Wearables and Big Data : Business Scope and Brief Details

This article on “Wearables and Big Data” explores the relationship between wearable technology and ever-growing amounts of data – big data. Various wearable devices are presented in connection with the application possibilities in the private as well as in the business area in our previous articles, the topic big data also has been discussed. In this article the potential and possible risks are explained to cover the topic to provide a basic knowledge. First we will discuss the basics of big data for a quick revise. The part of title “Business Scope” obviously has been covered in this article.

Big Data

The term big data describes the exponentially growing number of unstructured data that can come from many different sources. The goal is to store, analyze and utilize the unstructured data. A data source can be almost anything as long as it can be captured and stored digitally. In most companies, internal data is processed because there is no need to collect more data. However, there are increasing numbers of companies specializing in the collection and analysis of data.

Examples of data sources:

1. Social media
2. Transactions
3. Log data
4. Event data
5. E-mails
6. Sensors
7. Text
8. Geodata
9. Audio data
10. Still images/videos

Due to the large amount of data being collected, one has to differentiate between three aspects – Volume, Variety and Velocity.

Volume:
The volume of data is increasing exponentially each year, with global data volume increasing by 43.25% from 1.227 exabytes to 2.837 exabytes in 2011, 8,591 exabytes for the year 2015 and 40,026 exabytes for the year 2020 as forecasted. These data volumes require high storage capacities and computing power for the evaluation.

Variety:
Today, a variety of data must be distinguished and in particular unstructured data complicate the evaluation and storage in classical relational databases. In relational databases, the data is stored as records, giving it a structure in the form of tables. This structuring is not always possible for the large number of different data and thus complicates the management of the data. The diversity of the data can still be differentiated according to structured, partially structured and unstructured data. The goal is to generate added value from the unstructured, diverse data, which is referred to as smart data.

Velocity:
The speed of data acquisition has increased significantly in recent years. Data can be captured in real-time, meaning that large amounts of new data are generated in a short time. The second component of the speed is the processing of the collected data to make it usable. For a timely processing of the collected data high computing power is required and high data capacity.

Smart Data:
Smart Data describes the processing and evaluation of the collected data and the generation of valuable added value. Captured data provides information about states or measured values ​​and serves as information for further processes or processes. By creating intelligent relationships between the information, results can be derived and forecasts can be made. The data now has added value and is transformed from big data to smart data.

Wearables

Wearables refers to electronics that can be worn on the body as an accessory or part of a garment. The crucial factor is the connection to a smartphone, tablet or the Internet in order to use the collected data. However, the connection to another device (smartphone/tablet) is not absolutely necessary, since there are also independent wearables that use a SIM card. Wearables can be different components and can not be limited to one type. For example, there are smartwatches, cameras, fitness bracelets or jewelry, all of which fall under the wearable sector.

Field of application and potential

The variety of wearables allows a wide range of application areas, and the potential on the market is correspondingly high. Wearables are on the rise and sales will increase to up to 150 million units in 2015, Statista said. Basically, wearables can be divided into the following areas:

1. Security
2. Fitness/Health
3. Lifestyle
4. Communications
5. Glamor

The largest areas continue to be fitness / healthcare and smartwatches (part of lifestyle). [6] In the case study we look at the following 3 core areas: smartwatches, health-wear, eye-wear.

Smart Watches

Smartwatches are probably the best known and most widespread wearable available on the market today. A variety of manufacturers compete with each other, with different models and strategies. The first smartwatch was introduced in 2003 by Microsoft at CES in Las Vegas, then referred to as SPOT (Smart Personal Object Technology). However, this has little in common with the current smartwatch models. The big breakthrough came with the launch of Android Wear in March 2014. For the first time, there was a common platform for smartwatches used by manufacturers such as Motorola, LG and Samsung. As a counterpart to this, Apple introduced the Apple Watch in 2014, with a proprietary operating system and exclusive use with iOS devices. The functions of smartwatches are designed to control smartphones and are designed to simplify and speed up the operation. Messages and news can be read on the watch, or the music can be controlled. This is made possible by the coupling of the smartwatch with the smartphone via Bluetooth.

Health-Wear

The field of health wear is becoming more and more important. They can monitor the vital signs, including pulse, breathing, exercise or physical activity. Due to increasing awareness of nutrition and fitness this is the area with the highest potential. The variety of devices is immense, both in terms of manufacturers and models, as well as the range of functions. A pulse sensor has few devices, pedometer or motion sensors, however, are now standard.

Eye-Wears

Eye Wear is the area that is the least developed. Google has taken a first step towards eye-wear with the project Google Glass, but the project has since been discontinued. The potential is not yet as well developed as that of the other areas, as the technological requirements are much higher. Decisive is the acceptance by the customers and the usability in everyday life. To be suitable for mass further developments are needed. In addition, the prices for eye-wear are significantly higher in comparison and thus have a deterrent effect on some potential buyers. Google Glass was priced near $1000.

At present, not all of the possible application areas are being exploited, but the development of sales shows that wearables are becoming increasingly important.

Wearables und Big Data

Home users are very interested in wearables, especially in health wear and smartwatches. According to a survey, 29% of respondents prefer wearables to clothing, 28% wearables for the wrist and 18% integrated into the shoes. In the areas of the product range is also correspondingly large and the number of manufacturers is high.

In the field of health-wear/fitness there are most products, as the demand for advanced sports equipment has increased in recent years. With the help of wearables, every user can control their performance and share it with others on social media platforms. An example, a typical device offers wearables to measure the distance traveled, heart rate, steps and time. But more than one wearable is needed. On the one hand, the activity tracker, the heart rate monitor can work own smartphone. In addition, the data can be analyzed via app and then shared on Facebook or Twitter.

The use of smartwatches is also steadily increasing as there are more and more new vendors and prices are falling. The high prices prevent many customers from buying, since prices are comparable to mid-range smartphones ($250-400). For this price segment many customers do not see the need for a smartwatch and the functionality is not sufficient. There are also combination products that offer both the functionality of a smartwatch and can be used in the health/fitness area. Example is the Samsung Gear.

Business scope

The use of wearables in the business sector is still marginal. Even though wearables are on the rise in the private sector, it is still not enough for business operations. Interesting is the development of eye-wear, for use in construction or mechanical engineering. With the help of eye-wear, the plans could be visible in front of the eye and the user can continue working without interruption. However, the development is not so far advanced and in the business area, the products must be mature. As a result, it will take some time for wearables to reach the masses of the business community.

Wearables are able to save live data or, for example, to a smartphone app to transfer. These include, for example, vital data (heart rate, etc.), GPS, movement data and activities, but also audio or video data. The wearable sensors continuously record new data, which can then be analyzed. The continuous improvement of the sensors makes the measurement results more accurate and provides detailed information about, for example, the state of health.
The recorded raw data can be evaluated and graphically processed using apps or databases. For example, it is possible to follow the course of the pulse beat or the distance traveled, with the help of the GPS module. If the measurement results are combined, conclusions can be drawn on the daily routine of the user. How is the daily commute covered? At what time does the user leave his home to work? In addition to the data collected by the wearables, the user can capture additional data and complement their profile. Google Now is an extension of Google Search and is offered by Google Inc. It’s an app for Android and iOS devices that simulates a Personal Assistant. Information is provided to the user based on the information Google Inc. receives. Prerequisite is a Google Account and the consent of the data analysis. With the use of wearables even more areas can be used. This applies both to use with a wearable, such as a smartwatch, as well as the collection of vital data.

Data collection is no longer limited to empirical, technical and scientific data. The collection, evaluation and use of user data is becoming increasingly important. In addition to the technical and scientific data, data from each person can now be recorded and linked together. By using social media, users disclose their information and contribute to the steady growth of big data. With the proliferation and use of smartphones and tablets, new opportunities have been created to collect personal information. For the first time GPS data could be collected and evaluated by private users. In conjunction with, for example, the Google products or Facebook, a new range of data is generated. People worldwide use social media, share personal information, images, opinions and share their locations.

With the help of wearables, another component has been added, with which user data can be collected. The data collected is particularly sensitive and therefore requires high safety standards. Anonymised, the data are harmless and can be used for general evaluations. However, in combination with personal data, these represent a personal risk. In June 2012, Google introduced Google Glass. A pair of goggles with integrated display for extended use of Google services and access to the smartphone. The idea is a double-edged sword, because on the one hand, the prospect for the future can and probably will look the same. On the other hand, the use of a variety of data, which fall under the Data Protection Act. This includes, in particular, recording in sound and vision of persons who have not expressly consented to the recording.

The collection and analysis of data helps companies to tailor their products to the users. In many use cases users receive the offered products free of charge and the companies are allowed to use the given data. A data set is not meaningful on its own, but the combination and analysis of many data can create significant added value. For example, a flu wave in America could be predicted 2 weeks earlier, with the evaluation of tweets on Twitter. Wearables are able to collect health-related data to assist the doctor with a diagnosis. Not only the analysis of personal data brings advantages for companies and users. Through the development of sensors in vehicles, a large amount of data can be recorded, the evaluation of which, for example, can prevent traffic jams or rear-end collisions.

The collection and evaluation of data also has disadvantages. Larger data centers are needed to store and evaluate the data. This requires a high energy supply and thus contributes to high CO2 emissions. On the other hand, people will increasingly glass, since he has to disclose personal data for various services which are stored. The increasing flow of information about locations, for example, can have fatal consequences if data protection is not observed. So it would be possible, people wearing a smartwatch or another wearable to check on their state of health, their fitness activities, their daily routine and the like. Due to the large amount of data and their variation, special attention must be paid to data protection. Legal provisions govern the processing of personal data in various countries. Basically, it is necessary to protect all personal data and to record only with the consent of the person concerned. It is also important to take care not to hurt the person in his right to privacy.

Illustration credit : wittysparks.com/smart-wearables-influence-on-our-lives/. Our website used the illustration for academic purpose to visually present their analysis to the readers. Our website has not verified their analysis.

Conclusion

The volume of data and its complexity are steadily increasing. Storage, processing and evaluation are becoming increasingly important for companies. By processing big data into smart data, the collected data can generate added value that brings all information into a logical context. The era of wearables has just begun and the new technology is on the rise. Just as smartphones and tablets have conquered the market, wearables will also become part of our everyday lives. This gives us access to new data formats and other information that contributes to big data.