This is the first blog in the "Power of Where" series, authored by Brian Salisbury, VP of Product Management at Comtech Telecommunications Corp.

Every day, an incredible amount of data is being created and captured by sensors. The number of these sensors that are connected to the Internet is also growing rapidly every day. One of the great promises of the Internet of Things (IoT) is that this data will be captured automatically by a broad range of smart “Things” that will be distributed everywhere. Machine learning and artificial intelligence platforms will then consume this data and take actions on our behalf, as well as create amazing insights to help us make the world a better place. But many of those actions and insights won’t be that useful without the context of location. This is what we mean by the “Power of Where.”

This posting is the first in a series on this topic, in which we will discuss why location is such an important contextual element, how location is typically determined, and why many traditional approaches don’t work that well in IoT use cases. We will also share our thoughts on a different approach for location, and how it can conserve energy, minimize device memory requirements, reduce communication bandwidth, and support a broad range of networks. We welcome your feedback and questions, and invite you to share your insights and experiences on the subject.

Let me illustrate the idea of data records needing to be location “tagged” with some basic examples. If an air temperature sensor reports a reading of 23 degrees, it is obviously important to know whether the reading is in degrees Celsius or Fahrenheit and what time the measurement was taken. That’s interesting, but it’s not very useful without additional context. Where was the air temperature sensor?

• Was it outdoors? 23 Celsius is a very comfortable temperature, while 23 Fahrenheit means roads could be icy.
• Was it indoors? Again the difference between below freezing and normal room temperature is meaningful, and leads to different actions being needed.
• Was it inside a refrigerated produce storage area? In one case, the temperature is too low and produce may become frost damaged, in the other case the produce will spoil for a different reason.
• Was it in a refrigerated storage on a truck rolling down the freeway? Determining the best place to intercept the truck will require frequent location updates, not just an initial position.

Clearly context is critical to understanding, and context that includes “Where” is more powerful context.

When important assets are left unattended, there is risk that they will be lost, misplaced or stolen. Having the ability to request the current location of the asset is one way to keep track of it, but when there are hundreds, thousands, or many more such assets being managed, a more automated approach is required.

This is where concepts like geo-fencing come into play. If you can define an area where the asset is supposed to be and only receive alerts when the asset moves outside that area, you will significantly reduce the volume of requests.

Furthermore, once the device’s position is initially established, if the positioning solution is only activated when motion of the device is detected, you will significantly reduce the amount of time that energy is being consumed to determine its location. Less energy means the power source can be smaller and the cost can be lower.

In our next post, we will cover the primary methods that can be used to determine location and their pros and cons in IoT use cases.

Brian Salisbury is VP Product Management at Comtech Telecommunications Corp, which is an mbed Partner. Comtech Telecommunications Corp. designs, develops, produces and markets innovative products, systems and services for advanced communications solutions. Comtech sells products to a diverse customer base in the global commercial and government communications markets. Comtech believes it is a leader in most of the market segments that it serves.