Enterprise Data Hub and Wearable Sensors - Improving Digital Lifestyle

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McKinsey documented 12 technologies areas that will massively impact society and our evolution. Report denominated the total value of impact of these technologies in the range of tens of trillions of dollars per year. Although its hard to predict future but the analyis was done on recent advents and technology impact on social and economic indexes.

First in the list of these technologies is the Mobile Internet that covers increasingly inexpensive and capable mobile computing devices and internet connectivity. It is expected that by 2015, wireless web use will exceed wired use. These devices are helping people in interacting with the physical world. New formats of wearable devices are linking human digital data with applications and have capacity to distrupt and help us in learning more about human state & behaviour and collaboration. In the current paper we will be focusing on wearable sensor portion of Mobile Internet technology.

Advances in the areas of Semiconductor (MEMS), Software (Cloud and Big Data) and Communication (Low Cost Bluetooth) are enabling wearable sensors and brought intelligent watches for consumers. We anticipate that further advances in NEMS (Nano-electromechanical devices) will further improve the form factor. Also with advents in Big Data (Hadoop and NoSQL domain), it will have strong business impact. In our efforts to follow this innovation of wearable sensors, we are investigating two digital watches i.e. Metawatch (from Texas Instrument) and Gear (from Samsung) in learning the available technology landscape and evaluating their usage in two use cases that link real time human data with its potential in improving digital lifestyle. Both the devices have Bluetooth capability to connect with the cell phone devices and connect to centralized cloud application to transfer the recorded data.

Our first use case we are trying to link real time accelerometer data along with body temperature in improving detection of sleep and understanding relationship of stress and physical activity with psychological and physiological health in young children.

Our Second use case concentrates on building banking application for routine operations i.e. checking balance, recent transactions and act as a recipient for urgent notifications related to fraud detection. We anticipate that by recording real time behaviour data of users and monitoring the usage of existing bank applications, we will be able to improve customer retention in future.

The data from the devices goes over Bluetooth 4.0 via Android platform connected to cloud based NoSQL solution. Encrypted JSON data packets are used for data communication on real time basis. Data received on centralized repository is routinely crunched and analyzed via Hadoop Map & Reduce platform to extract information as per business requirement. Figure 1 highlights the high level data flow and solution schematics:
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