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Revue TELECOM 181 - The Rise of the “Citizen Sensor“

Articles Revue TELECOM



The Rise of the

“Citizen Sensor“


Par Ludovic Privat,
Le rédacteur en chef vous propose de découvrir l'article coup de coeur de son dossier. 

Smartphones, cars and wearables embed more and more sensors that offer significant opportunities of data crowdsourcing for the Smart City.

It all started with map crowdsourcing…
In September 2007 GPS manufacturer TomTom introduced Map Share, something that was considered at the time an industry revolution, enabling each navigation device user to update maps and share these updates with
other users. The transfer of these map changes to TomTom servers was made at the time by connecting the
Personal Navigation Device (PND) to a PC connected to the Internet. While sending and receiving updates, users were also asked to share anonymously with TomTom the GPS data of their trips, i.e. GPS probes.

In December 2008 TomTom had gathered through this program no less than 500 billion unique GPS points from 5 million users. This staggering data feed allowed TomTom to update its map faster and to build a database of the average speed of each road segment, providing end users with a more accurate Estimated Time of Arrival  ETA).

Map Share was the early days of geographical data crowdsourcing.
At the same time companies all over the world started to consider data from mobile networks as an interesting
source to understand people and cars movements.
Companies such as Applied Generics (Scotland, bought by TomTom in 2006), Airsage (U.S.), or Decell (Israel, bought by Airsage in 2015) worked on using cellular data (the movement of phones as seen by the network) to derive realtime traffic information.
This technology was not a real success because of the limited precision of network location. The rise of smartphones proved to be a better, cheaper and easier (Wireless operators are complex organizations to work with) source of data for that purpose.

That however opened the opportunity for wireless operators to use their network data for analytics applied to
crowd management, geo marketing and more. Wireless operators business units such as Verizon Precision Market Insight or Telefonica Smart Steps are now offering this kind of services.

Smartphone as a sensor for traffic, parking… and more

The advent of the smartphone platforms and related app stores empowered developers to reach million of users
from a single distribution channel. Waze was one of these developers with the promise of crowdsourcing a navigation map and real-time traffic data. It success culminated in its $1 Billion acquisition by Google. The company is currently working with a number of cities supplying them traffic information.
Crowdsourcing information about on-street parking availability is another area where there is a lot of development happening. GPS maker Garmin and parking data supplier Parkopedia have for example developed a solution using GPS probes (counting vehicles entering and leaving an area) to estimate parking availability on street segments. Anagog, an Israeli startup, is using a mobility status SDK embedded in 15 million apps to create parking events and even to predict when cars will be leaving parking spaces on certain road segments (Disclaimer: the author is an advisor to Anagog).

Smartphone apps can also be used to estimate crowd movements on large scale events. Antavi, a spin off from ETH Zurich offers such solution. Their platform was used in 2013 during Züri Fäscht, a large scale festival that gathers 3 million people over three days in Zurich.
The mobile app of the event was downloaded more than 56,000 times and included the mobility SDK of the startup. They were able to collect GPS positions from 29,000 users. Based on these data, crowd densities, speed and velocities were estimated and shown in real-time to police authorities.

Sensors on four wheels

As new cars are increasingly connected to the cloud, they also report data for traffic but because they have many more sensors than smartphones, the opportunity to crowdsource data is huge.
One clear opportunity is weather data. Using outside temperature, windshield wiper usage and data from ABS, one can detect rain, snow or ice on the road. Road traffic supplier INRIX is for example using windshield wiper data to add weather metrics within their algorithms.

Another example is a research project launched in 2015 between Jaguar Land Rover and the Coventry City Council in the United Kingdom. The project aims at having car sensors reporting the state of the roads (potholes, etc.) to the city council.

“Our MagneRide equipped Range Rover Evoque and Discovery Sport vehicles feature sophisticated sensors that allow the vehicle to profile the road surface under the wheels and identify potholes, raised manholes and broken drain covers.“ explained Mike Bell, Global Connected Car Director at Jaguar Land Rover. Volkswagen and General Motors also have research projects that use ultrasonic sensors of their cars to detect free parking spaces while driving along a street.

Wearable sensor data

Beyond cars and smartphones, consumers are increasingly carrying different wearables (fitness trackers, smart
watches, and more) that all contain interesting sensors. There are a number of smart city usages that can be applied to these data.

An example of that is OOmbrella, a connected umbrella that will be launched within a few months by Wezzoo, a French startup that specializes in crowdsourced weather data. The handle of this umbrella contains weather sensors (pressure, light, humidity, temperature) that connect to a smartphone app.

A surprising example is the gathering of seismic information. Using data from its users in the Napa area (California), a data scientist from fitness tracker brand Jawbone analyzed the percentage of people who woke up in the middle of the night during the September 2014 earthquake. The analysis of a few thousand user’s behaviour depicted with accuracy where was the earthquake epicenter. The data was crunched after the event, but one could imagine a realtime
gathering of such data.

The innovation in wearables, connected cars and smartphones will push forward the integration of new sensors into these devices in the coming years, opening up new waves of crowd-sourced data that could be tapped by smart cities.

Citizen Sensor: threats and opportunities

The advent of the “Citizen Sensor“ however raises a number of questions about privacy and data availability as well as the question for smart cities to invest - or not - in costly sensors if crowd-sourced data are available.
First, this collection of data on a massive scale raises the question of privacy. Is the data fully anonymized? Does it receive the consent of the end users? Is the data securely transmitted and stored?
Second, the staggering amount of data collected does not always translate in available data or actionable insights for smart cities.

Third, the positive aspect of this data collection by the “citizen sensor“ is that - once available - the data is coming
much cheaper than using a network of proprietary sensors deployed by a city. At that level there is a lesson to be
learned from real-time traffic data. Installing large networks of traffic sensors (loops) was very expensive for cities and departments of transportation. They became pretty much obsolete the day real-time data was available from
commercial suppliers. The same trend is likely to happen again on other types of data: parking information? Pollution? Others? The future will tell…

Biographie de l'auteur

Ludovic Privat is a worldwide recognized expert in location-based services, GPS navigation and connected cars. He is currently a member of the advisory board at Anagog and What3Words and co-founder of a geolocation startup that will be launched in 2016. He was for a decade the co-founder and editor of GPS Business News, an online business media dedicated to the location-based services market.


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