. Morgan Kaufmann, 2014.
[4] Bond, Alan H., and Les Gasser, eds. Readings in distributed artificial intelligence. Morgan Kaufmann, 2014.
[5] Hutter, Frank, Lin Xu, Holger H. Hoos, and Kevin Leyton-Brown. “Algorithm runtime prediction: Methods & evaluation.” Artificial Intelligence 206 (2014): 79-111.
[6] Charniak, Eugene, Christopher K. Riesbeck, Drew V. McDermott, and James R. Meehan. Artificial intelligence programming. Psychology Press, 2014.
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