Far beyond asset tracking: why location information matters in IoT projects

Location information is an essential part of every IoT project. You could even say it is essential to know the position of a thing, as this gives meaning to condition information collected for millions of connected devices every day. In this context, you may be familiar with the term “asset tracking.” It describes a solution that helps you know where your assets are – and find missing ones.

Geo IoT goes much further by combining localization and IoT technology . Not only do you know the precise location of an asset, you can also monitor its condition in real time. Freight companies, for example, rely on Geo IoT to monitor the condition of their goods in transit. By collecting information from your things, you can analyze who uses them how and when. This, in turn, makes it possible to trigger events and alerts, or set up access for certain users.

An infographic showing the difference between asset tracking and Geo IoT.

What are the differences between asset tracking and Geo IoT? A power tool provides clear answers.

Next-generation asset tracking

Geo IoT combines position data with additional sensor information. This opens up great opportunities for creating new geo-aware solutions .

In retail, the tracking of shopping carts allows you to analyze the dwell times and movement patterns of customers in a store. Why not leverage this data to optimize product placement?

In agriculture, locating a tractor regardless of its manufacturer can allow you to identify how tractors are used and how much distance they have covered. In addition, foresters can pinpoint and track stacks of timber and forestry tools. This is crucial given the rise in timber theft.

In aviation, geofencing ensures that specific pieces of equipment will remain in certain locations – and they will be on hand for maintenance tasks, if necessary.

In health care, monitoring the data on equipment use can make certain that treatment is nonstop and more efficient.

In manufacturing and logistics, the tracking of pallet trucks and routing of workers results in efficient workflows and production processes.

There are many examples throughout every industry. There is tremendous potential, but exploiting all that Geo IoT has to offer is more complicated. Customer expectations infrequently correspond to what localization technologies can currently deliver. We are frequently confronted with the wish for very accurate real-time tracking – using existing infrastructure components and localization technologies that work well together – all at a low price.

In reality, however, the technology landscape is highly fragmented. Every vendor adopts its own approach; environmental and regulatory restrictions impact your choice of a corresponding technology.

Ultimately, people must accept a compromise between a company’s requirements and a localization technology’s capabilities.

Making a success of Geo IoT

Irrespective of the localization technology you plan on using – whether it is GPS, GSM, Bluetooth, Wi-Fi, or some other solution – there is no general-purpose technology that will always meet all requirements.

Would you like to learn more? Based on our experience acquired by helping customers deliver location-based solutions, we have identified seven essential factors for adding value using new geolocation solutions in any industry.

More on Geo IoT

What is Geo IoT? And what are the current applications of Geo IoT in the industry? Check it out here

You want a quick introduction to Geo IoT that summarizes its benefits and challenges? Watch the video “Geo IoT in 1 minute”

7 factors for getting the most value from your Geo IoT project: Read blog post

 

About the author

Johanna Konrad-Mausser

Johanna Konrad-Mausser

Johanna Konrad-Mausser has been a Product Manager at Bosch Software Innovations GmbH since 2016. She is responsible for product and portfolio management for the IoT General Projects and Smart City Product Group and focuses on developing new product ideas and business opportunities. Before taking up her current role, Johanna worked at Bosch Corporate Research where she focused on business model innovation in the context of big data and data mining. Johanna holds a degree in physics from the University of Stuttgart.