AIRSAGE. ACCREDITED DATA VALIDATION
AIRSAGE IN RESEARCH and industry perspectives
As part of the I‑70 Polk-Quincy (PQ) Design project (70-89 KA-1266-02), the Parsons Brinckerhoff (PB) team was tasked with analyzing the peak hour conditions in 2025 to assess the impacts of closing I‑70 during reconstruction of the I‑70 PQ viaduct.
After review of the existing Topeka/Shawnee County MPO model and discussions with KDOT, it was determined that the daily model was inadequate to evaluate peak movements. It was concluded that AirSage would be able to best provide existing daily and peak conditions using their proprietary cell phone data capture methods.
AirSage data gave the project team two major contributions to the Polk-Quincy Viaduct Study. First, it provided a means to evaluate the MPO travel demand model and second, it allowed for the addition of a peak hour component to the model, which did not exist. Additionally, the AirSage data compared very favorably to the other observed data in the study area, showing the sample to be reflective of the full population.
Being able to evaluate the model against current observed data meant analysis from the model for the study was done with much greater certainty that results would be valid and conclusions meaningful.
The paper is authored by Andrew Coe, Senior Planner, Parsons Brinkerhoff
To view the full paper, click here.
Modern passive data collection methods are transforming the travel planning landscape because of the ability to provide comprehensive insights into urban, rural, regional and multi-state travel patterns with a high degree of confidence.
ITE Journal covered Transforming Data into Meaningful Information in their August 2014 issue.
The article covers:
- The challenges of rural traffic
- New passive technology
- Census data overlay options
- Data accuracy and privacy
- Advantages of cellular data
The journal also includes a feature article titled "The First Penguin Through the Big Data Ice Hole: Using Cell Phone and GPS Data to Improve Integrated Models." This article focuses on the development and application of each model level and how the availability of big data influenced the overall modeling and analysis process.
Check out both full articles from a portion of the August ITE Journal here and how planners can develop travel models in less-populated areas based on actual, current, local data rather than purely synthetic models and more...
To view the full issue or become a member of ITE, click here.
The Urban Transportation Monitor recently published an article on a traffic-reduction project conducted by NuStats, a research consultancy specializing in complex social research studies. NuStats needed data for their study on Sierra Vista, Arizona that would 1) augment and 2) validate data that had been gathered using a traditional travel study.
The need for data extended beyond city-specific boundaries to include outlying areas such as military bases. Capturing regional data like this has, historically, required expensive and time-consuming long-distance travel surveys.
Check out the full article from a portion of the July Urban Transportation Monitor here and read how NuStats was able to significantly reduce their resources spent on projects like this one.
To view the full issue or to subscribe to the Urban Transportation Monitor, click here.
Bill and Melinda Gates Foundation: Mobile Data Study
AirSage was proud to be a part of the Bill and Melinda Gates Foundation study on the ways mobile data can be used to reach development goals. With the help of Cartesian, a consultancy specializing in the communications and technology markets, the foundation created this report for Financial Services for the Poor, a program broadening the reach of digital financial services in order improve the lives of those that live in poor and rural areas.
Along with AirSage, more than 50 other interviews were conducted with technology service providers, researchers, and academics and other industry associations including UCLA, the Brookings Institution, Harvard, and Caribou Digital.
As with many forms of research, it is extremely difficult in poorer nations to gather necessary mobile data accomplished due to the significantly high amount of pre-paid devices. AirSage sees all signaling activity… both pre- and post-paid. And in addition to offering scale difficult to recreate through other research, AirSage data is unbiased.
Passive, mobile data is one of the only large-scale, digital sources that is able to reach vast portions of low-income countries. Similar to Pew Internet Project’s research, 90% of American adults own a cell phone.
This report details similar findings that show increasing populations with access to mobile phones across the globe – including developing countries such as Kenya, Nigeria, Uganda, Bangladesh and Pakistan among other countries across Africa and APAC. Some show cell phone ownership even as high as 50% where the average daily wage is less than $1.
Similar to AirSage’s core principles, the report highlights the importance of how mobile data, like ours, can help enrich and advance societies through developmental and improvement efforts like disaster relief programs and Bill and Melinda Gates Foundation’s Financial Services for the Poor. But, just as important as cultural improvements, anonymization standards must advance right along side with the advancement of the technology.
While AirSage provided data and background for much of the 52-page report, we are specifically mentioned on pages 27, 28 and 46.
Young Professionals in Transportation (YPT) launched its Innovator Series in 2014, highlighting people and organizations changing the transportation industry. AirSage is excited to be one of the first in this new series featuring its own Matthew Martimo, VP R&D.
Arthur Pazdan, YPT’s Deputy Vice Chair of Communication speaks to Matthew about:
- the current state of population analytics
- where the transportation planning industry is heading
- where AirSage is going in the next five years and
- how its innovative wireless signaling analytics is changing the transportation industry
Matthew explains that as a transportation modeler, instead of synthetic data to solve basic population movement questions, he wanted real, live data. “When I joined AirSage over a year ago it seemed like this data was a unicorn, people didn’t believe it really existed. Over the last year and a half part of my job has been to educate people to let them know our data is a real thing and they can have direct answers to some fundamental transportation questions.”
At AirSage, unicorns really do exist.
Click here to read the full story.
Young Professionals in Transportation (YPT) provides professional development, fellowship, and networking opportunities for young professionals in the transportation field across the country and around the world. For more information about YPT visit: http://yptransportation.org/welcome/
We are honored to be showcased in the Institute of Transportation Engineers’ (ITE) November journal. ITE covered our revolutionary technology, the AirSage Annual Transportation Industry Survey and our philanthropic support of LeadershipITE and Young Professionals in Transportation.
“Today’s professionals must keep current in new and emerging technologies to recommend the most cost-effective, site-specific solutions. In addition, we need to encourage new partnerships between the public and private sectors to develop collaborative solutions for transportation needs at all stages: planning, design, implementation, and maintenance.”
Thomas W. Brahms
Executive Director and CEO, Institute of Transportation Engineers
Click here to read the AirSage article on pages 16-17. This publication is courtesy of ITE Journal.
Like almost everything else the world of construction, the world of project planning is increasingly moving toward processes that draw upon data—including what is often referred to as “big data,” which holds keys to spotting large-scale shifts in communities.
One planning tool traditionally used to validate proposed projects is the interview-based travel survey, or trip matrix report. These studies capture patterns in where and when people move. The data can hold valuable information about the people in a certain area. But too often, and often too late, developers realize that the data used in the planning phase was grossly inaccurate, and as a result, millions of dollars are lost on projects that weren’t feasible in the first place. Add in dramatic fluctuations in demand as buyers becoming renters, office workers start working from home, etc., and the challenge to forecast population and traffic shifts becomes even more daunting.
But today there is a new approach to generating trip matrix data. Mobile devices are the new frontier.
"Communications and transportation are two staples of the economy. Our ability to provide insights allows us to contribute to a more efficient transportation system; it’s our corporate responsibility and ingrained in our culture."
- Cy Smith, Founder and CEO
For the first time in history, U.S.-based transportation planners and traffic engineers have access to insights into how their peers view the industry, their organizations, private vs. government jobs, gender and age issues and more.
Other findings featured in the research include:
Perspectives on government entities vs. private corporations
Views on technology and how innovative the industry is
Insights into how transportation planners view budget challenges and bureaucracy
The future of housing, infrastructure, transportation planning, urban/suburban sprawl and more...
In a recent paper--named a “Best Paper” at URBCOMP 2013--scientists at Massachusetts Institute of Technology detailed their research to make cities ”more livable, more efficient, and better positioned for the centuries ahead.” The foundation for the research was to establish reliable estimates of when and how 1 million residents use Boston-area facilities. AirSage data provided this insight, providing what the paper called an “improved ability to capture, store, and understand how massive amounts of data is changing the methods for inferring human behavior. (see page 1)”
Research by: Shan Jiang, Department of Urban Studies and Planning, Massachusetts Institute of Technology; Gaston A. Fiore, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology; Yingxiang, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Joseph Ferreira, Jr., Department of Urban Studies and Planning, Massachusetts Institute of Technology; Emilio Frazzoli, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology; Marta C. Gonzalez, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology
One of the biggest convcerns about VMT is privacy and how to protect it. But a solution may already exsist. Cy Smith, Founder & CEO of AirSage, explains in an article that appeared in Transportation Issues Daily and The Daily Transportation Update (AASHTO daily newsletter) "Could This Be a Solution to VMT Privacy Concerns?"
...some startups are building businesses by aggregating this kind of data in useful ways, beyond what individual companies may offer. For example, AirSage, an Atlanta company founded in 2000, has spent much of the last decade negotiating what it says are exclusive rights to put its hardware inside the firewalls of two of the top three U.S. wireless carriers and collect, anonymize, encrypt and analyze cellular tower signaling data in real time.
Since AirSage solidified the second of these major partnerships about a year ago (it won't specify which specific carriers it works with), it has been processing 15 billion locations a day and can account for movement of about a third of the U.S. population in some places to within less than 100 meters, says marketing vice president Andrea Moe.
As users' mobile devices ping cellular towers in different locations, AirSage's algorithms look for patterns in that location data - mostly to help transportation planners and traffic reports, so far. For example, the software might infer that the owners of devices that spend time in a business part from nine to five are likely at work, so a highway engineer might be able to estimate how much traffic on the local freeway exit is due to commuters.
Published by: MIT Technology Review
The ability to collect users' geo-loco data is becoming extremely valuable. On an individual level, it allows targeted advertising based on where the person is situated or is predicated to. Moreover, the information can be aggregated to reveal trends. For instance, amassing location data lets firms detect traffic jams without needing to see the cars: the number and speed of phones traveling on a highway reveal this information. The company AirSage crunches 15 billion geo-loco records daily from the travels of milions of cellphone subscribers to create real-time traffic reports in over 100 cities across America...
Research by: Mayer-Schonberger, Viktor, and Kenneth Cukier. "Datafication." Big Data: A Revolution That Will Transform How We Live, Work, and Think.
A global team of researchers have combined the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this research, they propose a network of road usage by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, their ability to pinpoint the few driver sources contributing to the major traffic flow allowed them to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.
Research by: Pu Wang, Central South University, P.R. China and Massachusetts Institute of Technology; Timothy Hunter, University of California, Berkeley; Alexandre M. Bayen, University of California, Berkeley; Katja Schechtner, Austrian Institute of Technology, Austria and Massachusetts Institute of Technology; Marta C. Gonzalez, Massachusetts Institute of Technology
In the National University of Singapore, Institute of Real-Estate Studies Working Paper Series, researchers used mobile-phone traces as a data source for urban-modeling as opposed to traditional methods data collection, like traffic surveys. AirSage mobile-phone data allowed for “lower collection cost, a larger sample size, higher update frequency, and a broader spatial and temporal coverage” (see page 3). Finding useful insight on intra-urban mobility patterns, which is crucial to their research, was accomplished through AirSage’s Wireless Signal Extraction Technology.
Research by: Francesco Calabrese, IBM Dublin Research Laboratory and SENSEable City Laboratory, Massachusetts Institute of Technology; Mi Diao, Department of Real Estate and Institute of Real Estate Studies, National University of Singapore; Giusy Di Lorenzo, IBM Research and Institute of Real Estate Studies, National University of Singapore; Joseph Ferreira, Jr. Department of Urban Studies and Planning, Massachusetts Institute of Technology; Carlo Ratti, Department of Urban Studies and Planning and SENSEable City Laboratory, Massachusetts Institute of Technology
IBM and participants from MIT investigate the use of mobile phones as a study platform for location data and group travel histories with the help of AirSage data to replace the use of dedicated GPS systems due to the “serious reliability and management issues” associated with their use (see page 3). They concluded that the use of GPS data was “not necessarily any more accurate than those produced by AirSage’s passive ‘Wireless Extraction’ system” which is why the use of smartphones is so important for their kind of research: “because such phones tend to be in near-constant contact with the network (to check for new email, to browse the web, download updates, etc.) they generate detailed traces that can be used to construct path histories with high fidelity across long periods of time.” (see page 19)
Research by: Giusy Di Lorenzo, IBM Research, Smarter Cities Technology Centre; Johathan Reades, Centre for Advanced Spatial Analysis, University College London; Francesco Calabrese, IBM Research, Smarter Cities Technology Centre and SENSEable City Laboratory, Massachusetts Institute of Technology; Carlo Ratti, SENSEable City Laboratory, Massachusetts Institute of Technology
This research is also referenced in the September 2012 the article “Creating the Sustainable City: A Community Engagement Strategy That’s Working” by Cori Burbach.
April - June 2011
“Mobile phone technologies can produce audience measurements that are more credible than current static measurements and can reasonably expect that credible audience measurements will make it possible for outdoor advertising to reach its full potential in the future.” This conclusion was come to by Pervasive Reasearch group when they set out to create a system for measuring the audiences of outdoor advertisments. Through AirSage they were able to use mobile phone location estimations as one of their primary research methods and reach a conclusion for their results.
Research by: Daniele Quercia, University of Cambridge; Giusy Di Lorenzo
and Francesco Calabrese, IBM Dublin Research Laboratory; Carlo Ratti, Massachusetts Institute of Technology
MIT SENSEable City Lab-Estimating Origin Destination Flows Using Opportunistically Collected Mobile Phone Location Data from 1 million Users in the Boston Metropolitan Area
In October 2011, MIT SENSEable City Labratory proved that “pervasive datasets, such as mobile phone traces provide rich information to support transportation planning and operation” (see page 9). They claimed that estimating a population’s travel demand in terms of origins and destinations of individual trips through mobile phone data would be a critical component of transportation management and emergency response. The lab’s analysis of 829 million mobile phone location data for 1 million devices was made possible through the AirSage Wireless Signal Extraction technology, which not only allowed them to ID the cell tower each mobile phone was connected to, but also gave them an estimation of its position within a cell.
Research by: Francesco Calabrese and Giusy di Lorenzo, IBM Dublin Research Laboratory; Liang Liu and Carlo Ratti, SENSEable City
Laboratory, Massachusetts Institute of Technology