अब लेट नहीं होगी एंबुलेंस: छात्रों ने बनाया AI मॉडल, ऑटोमैटिक डिटेक्ट होगा एक्सीडेंट और पहुंचेगी तत्काल मदद

ETVBHARAT

Ai मॉडल सड़कों पर ट्रैफिक निगरानी के लिए लगे कैमरों का उपयोग करके सड़क हादसों का पता लगाएगा.

Transcript

00:00Today, we have thought about a situation for India, which is all for India.

00:07Basically, what happens is that everyone is very important.

00:11Everyone is very important, everyone is very important.

00:13Today, accidents are very important in our country.

00:16The main point of accident is the time of ambulance.

00:21On average, Metro cities, Delhi, Gazi, Avaar, Noidai,

00:25there are 30-45 minutes of ambulance in the location of accident.

00:30Now, if you think about the accident,

00:33what will happen to you?

00:35This time, if you don't mind, it will be together.

00:39What do we have done?

00:41We have made a system,

00:43which is how many traffic cameras are,

00:46which detects the traffic cameras,

00:49which detects the accident,

00:51instantly the location is pinpointed,

00:54and it will be available in the RTO database.

00:57One thing is that,

00:59the CCTV camera is now,

01:02the number plate is seen

01:03and it will cut it.

01:05Now, this is the CCTV cameras.

01:06We will install it in the CCTV cameras.

01:08We will install it in the RTO end,

01:11which is our data,

01:12and the accident is detected.

01:13So, with the accident,

01:15we can send messages to their neighbors.

01:17The people say that,

01:18the car has crashed.

01:19So, we can send RTO data to our neighbors.

01:23What is the name of the model?

01:24How many of you have prepared?

01:26We have used the Volvo V8-4 model.

01:30We are using the model.

01:31We are using the object detects

01:33and then we have written the code from frame by frame.

01:37So, we are using the code.

01:38So, we are using it.

01:39So, my team mate,

01:40the connectioner,

01:41I can tell you about the user interface.

01:43I can tell you about the user interface.

01:44In the user interface,

01:45the model that we are working on is

01:46the AI scraper model.

01:47It is a beautiful soul scraper model.

01:49It is an AI model.

01:50It is an AI model,

01:51which is a news channel,

01:52which has been trained in the news channels.

01:54It has been trained in the words.

01:56So, you can use the words to use the user interface.

02:00You will give traffic updates,

02:01and you will give time updates.

02:02So, it will happen.

02:03If you are going to rally in an area,

02:06and you will go to the route,

02:08so, the normal time you will predict the Google map.

02:11It will be 70 minutes.

02:13What will our model do?

02:15If there is a rally in the time,

02:17and you will study the information and update the time.

02:21So, this will be an advanced version of Google maps.

02:25There is a future scope.

02:27In our model, there is a future scope.

02:29Because we are trying to do the same things,

02:31we will try to tie up the government.

02:33So, our model has an accident.

02:42There is an ambulance help.

02:44We can tie up the start-up.

02:46The ambulance will be connected to our database.

02:48The ambulance will send help.

02:50Now, in hospitals,

02:53there is a big process.

02:55You have to fill the form.

02:57You have to fill the form.

02:58You have to give information.

03:00You have to give information.

03:01But, when you already have an affiliated model,

03:03the government is already tied up.

03:05You do not need to keep it.

03:08You can directly admit your patients.

03:11If your case is serious.

03:13So, this is a future scope.

03:15This is a future scope that we can add.

03:17The team member, Kanishk,

03:18we have used the Yolo V8 model.

03:20The Yolo V8 model is an AI model.

03:22It is a work to detect the object.

03:24It detects frame-by-frame object.

03:26But the question rises.

03:28The accident is how to detect the accident.

03:30We have read it thousands of frames and videos.

03:34We have written it as accident.

03:37We have written it as accident.

03:38When there is collision, overlapping,

03:39or at the speed of any changes.

03:41So, we have noticed the changes.

03:43And the coding feed it.

03:45When there is something like this,

03:47it is accident.

03:48So, in the basis of our model,

03:49it tells us that if there is collision,

03:52then it is accident.

03:53And it detects the user portal

03:55and the RTO portal.

03:57And in the future scope,

03:58it can also go to the ambulance.

04:00It can also be aware of the people.

04:03Because one minute,

04:04the accident happens when there is accident.

Category

Transcript

Be the first to comment

Recommended