Wearables and Internet of Things : Part III

This series is complimentory to our practical guides with ESP32 & IoT. One can quickly check our 2nd part of Wearables and Internet of Things. In this part on Wearables and Internet of Things, we have limited the usage of Wearables in the Internet of Things to two out of five use cases – Health, Trade, Production & logistics, Field service and Lifestyle.

Using the example of the Fitbit Flex: The device has an ultra-low-power ARM Cortex-M3 with 32 Kbytes Flash, 32 MHz and a USB controller. To save power, the processor clocks variably between 32 kHz up to 32 MHz. The performance is not sufficient for complex computational tasks, but sufficient to count steps, to operate the LEDs of the device or to generate random numbers.

 

Potential Applications and Use Case

 

In the evaluation part, above all is the merging of the data is in the foreground, like to gain new insights from a variety of data, such as how little exercise combined with poor sleep together. Wearables in garments can provide information about the financial situation, giving “on-the-spot” instructions to the local staff for advice. Evaluations can take place on the devices, for example, graphic reprocessing. Complex evaluations (evaluations of several sensors, devices or the like) take place, for example, on company servers (IBM Watson Health) or on other devices such as smartphones or notebooks.

 

Health

 

In the area of ​​health, wearables could help limit cost increases. In 2013, spending was 314.9 billion Euro, an increase of 4% over 2012. With the help of wearables, it would be possible in the future, for example, to replace or reduce physician visits which serve only to measure blood pressure by transmitting the data from wearables. Also, the long-term ECG could be greatly simplified with the help of wearables and this could also reduce costs (fewer visits to the doctor required).

In particular, prevention should contribute to cost reduction, including, for example, sufficient movement through gamification . An example of this is the prevention of obesity. Overweight is also caused by too little movement. Obesity not only increases health care costs (eg diabetes), but also increases earning capacity (from work loss to unemployment (learned work can no longer be carried out)), and hence health care and/or health benefits Social system (reduced tax revenue, loss of purchasing power, etc.).

The health insurance can motivate policyholders, for example with attractive bonus programs or a reduced contribution rate, to transfer the data to insurance companies. But there are still legal hurdles to overcome, especially in the health insurance sector, the solidarity principle applies. This means that the costs of such a “bonus program” must be covered by savings. This has the background that not all policyholders may be able to participate in the bonus program and they are not allowed to finance the program.

An example of a wearable in the healthcare industry is the Fitbit Surge. The Fitbit Surge provides the following functionalities (reduced to health-relevant functions):

• GPS
• Optical heart rate measurement
• sleeping recognition
• step counting

In addition to the features provided by the wearable, Fitbit provides a dashboard to evaluate the data using the Fitbit software. Furthermore, additional data such as nutritional information can also be collected. The software should help to evaluate the data and to motivate the user (ranking system, challenge friends and family members). Other functions that are not directly related to “health” are, for example, the alerting of calls or messages from the paired smartphone. The Fitbit Surge communicates with the help of the smartphone and has no direct connection to the Internet.

Data and sensors

1. GPS
2. Speed ​​and 3-axis accelerometer
3. 3-axis gyroscope
4. digital compass
5. optical heart rate monitor
6. altimeter
7. Ambient light sensor
8. vibration motor

 

Currently, the data to be evaluated is still low, as a result of which the wearables do not yet have “everyone” (in comparison to smartphones) and that the data is not yet centrally stored and evaluated. Each manufacturer still rates the data independently. The biggest problem, especially in the healthcare industry, is data protection. The data is highly sensitive and everyone wants to protect this data in the best possible way. Another problem is the quality of the data, erroneous measurements are quickly detected, the defect of a device is noticed and the doctor can be sure that the patient has adhered to the manufacturer’s instructions.

 

Trade

 

In terms of trade in the Internet of Things, humans no longer play a decisive role. The focus is much more on the fact that machines can communicate directly with each other or data can be exchanged without human help. This is essentially about the general automation, as well as networking of machines (M2M). The main goal here is that the wearables make everyday life easier for people and reduce their thinking as far as possible.

A goal of the retail trade is the cost reduction in industrial production with the idea that systems should control themselves in the near future. This new development in retailing will give digital forms of business a huge boost.

Ultimately, the end-user’s refrigerator learns to shop and now makes purchases for its owner. Buying is of course online, without the human time loss factor. However, the consumer will be deprived of the opportunity to opt for an alternative at the last minute. A potential danger here is that the high earners then no longer buy the expensive products, but the purchasing is generalized and the service and quality services are neglected. Strictly speaking, the local dealers would no longer be needed, then the manufacturer of the products would be very close to the customer.

The Internet of Things provides vendors with a direct channel to the bathroom, bypassing commerce, and a much-quoted example is the Gillette razor, which orders new blades at the push of a button – perhaps even completely automated, if you trust the brand The bonding potential of brands is thus extremely strengthened, because no consumer is distracted from other stimuli, ie other brands and manufacturers, before the purchase decision: between consumer and manufacturer, there is only one button left – and no shelf with competing products.

The Internet of Things is a very lucrative business for manufacturers, but for small businesses promoting services and quality, there would be barely any room in the market in the era of the Internet of Things with wearables.

Data and sensors

RFID

Or procedures such as the Gillett box. “The Gillette box must be registered with your ID once in the Perfect Shave shop and assigned to a customer with delivery and payment data, then it can go online via GSM connection and submit the reordering at the push of a button triggers an HTTP request to the server, passing the IMEI number of the device paired with the box ID. ”

Automating repeat orders creates customer loyalty between manufacturer and consumer. The consumption of individual consumers can be read by the companies on the products. The companies can thus optimize their production and retain customers.

 

In the next part of this series, we will continue the discussion with rest three use case.

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