In part-I, we have discussed the meaning, scope, stages of AI, few applications, and benefits/uses of AI in society. in this article, we are going to see about the transportation and medical applications of AI.

AI in Social Problems:

Litterati

It is a crowdsourced litter clean-up app and a global database for litter. Identifies litter type, distribution, and location and helps to find more sustainable solutions.  

In 2017, 1.1 billion cigarettes were found all over the world.

AI in Road Transportation:

Road transport is a major sector where AI can be applied more prominently. AI can make transportation modes much safer, cleaner, smarter, and more efficient. 

Self-driving cars

Self-driving cars are a combination of sensors, cameras, radar, and AI technologies like machine learning and neural networks. Developers use a large amount of data from image recognition systems. Neural networks identify the pattern in data i.e., images from the cameras and sensors. It identifies the traffic signs and signals, boundaries, trees, pedestrian walks..etc.

One such technology developed by Google is Google Waymo Vehicle

Google Waymo Vehicle

It is an example of self-driven cars. It is almost an autonomous vehicle but still needs a human to perform certain functionalities but can drive in ideal conditions. 

Levels of Autonomous Cars

LEVEL 0: No Advanced Driver Assistant System(ADAS) is used. The human driver should drive.

LEVEL 1: ADAS assists the driver by its alert systems by its rear-view cameras, but the driver should take care of the steering, brakes, and acceleration

LEVEL 2: Human presence is important even though ADAS will take care of the steering, brakes, or acceleration.

LEVEL 3: ADAS can take driving tasks and parking can be performed under certain conditions. But still, human is the main driver here and need to take care of the circumstances.

LEVEL 4: The driver need not pay much attention as ADAS can take over the driving.

LEVEL 5: No human help is required. ADAS can drive the vehicle under any circumstances.

Truck platooning

Truck platooning is also an example of Artificial intelligence. It is a heavy coupling of trucks. The first truck is occupied by the human driver and the rest are fully automated. They maintain a minimal distance between them and accelerates at the same rates. It might be a risk during traffic and unexpected accidents might occur. In the future, the risk factor is expected to be less.

AI in Medical Sector:

AI helps health professionals to diagnose the patient faster and more accurately. 

AI is developing innovative drugs and treatments by reducing medical and diagnosis errors by predicting adverse reactions. Lowers the cost of healthcare work providers and patients.

Problems at the healthcare centers

Due to more number of patients, general practitioners and primary care surgeons are over-burdened because of which there are extremely long waiting at the hospitals.

Solution  

Your.MD

Your.MD aka Healthily is the world’s first AI-based health assistant which provides personalized advice about their medical complaints. This app records the symptoms and, maps them with the clinical data compiled from public sources. Engages about thirty doctors to research illness.

Research

It creates a pre-primary care market and eases the burden of medical staff and helps improve their work through digital screening of non-accurate conditions.

Google Launchpad Studio

Creates an ecosystem of applied Machine Learning startups and focuses on healthcare.

BYTEFLIES is the first company to use this studio.

Supervises Learning for Telemedicine 

Technology can be used for good and bad so there is a need to be vigilant. The latest technologies are typically applied to the wealthy. 

But,

“AI has the potential to extend knowledge and understanding to a broader population. Image-based AI diagnoses of medical conditions could allow for a more comprehensive deployment of the telemedicine”. 

Google deep mind

Google deep mind can diagnose diabetic retinopathy like a highly trained ophthalmologist via telemedicine.

‘BETTER DIAGNOSE WITH LESS HUMAN EFFORT’

It uses a portable fundus camera which is deployed in the screening site and transmits images securely to the cloud software platform for analysis and automatically generates a report which facilitates compliance with follow-up examinations.

credits to the right owners of the images used.