In a time of crisis, like the recent pandemic, healthcare managers scramble to obtain critical medical supplies. It’s important to be able to locate many thousands of assets, such as ventilators, and quickly get them where they are needed. Digital twins provide powerful, real-time analytics that can track these assets and verify their condition, giving personnel vital information at the right time. In addition, digital twins can track needs, such as the shortfall of critical supplies at each hospital, so that managers can prioritize where to direct available supplies.
Because digital twins maintain contextual information about the assets they track, they can store key parameters and update them in milliseconds. For example, the digital twin for a ventilator can store its identifier, make and model, current location, availability, technical issues, and recent repairs. The ventilator sends a message to its digital twin whenever its status changes. In this way, digital twins give managers the information they need to get the greatest benefit from all available devices.
Because digital store contextual information, like medical history for wearables, they enable the next generation in real-time analytics.
Digital twins can integrate sophisticated analytics with key contextual data and generate alerts in milliseconds.
Using powerful in-memory computing technology, digital twins can track thousands of devices simultaneously.
Managers can track data aggregated across a large population of digital twins to detect widespread problems in real time.
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As smart watches and other wearable devices have become more sophisticated, wearers have grown increasingly dependent on their daily feedback. They report biometrics like heart rate, calories expended, and even blood pressure. However, they lack context about each wearer’s medical history, current medications, and recent activities. They don’t integrate this information to provide alerts when conditions dictate. For example, they lack the intelligence to detect when a specific individual might suffer heat stroke during hot weather.
Digital twins offer a breakthrough in computing power that can support a new generation of real-time analytics for wearable devices. They can store contextual medical data for each wearer and run sophisticated machine learning algorithms, detect emerging medical issues, and send immediate alerts.
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Fitbit watches sold in 2022
Heat-related deaths in Europe, summer 2022
Ventilators in the U.S.
Digital twins use in-memory computing technology to track millions of wearable devices at once, instantly access medical information for each wearer, and send alerts in milliseconds. Each wearable sends regular messages to its digital twin in the cloud. The twin performs sophisticated analytics and sends feedback to the wearer as needed.
The ScaleOut Digital Twins service can also analyze information across all digital twins to spot patterns of concern. For example, if it detects many severe medical alerts in a small region, it can identify a possible mass casualty event and immediately alert security and medical personnel to take action.