The Internet of Things is expanding rapidly, and the amount of information generated by connected devices is growing exponentially every day. While it may be impossible to comprehend how much information the world’s smartphones, sensors, and other electronics create if your work involves artificial intelligence, it’s not hard to spot opportunities on the horizon.

The proliferation of peripherals – essentially any device with a direct connection to the Internet – and the relatively recent emergence of 5G networks have created new uses. Artificial intelligence it could change entire industries. Healthcare organizations in particular will benefit from this convergence of trends in many interesting ways. Before exploring some of the ways in which these technologies can affect healthcare, let’s talk about why recent developments are so appealing to artificial intelligence developers.

Big Data jobs

Edge computing is the practice of placing servers close to the data on which the data is created. By capturing, storing, and analyzing data in the vicinity of the IoT device it created (instead of sending it to a central cloud), companies can process data faster using less bandwidth. As a result, not only do their applications run faster, but they can also reduce the cost of processing data for multiple applications running simultaneously.

Potential time and cost savings are hard to ignore, and Gartner roughly predicts 75% of the data produced by companies will be addressed on the edge by 2025. Artificial intelligence has the potential to facilitate intelligent edge computing by automating the allocation of processing power between peripherals and cloud resources as needed.

Particularly fascinating is the idea of ​​education Artificial intelligence patterns on the edge – after all, it’s where the information they need is created. Unfortunately, the prerequisites for adequate training in advanced machine learning algorithms can only be found in centralized repositories. However, a handful of companies are working on this problem, and the latest breakthroughs from IBM suggests that model training on the edge may soon be available.

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2. How will artificial intelligence trigger the next wave of healthcare innovation?

3. Machine learning using a regression model

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As IoT continues to invest in cutting-edge computing and artificial intelligence, new opportunities will begin to emerge. Here’s how the future of healthcare can look like:

  1. Improved security and privacy. Complex data protection regulations are a huge barrier for product teams looking to bring innovation to healthcare. Healthcare organizations cannot adopt new technology unless they comply with HIPAA and other industry guidelines, and new data protection laws such as the European GDPR and the California CCPA add to the complexity. However, the data at the edge is left to the user because it is processed locally and not in the cloud. The huge burden of compliance will be greatly reduced if IoT applications can operate without the need to collect and store all sensitive patient data.
  2. Reduced delay. In the case of many healthcare applications, the latency must be absolutely low. Take, for example, sensors that use portable heart monitors or attached hospital wristbands. These devices collect patient data and transmit it to the cloud, allowing care providers to monitor patient health remotely. A slowdown in data processing may prevent them from detecting a sudden change in a patient’s heart rate or blood pressure in time to respond to a life-threatening emergency. As consumer demand for health-related clothing increases, so does the need to ensure real-time computing.
  3. Robot nurses. No, machines will not replace your family doctor at any time. But new developments in robotics and artificial intelligence have brought Industry 4.0 to the fore, and physical IoT devices, such as artificial intelligence-assisted voice assistants, will undoubtedly play a greater role in patient experiences going forward. Instead of displacing healthcare workers, these devices help physicians, nurses, and administrative staff make better use of patient data, leading to more and better quality time with patients (either in person or through telemedicine).

In healthcare and other industries, organizations are increasingly aware of the limitations of the cloud. Don’t just wait for it to disappear. Cloud-based solutions continue to dominate the healthcare technology market due to their excellent scalability and ease of development compared to IoT devices. However, as IoT matures, artificial intelligence devices are playing an increasingly important role in maintaining health.

At Saip, we are excited to help companies seize the opportunities offered by these converging trends. That’s why we offer several services specifically for teams that build artificial intelligence for IoT devices. Our staff consists of professionals with in-depth expertise in the development of IoT-based solutions and our people are at the heart of our offer. In addition, we give the IoT product team access to more than 7,000 trained partners who can provide the information you need to develop scalable IoT solutions on the edge.

If you would like more information about what we offer, please visit our website or contact us.

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