Although AI has been around for decades, its advancements in the recent past have made it a hot topic and technology for multiple applications, including the medical field. AI is particularly good at identifying new medicines, proteins, etc., by boosting R&D in these fields. But one particular area that not many people know about AI in the medical field is its use in smart cameras. Most people know about AI-powered cameras in autonomous vehicles, robotics, and industries, but this technology is applicable in medicine as well in the following areas.
Applications of AI-Powered Cameras in the Medical Field
Detecting Vial Swap Errors
Since AI-powered cameras provide real-time insights and error detection, they are handy in detecting things like erroneous vial or syringe swaps. The AI model behind them can be trained to detect cap colors, vial shapes, or label sizes with a high degree of accuracy (above 95%) to assist medical experts, doctors, surgeons, and researchers in labs avoid mistakes that cost time, money, or even life.
These extra sets of eyes are particularly useful in operating rooms and intensive care units where drug administration errors are frequently reported. Ideally, safety measures like barcodes should be used to prevent such accidents but the high-stress environment coupled with human error causes mishaps or failure to do these checks, making AI cameras relevant in this use case.
Enhancing Patient Safety
Elderly patients who require caregivers, such as the elderly, need round-the-clock monitoring, which can be expensive if you employ someone to do that as a full-time job. But with AI-powered cameras either mounted around the home or on a robot can do the monitoring and only alert the caregiver when something goes wrong, such as if the patient falls or experiences a seizure. Essentially, this remote patient monitoring system enables one caregiver to do the work of 5 or 6 people.
In hospitals and mental facilities, AI cameras can detect violent behaviors like fights and aggressive behavior and then alert the relevant personnel accordingly.
How To Develop AI-Powered Cameras for Medical Applications
There are 4 ways to do it. You can buy a ready-made camera with edge computing capabilities to handle the AI inferencing locally on each node. The second option is to get pre-made SOMs and the third is to use SBCs, such as NVIDIA’s Jetson Xavier NX.
The fourth and most recommendable option for hardware-savvy persons is to design and have everything made from scratch, except the chips. Companies like OurPCB provide custom PCB manufacturing and assembly services at reasonable prices to get your AI camera project off the ground.
But there’s one critical thing to consider in this use case, which is the medical factor. Because these cameras can be the difference between life and death, it is important to build them using Medical PCB standards to ensure they are highly reliable. These involve optimizing the PCB design, using high-grade materials, and complying with international standards, such as IPC, ISO, UL, and FDA.
The AI training should also be done thoroughly to ensure high accuracy levels during inference.
Final Thoughts
AI is revolutionizing the medical industry because it is almost equivalent to having another human on watch, only this time running 24/7 with minimal chances of errors. And it will only get better with time. Therefore, incorporating AI into your operations is a sure way to stay ahead of the game. I recommend developing these cameras using PCB assembly manufacturing services to customize the solution to your specific application.
