Sensors: Like Your Car's GPS

When it comes to brass tacks, the point of a sensor is to get information about a point in space from either a third-person or embedded view. Third-person sensors are essentially ones that you set up independently of the thing you are trying to capture, whereas an embedded sensor is just that: embedded directly in the device.


Third-person, for example.

A good example of this is a camera. It’s able to grab information from an environment and, depending on the camera, with high amounts of resolution and consistency. But with a camera, if you’re trying to identify individual patterns, it’s hard to remove all the surrounding noise. Not to mention even harder to pinpoint specific actions unless you have a 360 degree view from every possible angle.


So how is an embedded sensor different?

Having a sensor directly embedded on a device allows for a significantly closer view, which allows for even the most microscopic of vibrations, naked to the human eye, to be picked up. It allows us to accurately pinpoint motion, light, heat, pressure, etc. and generate much more quantifiable data.


If the personal computer is like a car, what are sensors?

What I mean by “the personal computer being like a car” metaphor, is that a computer is a way through which you can train your product, and get it driving down a significantly broadened set of roads, much quicker. You can simply get in your car and go wherever you want.


But what if you wanted to go to a specific location?


We think the sensor could be considered the metaphorical GPS for your product. It allows you to take a load off your mind, without having to think about how to get to where you want to be - the sensors provide all the appropriate information.


Sensors can be seen as the fabric that connects us. Each sensor is able to connect us even deeper to the internet, deeper to those around us, and deeper to ourselves. Just like the GPS is an effective way to simply get from A to B, sensors allow us to confidently navigate through our decisions with quantifiable metrics to act on objectively.

John David Chibuk

Toronto, Canada |

Entrepreneur in machine learning and sensor based software development (>10 years). Background in engineering, tech with professional experience in North America and Europe.