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Leveraging sensor data analytics in 'Big Data'

Posted: 15 Jun 2015 ?? ?Print Version ?Bookmark and Share

Keywords:Big Data? Internet of Things? IoT? sensor? MCU?

The second category opened by sensor data analytics involves the monetisation of the information itself. Taking the hospital smart bed to the next level, the sensors in the bed can detect whether or not the patient has been moved or turned within a certain timeframe to help avoid skin ulcers or "bed sores," a leading cause of hospital readmissions. Using this information proactively can not only improve care quality, but also have a major financial impact on the hospital's billing and cost structure.

In the manufacturing or facilities world, a stationary motor presents a vibration signature as it rotates, and that vibration pattern can be recorded by an accelerometer. A healthy motor generates a frequency signature that is relatively constant.

As the motor wears out, a defective ball bearing or a slip in the gears will cause the motor to vibrate more vigorously and generate a broader vibration frequency spectrum. By detecting frequency content changes, sensor data can be analysed to derive motor health over time. Armed with this information, factory managers could schedule preventive maintenance more efficiently, saving time and money.

Or, to use just one supply chain example, imagine the intelligent beer keg. Using sensor data to determine how much beer is left in the keg, bar owners and their distributors could derive real-time beer consumption information, allowing them to order beer only when it's needed, avoiding lost sales opportunities and lowering inventory costs.

Good news, bad news

The good news in all these examples is that there will be no shortage of data from sensors for analysis and action, opening unlimited possibilities for designers and business people. There is one challenge we must consider, though, in design and implementation in the IoT: security and privacy.

Sensors are so sensitive and can pick up ambient signals that not only contain the target information needed by an application, they often carry other information that different sensor data analytics algorithms can uncover. Without the proper security and privacy built into products, private information could be unwittingly transmitted.

For example, a potential burglar could notice that a smart bed has not been used a few consecutive nights and deduce that the owner may be traveling. Hacking into the data from the connected beer keg would allow competitors to determine how much business the bar or restaurant down the street is doing, and react accordingly. And, it's been shown that the accelerometer in your smartphone, sitting next to your computer keyboard, can detect what you're typing with a reasonably high degree of accuracy.

To guard against mayhem and financial disaster we need to think beyond the IoT and get to the Internet of Tomorrow. The Internet of Tomorrow is a highly-secure version of the IoT, one that implements strong security at every level of the Internet infrastructure, at the end node, gateway and cloud levels, and within each device at each level. Only secured data can be trusted data.

The secure IoT will continue to grow, and sensor data analytics will be a key component in driving new applications. Those applications will redefine products and categories, and help companies monetise sensor information, providing new benefits to consumers and to companies bottom lines. We are limited only by our imaginations and our ability to provide practical security and privacy protections moving forward.

- Ian Chen
??Freescale Semiconductor

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