Wired: Algorithm is the next frontier of wearable technology

The next frontier for wearable technology is the algorithm, according to Wired magazine. Wearable equipment requires not only monitoring of various movement data, but also accurate monitoring data. Now, you and any?? A person with a scientific and technological mind talking about the biggest industry trend is sure to mention the term "wearable equipment" frequently. Two years ago, wearable equipment was a relatively unfamiliar type of equipment, and almost all technology companies are now involved in wearable markets.

Although wearable markets are fiercely competitive, technology companies are still scrambling to develop wearable products. Today, large technology companies are trying to compete in the physical design of wearable devices. Most wearable products are very similar in appearance, but in the next stage, the price, material, color and style of wearable equipment will provide more choices. Then, wearable device developers will differentiate their own software experience. After all, wearable devices without good software are just flashy jewels.

So what's the next trend in the wearable industry? Perhaps the most important part of wearable equipment is the use of algorithms to ensure that data accurately responds to various actions and satisfies various users.

The current situation of wearable algorithms

Whether it is the fuel points of the Nike FuelBand wrist strap, or the steps of the Fitbit Flex bracelet, or other wearable data, wearable devices can track and understand the user's actions, and then use proprietary algorithms to determine the action. At present, wearable equipment still has many technical problems, one of them is that the algorithm almost all tracking the same data (such as the number of steps), so wearable equipment is basically the same.

In particular, most fitness wearable devices have a common problem, which is that they are essentially "beautiful electronic pedometer", and they do not always recognize all of the user's behavior activities. For example, when a user takes a weightlifting workout, they remove the Nike FuelBand wrist strap, FuelBand not only interferes with exercise, but is unable to monitor the workout data. The user must manually input exercise information on the smartphone, the exercise process is bound to be interrupted, resulting in users of the device's interactive experience is extremely disappointed.

The problem with wearable equipment is not only the inability to monitor more body movements, but also the inability to accurately monitor movement data. Consumers are eager to get data on walking all day. Today is a lot more than yesterday, which means progress, but when consumers become more familiar with wearable devices, they will have higher accuracy requirements. For professional athletes, the accuracy of training data directly affects their performance.

What advice can wearable devices offer to users in the future? A truly intelligent wearable device should be able to analyze current and previous user movement data and alert users 24x7. For example, when a wearable device identifies a user sitting for too long, it encourages the user to get up and walk.

How to improve the accuracy of the algorithm?

Now, the algorithm can not really meet the needs of customers, we need the best way to fully mining data. Technology companies such as Apple have hired a large number of data scientists, and the recruitment of such talent will continue to increase.

Moreover, user research has become a key component of any successful wearable device, as wearable product manufacturers narrow their market boundaries by defining user groups. But user research is not necessarily the only skill the researcher needs, and the researchers need to be highly sensitive, analytical and creative. After all, user researchers will be the "consumer's advocate", using wearable equipment knowledge to spread users ' views across the industry and predict the success of the market for wearable equipment in the future.

Consumers need not only the beautiful electronic pedometer, they need not only the equipment with tracking function, but also the equipment to guide the fitness, sleep and diet. Users are eager to get all the daily activity data and need accurate data. If the algorithm can always understand the user's activities, and you continue to refine these algorithms, then you will gain long-term market advantage.

(Responsible editor: Lvguang)