HomeTECHNOLOGYEmbedded Machine Learning: The Other Smartphone

Embedded Machine Learning: The Other Smartphone

Some predict the end of the economic model of mobile apps, as usage has stabilized overall. But machine learning (ML) research promises an exploration of smartphone sensors and unparalleled technical opportunities. We are entering the era of embedded ML.

Some predict the end of the economic model of mobile apps, as usage has stabilized overall. But machine learning (ML) research promises an exploration of smartphone sensors and unparalleled technical opportunities. We are entering the era of embedded ML.

Stabilization In The World Of Mobile Applications

Commentators speak of an already outdated mobile era and users’ disaffection with apps. If there is disaffection, it is related to the increased competition in the small market for mobile application stores. To stand out today is a real challenge, that’s for sure. Ten years ago, it was the El Dorado for mobile projects. Remember the expression “There is an app for that! “.

The world of the mobile app would have finished eating its white bread. Redundant offers, lack of relevance, sometimes unconvincing achievements… help make consumers more demanding, less patient, and above all, more selective. Users are less inclined to be early adopters, have selected several referral applications, and only slightly deviate from them.

In short, a market in danger should we conclude. And yet. On the professional side, the mobile application has never done so well. The smartphone is the new workstation in business and promotes the mobility that works, driven by the software and hardware power of devices. In addition, let’s not forget that the appetite for the device is still there. 78% of the population of industrialized countries own at least one smartphone.

Technological Capabilities Still To Be Explored

Is there still space to occupy in the world of the mobile app? To answer, let’s take a look at Uber’s little story. To make their idea of ​​a shopping reservation platform a reality, the creators of Uber first sought to install an order-taking box in cars before turning their attention to the smartphone, which has advantageously replaced the investment and propelled Uber to the heights we know.

Uber, Instagram, Snapchat, and Whatsapp have in common, not Mobile First, but Mobile Only. For each of them, the mobile device is the cornerstone of the business process. However, we have not yet explored all the possibilities this mini-computer offers, as powerful and complete as the smartphone.

What are we talking about? Accelerometer, gyroscope, magnetometer, altimeter, barometer, pedometer, sound level meter, facial recognition sensor, microphone, camera… more than thirty sensors with which new services will soon emerge.

Embedded ML, The Future Of Mobile, Uses

Health projects that are still confidential can transform the smartphone into a specialized measuring instrument, making it possible to collect data to aid in the diagnosis via the measurement of lung capacity, for example. The camera directed with the flash on the finger’s skin makes it possible to assess possible anemia roughly. 

The detection of osteoporosis is made more accessible by using motion sensors. And to oversee the entire processing of this data, machine learning in the background. Both Apple and Google, through their R&D work, invest heavily in ML. Core ML for Apple, ML Kit for Android are software systems embedded in the smartphone, capable of analyzing and processing the data collected by the sensors and building models. 

All this locally, security and confidentiality of personal information oblige. Users and their smartphones are hubs of moving sensors. Uses will never stop changing, and the projects are ambitious, excite the imagination, and push back limits that we thought were well established. The smartphone is really in its infancy.

Also Read: How To Govern Data With Machine Learning Tools

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