Sensors are new Normal

From 2000 to 2012, we saw applications and services coming out of the transition of data sources moving from desktops to mobiles. Similarly now the data sources are rapidly moving from mobiles to the individual users themselves. The question is “what” promises this shift of data-flow gives us? Who is disrupting this? How it is being done? And what business models might emerge from all this? To answer these and other allied questions, we need to analyze it so that we can benefit from it.

Up-till now, we have seen that wearable computing contains computing sensors to be used on an individual user. These sensors communicate with each other. An onboard processor, whether centralized or de-centralized, is used to embody filters and algorithms to help gather the needed data. Post-processing of this data gives us decision-making choices on the individual data source as a whole or in partial. So the questions are such that how these sensors efficiently communicate? How they transmit the data to the processing unit? How processing unit takes this data and feeds to some server? How the data is get stored in the storage-units? How it is fetched again? How it is leveraged or benefited? Which algorithms are employed? And many more!!

The market is huge for sensors, and its potential to penetrate into the consumer market has been realized by explosion of mobile device growth. So far sensor technology has been focused on industrial grade applications, but the accuracy of measurement was an issue. Now due to new advancements in the physics and innovation of technology, sensors are both accurate and consumer-driven. Big players like Google, Samsang, GE, Apple, Honeywell and the like had a deep focus on technology innovation in 2012. Wearable computing, which was considered weird, is the new normal these days. Research firms are forecasting a mega growth in sensor density from this year onwards. We are already seeing wearable devices from Nike (Nike Fuelband), Adidas (Adidas Watch), Fitbit (Fitbit Flex), Moondial, Jawbone (Jawbone UP), Pebble, Recon Instruments (in collaboration with Intel), Ulocs True Revolution etc.

There are certain visionaries in the game as well. One such example is the concept of Networked society from Ericsson. Ericsson knows the fact that sensors will definitely penetrate in the next few years, and there would be an aggressive need for a reliable connectivity among them. So for this reason they are developing their platform to support this mega growth in the future. On the chip scale, Intel is another example which is innovating in the design of smart sensor chips e.g. Intel Quark Chips. These chips are ultra-small chips which can be used in wearable devices, skin patches, or in-abdomen sensors for medical data aggregation. Qualcomm is also introducing new chips which are solely targeted for the wearable computing field. Ulocs is making waves in the creation of a platform for movement tracking and analytics. GE’s Proficy Intelligent Platforms have already shown great promise in the analytics domain.

Sensors can measure temperature, humidity, motion, position, pressure, magnetic change, etc. Due to these huge possibilities they are being leveraged by all industries big or small e.g. Aerospace and Military, Industrial, Medical, Transportation, and Test & Measurements. Those companies which are targeting a generic platform, for any such measurement entity e.g. position, will have a big share in the next incoming markets. One such example is Ulocs. Ulocs provides a technology which can detect accurate position/movement of an object without the need of GPS or radio. This generic platform coupled with an analytics engine will create a great benefit in virtually all the vertical markets. Honeywell which produces sensors for control applications is leveraging the benefits of sensor application provisioning to these vertical markets, one of the big reason that its place is still secured in the Fortune 100 scale.

The top concerns for sensor penetration are the security and non-interruption or non-interference. Many companies are focusing on the non-interruption side of the sensor application to daily life e.g. Google glass is designed to be easily wearable with very less interference to the wearer (but still many have some reservations e.g. wars between head-mount and wrist-mount). But on the security scale, these sensors will generate a lot of data, which in wrong hands will create a new wave of “hacker productivity”, whether gray-hat or black-hat. There are very few companies which are solely targeting the security aspects of the data that is being generated. Many companies are focusing on the handling of this data to generate analytics e.g. the realm of big data analytics. Just like we have anti-virus or anti-spyware or anti-DDoS companies out there, we need to have some sort of endorsement to generate some new mechanism in order to target the sensors’ area specifically. One such focus that I see is the secure storage of the sensor generated data. But I think the focus should also be on the security of the link among the actual sensor, the on-board processor, and the storage location.

Gathering the sensor data points, putting it in the secure storage, and then using an analytics engine to derive the decision-making is already on the move, for the last 5 years, but on the industrial scale. Since companies are making new devices to be used in the consumer market, the dynamics of this data aggregation, storage, and analytics is to be changed significantly. We already know that sensors are being matured, algorithms are getting more accurate day-by-day, and sensor-data-focused databases are being evangelized, its’ time to create a disruption in the area of big data analytics for sensors.