Benefiting from intelligence at the network edge
Written by: Sam Fenwick | Published:

Paul Steinberg, CTO of Motorola Solutions, speaks to Sam Fenwick about his company’s efforts to use AI and machine learning to bring the right data to the user in the right way

Paul Steinberg presides over a huge range of research and development activities, ranging from RF engineering and wireless network architectures to drones and robotics. He also manages Motorola Solutions Venture Capital’s portfolio and plays a key role in managing Motorola Solutions’ intellectual property.

One of the things the company is moving towards is a virtual partner – a combination of AI and natural language processing, which allows someone in the field to verbally request information and give commands without talking to a human. Part of the thinking behind this is that people speak faster than they can type, and the need for field workers to stay aware of their surroundings.

“The way you and I consume [mobile data] is a slab of black glass, [but the] fundamental imperative [for a police officer, etc] is eyes-up, hands-free. That slab of black glass [is] exactly the opposite: eyes-down, hands-busy. A big part of how we’re navigating this problem is around ethnographics and human factors research – living a day in the life of our users and then [working] with the technologists and designers.”

The company is working on transcription, translation, and audio and speech analytics. “We invested in a company called API.AI and they gave us a programmable platform for natural language processing, so we could create a contextual dialogue. That company was acquired by Google last year, but we have learned a great deal from it and [now] a lot of the basic building blocks are out there for us to use.”

Some of Motorola’s customers are already making good use of text to speech. One bus company keeps passengers informed of delays by sending text messages from its control and dispatch system to on-board two-way radios, which are then converted into spoken announcements.

Steinberg believes more intelligence can be pushed to the edge and explains how it could significantly reduce the load on broadband networks, giving the example of using officers’ body-worn videos and facial recognition to look for a missing person. Rather than streaming all the video to a command centre and doing the facial recognition there, “what if I could push a classifier down to the edge, turn that camera on and have it look for someone who matches the basic description?”. Then only the few faces picked up by the cameras that match the description need to be sent “to the cloud for the final determination as to whether there’s a match”. Steinberg adds that last year, he opened a research centre in Tel Aviv focused purely on AI, and some of its work is along these lines.

Another area where intelligence on the edge of the network can be used is responding to an officer’s gun being drawn from its holster, with elevated biometrics and geo-fencing that recognise the officer is not in a firing range. “We can turn on the body-worn video camera, perhaps activate it in streaming mode, switch audio communications to be covert [and] we might trigger an emergency or notification to command and control.”

While many other companies have released dual/multi-mode handsets that combine LTE with PMR, we have yet to see one from Motorola Solutions. Steinberg says it built a converged device about three years ago: adding mobile broadband to an LMR radio “just to give it a data path” and building “a heavyweight smartphone”. It is working to provide a highly secure version to a military customer in the Middle East.

However, “it’s not obvious to us [that a dual-mode device is the] best consumable form factor for the end-user. As we got into this research, lots of questions materialised.”

“We’re starting to do a lot of work now on collaborative devices. One of the ways we talk about it is the notion of hub and peripherals. The hub might be the computing platform, the core radio or radios, but [the user might interface] with the technology [through] wearables, sensors arrayed around the hub.”

There is also the mismatch between the speed of LTE and PMR, and size and weight considerations. “It’s not unusual for our systems and devices to be used for 10 years, [while] the half-life of a smartphone is months. [Dual-mode devices seem] logical. But then you get into the physics and [once you’ve added LTE or PMR], it doesn’t look like [the original device] any more.”

Given mission-critical communications’ more demanding requirements, does Motorola Solutions focus on addressing them, and then trickle down features into business-critical solutions? “What I like to do is almost the reverse,” Steinberg says. “In areas where we’re still perfecting the technology, often it’s easier to innovate with the commercial application and then extrapolate the learnings from there into the mission-critical environment.

“Fundamentally, the problems are not that different – consuming information on the edge in an eyes-up, hands-free fashion, monitoring environments, fusing environmental data with individual data, [having] intelligence at the edge, [the use of] multiple networks and the collaborative applications that we built around voice; group-based rich-media messaging, white-boarding and video-sharing.

“We have a branch of study called high-velocity human factors – the more stress or distraction you’re under, the less ability you have to do other things. When you need the technology the most, you have the least capacity to extract what you need from it. This is back to where context becomes important. The more [AI] can sense about the human condition and what’s going on, the more I can make intelligent decisions about how to get the right information to the right person at the right time and in the right way.

“A lot of work is conversational. If I can speech-to-text transcribe it, I’ve got a record that I can refer to. Now we start to blur this platform with the voice platform, and suddenly they become collaborative.”

Another trend is polarisation within the PMR handset market, with the middle ground between those requiring cost-efficient voice-only terminals and those needing feature- and application-rich radio systems being eroded. Speaking of the latter, the company is looking to expand and improve upon Capacity Max, with early adopters and application partners seeking more functionality.

Motorola Solutions demonstrated the use of VR headsets and eye-tracking for control room operators at PMR Expo. However, at Critical Communications World, it took a different approach – mixed reality using Microsoft Hololens for incident scene visualisation. Steinberg says the use of VR to give an immersive command centre setting was “the right idea, wrong implementation… people don’t want to be cut from their ability to communicate with their surroundings or be in a virtual world, but they want the augmentation”.

On the predictive policing front, Steinberg discusses a risk-terrain modelling approach “based on the environment. So, things like abandoned vehicles, what kinds of businesses are in certain areas, dosing it with weather. It is a more accurate predictor of crime. It tends to be a lot more objective, it’s not related to the human being and there’s no real danger of bias.”

Steinberg’s enthusiasm for AI and machine learning extends beyond his role at Motorola Solutions. “It’s interesting because of [the potential for unintended consequences] and the profound implications for humankind. We’re all familiar with automation eliminating manual labour, but AI and machine learning is at the point where routine cognitive tasks can be done better with technology.”

Motorola Solutions may be best known for its hardware, but a lot of work is going into trying to ensure that device, data and user work in harmony during stressful situations. It will be interesting to see the fruit of its labours in the years to come.

CV - Paul Steinberg
Paul Steinberg serves as senior vice president and chief technology officer for Motorola Solutions. He oversees development and execution of the company’s technology strategy, vision and venture investments. Steinberg joined Motorola in 1992 and most recently was chief architect for integrated command and control and private broadband solutions for public safety systems. Prior to that, he served as chief architect for carrier wireless infrastructure broadband products in Motorola’s wireless networks business. He is a member of Motorola Solutions’ Science Advisory Board Associates (SABA) and holds several US patents.

Steinberg earned a bachelor’s degree in computer science from Illinois Benedictine College and completed graduate studies in computer science at the University of Illinois.

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