A Sensor is Only As Good As the Data Gleaned from It

Modern business moves at the speed of technology. Today, it is all about data. Gathering and utilizing data is a matter of combining scientifically advanced sensors with computer software capable of figuring it all out. What many companies are discovering is that their sensors are only as good as the data gleaned from them.

Imagine being able to collect the equivalent of one ton of paper in electronic data. Imagine that the data covers hundreds of different data points on thousands of different topics. What could you possibly do with it all? A lot, if you knew how to process it. Otherwise, it is kind of useless to you.

This is the big data problem so many commercial enterprises face. There are plenty of sensors to choose from, sensors that can tell enterprises just about anything they need to know. Yet none of them is of any value if the people using them do not know how to collect and analyze data.

From the Simple to the Complex

One example of an amazingly simple sensor is an RFID sensor. Such sensors are pretty commonplace in retail these days. Objects are fitted with RFID tags that contain inventory information. They are then scanned and tracked throughout the supply chain – from the point of receipt at the warehouse until the customer walks out the door with a tagged item.

This sort of technology works extremely well thanks to its simplicity. Tags and sensors produce a limited amount of data that is easily manageable with rudimentary software. But as one moves up the ladder of complexity, sensors and the data they produce become equally complex. Then it becomes harder to glean useful data.

Imagine a computer data center with thousands of servers. Management could deploy a range of sensors to help them determine when a particular server starts acting up. They could have a sensor keeping track of each server’s temperature. Other sensors could listen for the sound the servers make. Regardless of the number and types of sensors deployed, technicians have to make sense of the data sensors produce. This is where signal processing comes into play.

Getting Rid of the Noise

Every kind of sensor used in commercial operations produces some sort of signal, explains Rock West Solutions. Signals can take a variety of forms. One sensor can produce an audio signal while another produces an image. Still another sensor can produce an ongoing stream of numerical data. The goal of signal processing is to take those signals, remove the noise, and present only useful data.

Noise in the signal processing environment doesn’t have to be audible. Noise is defined simply as any information that isn’t necessary. For the purposes of illustration though, data from an acoustic sensor works well to illustrate the point.

Let us say a data center owner placed acoustic sensors around the facility to listen in on individual servers. A server makes a certain noise when running properly. As such, an acoustic sensor can continually monitor the sound a particular server makes and send a signal to connected computer software.

That software continually monitors and analyzes the signal. It continually processes the signal to get rid of all the ambient noise so that it can concentrate just on the sound the server is making. If the server makes an unusual sound, the software alerts human technicians of a potential problem.

It is examples like this that show us just how advanced modern sensors are. But any sensor, regardless of its function, is only as good as the data gleaned from it.

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