For IoT, alternative location services are better than GPS

Traditional location positioning such as GPS isn’t going to be suitable for a Location of Things world filled with Internet of Things (IoT) sensors, say experts. The centralized, anchor-like system we use now, as found in GPS, mobile network cell tower positioning services, and Wi-Fi-based location positioning, is going to be a problem. The usual suspects being bandwidth, excessive power use, and cost.

The problem is IoT devices are required to communicate with positioning anchors, whether it be satellites or radio towers. That’s bandwidth-intensive; it can use a significant amount of power to cover the distances, as well as to power the multiple chips needed. The system is also conceivably susceptible to congestion as the numbers of devices increases — projections are for billions and billions of IoT things worldwide, ultimately.

The solution is to get the IoT sensors to communicate among themselves, scientists from Tufts University say. Forget about accessing distant resources for a locating ping, and simply use an algorithm to figure out where the device is in relation to other sensors, they say.

“Centralized positioning can become unwieldy as the number of items to track grows significantly,” Tufts researchers say in a news release on the university’s website. So, get “the devices [to] locate themselves without all of them needing direct access to anchors.”

In this case, the scientists are talking about within a 5G wireless network. But the decentralized principal, conceptually, will relate to other networks, too.

Indeed, I’ve written about theoretical, self-configuring ad hoc networks before. That’s where sensors learn on the fly about where other nodes are within the network rather than being told. It uses a technique called “random walk” and is based loosely on how ants learn of other insects nearby — by bumping into them. Explorer ants count other ants to create a sample.

How Tufts’ location-services concept works

Tufts’ non-centralized location-services concept uses a device-to-device algorithm. It’s tricky because the assumption is the device is mobile — one needs to calculate and obtain a track in real time. “The key is to obtain positions rapidly,” the researchers say.

But they say the concept works.

The sensors calculate their location by measuring their position to a center of mass of other devices, or one other device, rather than to a distant, stationary anchor, such as the aforementioned cell tower or router. It gets more efficient the more nodes you add, unlike traditional positioning.

Additionally, it removes “the need to install a lot of transmitters [anchors] in buildings and neighborhoods,” says Usman Khan, associate professor of electrical and computer engineering in the School of Engineering, in the release. That saves money.

Cost reduction is one major advantage to reducing the number of hard, location-services anchor points.

PoLTE Corporation’s software-based location services

By using just software and radio signals for location, PoLTE Corporation, says it can reduce energy use in IoT and, along with it, cost. Unrelated to Tufts’ locationing, PoLTE’s software-based location services — which it’s pitching to wireless network operators, such as those planning on building out 5G — combines cloud services with “computationally complex location algorithms [that] can be offloaded from the device module,” a representative told me in an email.

PoLTE’s system uploads the location data to the cloud, and that’s where the heavy processing takes place. It removes the load off the sensor. Thus, as with Tufts’ proposal, it is also taking location-services beyond traditional global navigation satellite systems (GNSS). PoLTE claims its cloud-based “location engine” algorithm “can not only efficiently locate Internet of Things and mobile devices in real time, but do it seamlessly as they move between indoor and outdoor environments.”

By not using a group of chipsets, like GPS, plus sensor, plus microprocessor, and so on, it “reduces battery drain to a fraction compared to GPS-location or other technologies,” PoLTE says on its website. Fresh, mobile Location-of-Things data is going to become more important. Self-driving cars is one example that can use such a system.

“The need to provide location awareness of every device, sensor, or vehicle, whether stationary or moving, is going to figure more prominently in the future,” says Kahn.