CloudNav: Transforming the Future of Indoor Positioning

Erik: Johnson Controls is a multi-billion dollar conglomerate with a global footprint. They have a product called Atlas, which is a cloud sensor input solution with artificial intelligence. Johnson needs partners like us to provide them with smart edge-node sensors that they can utilize for their AI engine. In turn, they benefit from a massively parallel processing scalable solution that can take a million nodes and still perform actions intelligently. Our focus is on providing them with an edge product.

Our first product in the market in association with Johnson Controls is a co-defined employee badge which has two versions. The first one is a basic badge which tracks the individual. The second version has a panic feature which the employee can press in times of duress.

Johnson sees our products and system architecture as unique solutions to some of their biggest deployment headaches. In particular, our node-based architecture enables seamless interoperation with any already deployed beacon systems, even if the original systems weren’t originally intended to be used for location. Johnson has broad deployments of lighting systems, smoke and gas alarms and building security systems all capable of emitting BLE advertising packets and integrating smoothly into our overall location system.

What are the challenges that your clients are facing in the indoor positioning landscape? How do your solutions solve the challenges?

Drake: One of our clients, Johnson Controls, did an incredibly detailed report on the product offerings of their partners. The pain points that they identified was the level of accuracy in indoor positioning. Johnson Controls wanted a scalable solution. Some of their clients wanted three-meter accuracy while others less than one-meter accuracy. However, our product offering had both the features, which is a definite advantage for us.

Scalability is also one of the challenges that our clients face. Our clients send a lot of data from the node to a beacon and then to the cloud. For instance, the client has 1000 employees, which means that they have 1000 assets to track simultaneously. At some point, while transmitting data, the clients lose location packets. Since we only listen and transmit X/Y location vector back to our gateway, we offer massive scalability.

Erik: Every tag is going to have a Bluetooth radio. The processor that’s running that Bluetooth stack has some extra resources available. So, the only processing resources we’re using for our solution are those extra resources not being taken by the Bluetooth radio. In a typical architecture, anchor beacons are much more complicated. These beacons either go on a wall or a ceiling as they have to listen to the tag information. All the packets go back to the cloud for processing. So, in a typical system, a tag sends out one packet detected by 25 beacons which goes to the cloud and then comes back. In total, 50 transfers take place from that one broadcast in our architecture. In our architecture, the fixed beacons functionality is very simple; all they have to do is send out advertising packets. Our tags, on the other hand, hear it, calculate a position and send a single packet X/Y to a gateway. Thus, the reduction in traffic tends to be around 50 to 1, and we can scale much better compared to our competitors. The reduced traffic along with the removal of a required round-trip transfers to the cloud (required by other systems) also results in a greatly reduced attack surface for hackers, meaning the system provides a big security advantage.

Please share a customer success story with us.

Drake: A couple of large pharma companies wanted to use location as input for tracking employees and tools that they use. Our clients wanted to figure out two things. First, they wanted to figure out the movement of fixed assets. The second was the analysis of the movement of the assets. We have unique motion expertise using inertial sensors and embedded the software IP into the custom application for our clients. For instance, if the client wanted to do geofencing for elderly people, along with CloudNav can customize a solution for that specific vertical. The same strategy can be utilized for any of the larger deployment and our company is already set up to do custom consulting work for our customers.

What does the future hold for CloudNav?

Drake: We are bringing our multiple version tag-based solutions to production with our partners. Working with our partners, we already have four pretty significant engagements. If we talk about Johnson Controls, they have thousands of salespeople, and they are waiting for us to scale up. In the next six months, we will be doing integration testing with multiple partners and end customers. In 2020, we will ramp up the revenue of our location product lines.