The Internet of Moving Things: Where Big Data meets mobility
Robin Chase doesn't buy into the hype about mobile — at least when mobile is associated with portable gadgets like smartphones.
But the rising stock of technological tools related to smart cities and sensor-enhanced transportation networks has led to a market for larger-scale mobility challenges that the ZipCar and Buzzcar founder can get behind.
"It’s kind of funny. When it comes to mobility, people are usually talking about things that aren’t moving," Chase told GreenBiz. "I can get my Gmail wherever I am, but the object itself isn't moving when it’s doing the interaction."
With her newest venture, Veniam, Chase is taking aim at what she sees as a logical, if a bit more technologically-challenging, next step: Connecting as many of the world's 1 billion moving vehicles to cellular and Wi-Fi networks as possible.
For consumers, the company's technology installed in public buses or cars provides free Wi-Fi hotspots. But the real long-term potential lies in the data generated by sensors being installed on cars and transportation infrastructure, which could be tapped for new insights on fleet management, heavily-trafficked corridors, peak drive times and other transit metrics.
“All these sensors that are supposed to be around a city — how does that data get collected and actually into the Internet and worked on?” said Chase, who coined the term the "Internet of moving things" to situate her company in the technology lexicon.
The mobility twist on the Internet of Things trend, which has buoyed connected-home products from companies like Google's Nest and General Electric, recently helped Veniam close a $4.9 million Series A funding round. Intially dreamed up by Portugese professors João Barros and Susana Sargento, the company's hardware, software and cloud products are currently deployed in 600 vehicles in Porto, Portugal, as well as ports in the San Francisco Bay Area and Singapore.
Silicon Valley startup Veniam launched its vehicle-to-vehicle and vehicle-to-infrastructure communication products on public buses, cars, taxis and garbage trucks in Portugal.
Chase said her involvement as co-founder and chaiman of Veniam was driven by dual ambitions: to lower the cost of transmitting data and to better motivate sustainable behaviors.
The company aims to help drive down the price of connecting sensors to a network by leveraging existing Wi-Fi hotspots and creating new ones, rather than relying on the costlier default of beaming a signal up to a sattelite. The utilization of "shared assets" is a carry over from Chase's days at ZipCar, when she saw first hand the higher return on investment that comes from shared cars.
Once urban connectivity is enhanced to allow for more data transfer, Chase is intrigued by the potential availability of more targeted traffic data to support sustainability-minded policy goals. Two possible strategies are dynamic pricing for peak driving hours or especially congested roads — an economic imperative for governments looking to augment declining fuel taxes that are relied upon to finance transportation infrastructure.
"I’ve known that was one of the things I wanted to work on so that we could actually charge people the right price when they drive down the street," Chase said. "That sounds very putative, but I mean it in an informational way. Some people need to be on the road at 6:00 p.m. on a weekday, but a whole bunch of us just decide to go the mall at that time and we don't care."
Another financial driver for Chase's interest in Veniam is the overarching cost of infrastructure projects. The goal with after-market products added onto infrastructure that has already been paid for, like public buses, is to make technology upgrades less time consuming and costly.
And then there are more niche use cases for that technology once it's up and running, like embedding sensors in communal trash wells in Europe and connecting garbage trucks to a network. Ideally, garbage trucks would only be signaled to collect trash when a large bin is full, which Chase said could reduce pick-up trips by as much as 30 percent.
In the meantime, however, major questions remain to be answered about both technical nuances of Big Data applied to mobility — which metrics are most valuable, and how can they be utilized? — as well as more finicky issues around data ownership, security and consumer trust in new business models.
The push to better leverage transportation data in cities comes during a period of much bigger upheaval in urban mobility.
There have been big advances in electric vehicles, connected cars, bike sharing, new forms of public transit and the advent of sharing economy companies like Uber and Lyft. The next hurdle is figuring out a way to get those disparate systems working in tandem to more radically improve efficiency and curb carbon emissions.
“We’re at a very pivotal place in transportation," said Susan Shaheen, associate professor of civil and environmental engineering at the University of California, Berkeley and co-director of the univeristy's Transportation Sustainability Research Center. "Data are now available, and the sensing technology — the ubiquity of these technologies is really changing dramatically now, which can enable a lot of things to happen."
Shaheen is particularly intrigued by the possibility of more advanced, personalized real-time transportation planning.
Just as smartphone apps like Google-owned Waze currently suggest alternate driving routes based on current traffic conditions, she describes a scenario where a transportation aggregator also suggests real-time public transit options, ridesharing, bike sharing, walking or other modes of getting from point A to point B.
Veering into another tech field du jour, machine learning, Shaheen added that another potential application could be a program that analyzes recurring travel patterns and then recommends potential alternatives — like a bus route that overlaps with a daily car commute.
“How can these devices learn by sensing what you’re doing from a geographic standpoint, from a timing standpoint… and suggest options?” she said.
While real-time data could be great for individualized trip planning, Shaheen adds that there is a bit of a balancing act to be negotiated when it comes to avoiding being overwhelmed by data.
For example, algorithms might only make it necessary to penetrate 20 percent of the market in a city to get an accurate picture of congestion that can be used as a basis for dynamic pricing. But constant data collection and transmission could be lucrative for businesses looking to build out geographically-tailored marketing profiles, or for governments aiming to more thoroughly map transit patterns or improve service delivery.
Given some consumer pushback on a lack of transparency when it comes to how personal data is used by online service providers, the trick will be amassing data without alienating the consumer.
“We’re going to move into something more of an opt-in [model] and see more incentivization,” Sheehan said.
Gamification and financial incentives like free bus passes are two potential options to reduce the necessity of single-driver car trips. While cities like Paris, San Francisco and San Diego are already embarking on sophisticated data modeling or building out alternative mobility infrastructure, Shaheen said real progress will likely ultimately be reflected by consumer purchasing choices.
“The mechanism that we are quite confident is causing these dramatic shifts is the sale of the car or the decision to forgo a car. Fixed costs are then converted to variable costs," she said.
The core question for transportation observers: “Is this causing someone to change their lifestyle vis-à-vis the automobile?”
While those working in mobility are now starting to think beyond traditional metrics and car dependence, Chase also sees that the road for infusing Big Data into mobility — much like the curve of implementing new data analytics in fields from human resources to logistics — is likely to be a long one.
"It’s a vision without reality right now," she said.