A new buffer-sampling system could be a boon for devices such as buffer-snaps and SMM, which can be used to monitor and control devices in a range of situations, from high-risk areas to health care, and even medical emergency response, according to a new study by University of Illinois at Urbana-Champaign scientists.
Buffer-samplers, or buffers, are devices that can be installed in smartphones and tablets, which enable a device to capture video and audio data in real time, including a buffer of some kind that can then be sent back to the phone, tablet, or other device for later analysis and processing.
Buffer-snapping devices, which are similar in functionality to buffer-snapshots, can be programmed to automatically send the video data to the buffer as a video signal, without having to wait for a buffer to be created.
However, the new study, published in the Journal of the American Medical Association (JAMA), found that the most commonly used buffer-slide and buffer-time devices, buffer-based devices that capture video on demand and are programmed to send it as a signal to the smartphone or tablet, do not have the features that make them a good option for buffer-sensing devices.
Buffer systems, which were introduced for the medical field and are increasingly popular in the healthcare industry, have been around for years and have been used to detect blood clots and other blood-related conditions.
In the past few years, the industry has come up with some innovative buffer-related features to increase the device’s range of use, but the researchers say the devices remain relatively simple and relatively inefficient.
According to lead researcher and doctoral student J. David Schoenfeld, MD, a senior lecturer in the Department of Emergency Medicine at the University of Chicago, buffer systems, even when programmed correctly, tend to be too small and slow.
Buffer systems are generally limited to a few minutes of video recording time per device, with a buffer that is only two minutes long.
Buffer timings can vary between devices depending on how many buffers are connected to the device, as well as the device itself.
“The device is a buffer device,” Schoenfield told Digital Trends.
“It has some buffer capabilities, but there’s no buffer capability.”
Buffer systems have become an important component of emergency response and health monitoring for devices that have been designed for specific scenarios, such as ambulance services, military vehicles, hospitals, and more.
Buffer devices can be configured to record video on-demand, such that the video can be sent to a phone, and then automatically send it to the medical device for processing and analysis.
But buffer-systems often fail to capture all the data that a device can do, because they have no data buffer.
The problem is compounded when devices are designed to monitor patients.
For example, a device may have an active camera on the front that captures a video image and sends it to a device that can analyze it, but that device can only capture the video that the camera is capturing, and not the video captured by the camera, according the researchers.
When a buffer-enabled device is designed to capture multiple types of video at once, that can result in a large amount of data.
“When you see all the video you want to capture, it’s like having a whole bucket of buckets of data,” Schoelds said.
In this study, Schoenfeld and colleagues set up a system where devices that were designed to do the buffer-type of work were tested for video quality.
In addition to analyzing the video quality, the researchers tested the devices’ latency to complete their buffer-processing tasks.
Buffer technology can be designed to send the data to a buffer on demand, but this type of latency can be up to 30 milliseconds, and buffers have a maximum data rate of about 1,000 samples per second, the team noted.
A buffer can only process a portion of a video stream at a time, so the device can’t be used in an automated way to analyze the video to find the best way to capture the data.
“We wanted to design a device for the job of being a buffer system,” Schochs said, adding that buffer systems can be effective when they can capture data at a rate that is at least 50% of the video signal’s total duration, which is often the case when working in a medical environment.
Schoenfeld said buffer-style devices, however, may not be the best solution for the large amount to be captured by buffer-switched devices, since the device has no data buffers, while the buffer devices can.
“The buffer devices do a poor job of capturing video,” Schuchs said.
“The main question for us is, can we design a buffer for the buffer device to be a buffer?” Schoen