AR is converging with the IoT. Thinkstock / eternalcreative
AR is converging with the IoT.

Why Augmented Reality and the IoT Are Converging

While the potential implications of the Internet of Things are endless, one of the hottest IoT niches is its intersection with AR, says Infobright CEO Don DeLoach.

In this extensive interview, Infobright President and CEO Don DeLoach (who will be speaking at our upcoming IoT Emerge event held November 2-4 in Chicago), touches on augmented reality, explains why the Internet of Things needs broad adoption to work, and the implications of tracking everything from your energy usage to your eating habits.

Please describe a recent IoT project you have worked on.

We are working with a partner, MachineShop, who does a fantastic job in delivering on the promise of IoT in a very real and pragmatic fashion. Specifically, they have software that is extremely efficient that can be deployed on different, and often very tightly configured, edge devices. As such, this software has transformed them, from functioning merely as protocol translation and forwarding, to fully functioning computational event management services that deliver a much more comprehensive set of capabilities to the edge. These services include the interpretation of the message stream and corresponding alerting and triggering, filtering, and even the augmentation of security. This has the net effect of increasing the value of the payload being transmitted beyond the edge reducing the costs associated, and in many cases, reducing the latency associated with actions taken against the sensor messages. This is in production with a variety of users ranging from oil rigs to manufacturing plants.

What do you see as the biggest potential of the Internet of Things?

The potential implications for the Internet of Things are endless across many industries--as examples, smart parking where sensors are used to monitor when parking spots are free; waste management where sensors in the city trash receptacles detect when they are near full, informing city services when they need to be picked up; and audience profiling for online advertising where IoT data could generate a much higher quality profile, which would lead directly to more money.

However, there is one particular area that is starting to pick up steam in the realm of IoT, and I don't see it slowing down anytime soon--Augmented Reality (AR). The vast repositories of data will enable an AR lens into the scenarios in ways that provide near immediate insight at a level of depth unimaginable previously. If you think about all the data points you get from IoT, it is easy to envision building up a historical repository of data including things like street traffic, pedestrian traffic, weather conditions, traffic incident data, building data, and much more. All of this data can then feed augmented reality apps for allowing you to envision and "engage" in hypothetical situations. Take for example emergency responders. They might plug certain variables into an incident as it is unfolding to "see" the prediction of what will happen. This will enable first responders to visualize where the crowds will go, how the flood will expand, where the fire might move and which people and facilities would be impacted, likely saving many lives.

What do you see as the biggest problems involving IoT deployments at large?

For starters, for the Internet of Things to work, there must be broad adoption. You can't have smart cars, smart cities and widely-connected, well-functioning systems if the parts don't fit together, which is a lot easier said than done. Lack of standards must be addressed for global adoption of the IoT to take place. Security also must be taken into consideration. The planet may become inadvertently more vulnerable due to the ramifications of having a more connected world. Increases in cyber crime, or in extreme cases, the destruction of city power grids, could have disastrous impacts on life in the world's most powerful cities.

What kind of policy changes or societal shifts do you think are needed for the Internet of Things?

Data governance has been an issue in many organizations for a long time. But more often than not, these issues have been the toughest to address; who owns the data? Who administers the data? Who determines how data standards are set? The answers to these questions are still open for debate, although they will become a lot clearer, especially on an international scale. The World Trade Organization (WTO), for example, is a likely candidate to emerge as a leader in introducing international governance. There are also key ethical considerations when it comes to the IoT and who exactly owns all that data. For example, what data can and might be collected in the future, and what are the tradeoffs associated with this data? If you are spooked by call data records, then what about your energy usage, or your driving, walking, buying (even eating) habits? One of the things that is cool about the IoT is that the world can become somewhat tailored and much more efficient to you as an individual because the data can be understood and interpreted in the context of what makes your life better-- from energy management to transportation to shopping and more. But for this to work, the data has to be there. And in the hands of the wrong people or organizations, it can certainly pose an increasingly large problem.

What is your advice to other industry professionals looking to deploy an IoT solution?

While the data growth in IoT, and for that matter, the overall growth in deployed IoT systems remains relatively small compared to almost any projection, the consensus remains strong that data growth will be enormous. The key for any professional looking to deploy an IoT solution is to make sure that solution leverages the underlying value of all of the data to translate it into insight that begets action. And the best way to ensure this is through a high-value approximation approach, which can be used to gain equivalent insight to exact queries while overcoming the prohibitive time and costs associated with continuing with traditional models. Rethinking the problem using statistical metadata offers professionals a compelling opportunity to overcome the mounting scale barriers by drastically reducing the resource requirements and query times to enable previously unattainable opportunities.

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