With end-to-end IoT solutions and services,
we are the people powering IoT.

Blog Post

Ford’s “Smart Mobility” shows M2M as key stepping stone from lab to commercial innovation

Posted by Norman Miglietta on 08/13/2015


Even as we see that Google’s autonomous car is getting into more accidents of late (most recently in early July), nearly every case proves out that the self-driving car is not at fault. Rather, these incidents expose an extreme error-prone and inattentive driving public; perhaps, for that reason, self-driving cars could be said to be too smart for their own good. 

Be that as it may, the fact is the same sensors that are put into play for autonomous cars are also making the cars we drive safer, and in many ways are making the very roads we drive on safer as a whole, too.

Specifically, a number of intriguing connected car projects between Ford Motor Company and Georgia Tech University recently caught our attention. The first is probably best classified as a matter of convenience more than one of safety, but it speaks to the growing ability of a car to sense its surroundings and make recommendations and decisions on behalf of its occupants.

Called Parking Spotter, the gist is this. Sensors embedded in the car are able to provide the driver with intelligence about open parking spaces in their immediate vicinity. In practice, the car becomes a “probe” for open parking and would be able to marry the information to the car’s navigation system so that, more than simply mapping a driver’s route to his or her destination, it guides them directly to an open parking space close by.

Ford gathered data to illustrate the urban challenge of parking: only about 12 percent of drivers looking for an open space at any one time actually find one directly. Put another way, that’s more than 70 million hours wasted each year looking for parking. Translation—it’s a crap shoot. 

Putting the frustration factor aside, this constant hunt for parking by city drivers is one of the biggest contributors to congestion, which in turn creates a cauldron for more potential accidents to occur. The process also contributes to fuel consumption and carbon dioxide emissions, both of which stand to be lessened if a Parking Spotter assistant comes to bear.

The next application holds significantly more potential for safer roads in our view, but perhaps not quite in the way you’d expect. Ford calls this one Remote Repositioning, and it is essentially the idea that someone can sit in an office, or a studio, or in their living room and remotely drive a vehicle via streaming video over LTE networks. 

As Ford’s Dave McCreadie puts it, LTE has enough capability in the way of bandwidth and latency that we can stream live video and data from a vehicle to a remote driver, and stream that driver’s actions back to the vehicle to control it.

Initial testing is of course being carried out with golf carts in a controlled environment at Georgia Tech, but the implications for remotely driving a person’s car are a much greater sight to behold. Ford notes the business benefits (boosting productivity for a roving car rental employee, or a valet service where the valet parks your car without the valet having to get in it) and the opportunity to improve quality of life, where disabled or elderly persons could be granted mobility via such a machine. 

We, however, envision an even more noble use, mainly as a means to dramatically reduce the incidence of DUI. Imagine if cars were one day equipped with this technology and there was a service standing by to, essentially, drive you home in your own car if you over-imbibed. The concept could go even further, where the car itself could “breathalyze” its driver after a night out and automatically turn itself over to a remote “drive-me-home” service if BAC levels were not where they should be.

These are heady thoughts to be sure, but the fact we can even think them comes down to an evolution of M2M sensors and devices, which not only take advantage of increased LTE network strength, but also now contain a level of mechanical sophistication to do what’s asked of them, in real-time and every time. Without that, none of these applications would go further than an engineer’s train of thought.