Did you miss LUCA Talk: Using mobile data in the transport sector?

AI of Things    6 October, 2017
LUCA Talk 7, held on Tuesday 3rd October, gave us an invaluable insight into the transport sector. There was a focus on mobile data and the way it can be used to track the movement of people. This data is always anonymized and aggregated and at LUCA, we have been collecting it since 2012. With LUCA Transit and the power of this information, it is possible to track anonymized groups of people when they move or dwell. Ultimately this allows our clients to make more informed decisions on transport planning, as explained in the talk.

It’s not too late to catch up!

The talk was split into 4 sections. Firstly, Tom Brealey gave us an introduction to the topic and helped us to understand the key areas of the technology. He then went on to talk about a specific case study, LUCA’s project with Highways England, an interesting example of how the mobile data can be utilized. Oscar Garcia Costa followed this up with an incredibly detailed analysis of the utilization of mobile data in Quito, Ecuador. LUCA has worked with the transportation authorities in Quito to help to plan and manage the transportation system. This has been achieved by analyzing the movement of people, as explained in the video below. The webinar concluded with a Q&A section, giving viewers the opportunity to ask questions to our experts.

If you have not seen yet our LUCA Talk you can do so below:

Don’t miss out on a single post. Subscribe to LUCA Data Speaks.

Feel Free to browse: How online retailers are driving sales with sponsored data

AI of Things    5 October, 2017
Leading online retailers are using sponsored data to remarkable effect: Consumers are spending more time in apps, browsing more frequently, and making more purchases. Before the internet, ‘browsing’ meant looking at goods on display in a store. So it was a perfect descriptor for early web use, which tended to be wide-ranging and exploratory rather than specific.

While the explosion in smartphone apps has led to our web use becoming far more targeted, browsing in the original sense remains fundamental to some of the most popular apps in the market.

It may have become swipe- and algorithm-enhanced but browsing is as essential a part of the customer experience in retail apps as it is in brick-and-mortar stores. The reason is simple: maximizing the number of browsers, whether online or in-store, is key to growing the number of paying customers.

But in retail apps, which require a mobile data connection, the act of browsing itself costs the user money. So any retailer with an app is effectively asking users to pay simply to view what’s on offer. The equivalent in physical retail would be to charge customers an entry fee.

In many markets, particularly among cost-constrained and prepaid segments, mobile data is a precious resource (and a Wi-Fi connection is not always a convenient alternative). Consumers tend to reserve their data for their most important activities; typically social media and messaging with friends and family.
In Brazil, mobile operators report that, on average, 42% of mobile users run out of mobile data each month. So for an app to be used at all, it must either be essential to the user’s everyday life or made compelling in some other way. For retail apps looking to create customers in these markets, having a cost to browse clearly makes little sense.
Recognizing this, a number of leading retail apps are now looking to remove the cost of using their app by sponsoring the associated mobile data. The app experience isn’t changed or restricted. There is no advertising added or data collected with the sponsorship. But for the end user, it becomes entirely free to use these apps because they no longer consume the user’s mobile data allowance.

By sponsoring data, retail apps are simply following best practice from the physical world. Brick and Mortar retailers invest heavily to entice people into their stores, providing services and amenities beyond their core proposition to enhance the customer’s experience.
So not only does sponsoring data remove a barrier to app use, it allows the retailer to promote an additional customer service.

And, by freeing the app from mobile data charges, apps can become far more effective at fulfilling its core functions—showcasing goods, encouraging browsing, converting browsers into customers. Indeed, sponsored data is already having a dramatic impact.

Creating more browsers generates more sales
Figure1: Creating more browsers generates more sales

In Brazil, six leading online retailers—Magazine Luiza, Mercado Livre, Netshoes, Privalia, Natura and Zattini—have all reported increases in usage of their smartphone apps since they began providing sponsored data. Overall session numbers have increased, as well as average session lengths (the app equivalent of in-store dwell time).

At Datami we see an average increase in app use of 31%, three months after the introduction of sponsored data, taking into account session volume and session length. And, interestingly, the postpaid customers (with presumably more data in their plans) actually respond as good or better than pre-paid users—preferring sponsored apps to non-sponsored ones.

Furthermore, Mercado Livre, Netshoes, Zattini and Privalia have all reported increased conversion rates since they introduced sponsored data (the others started only recently); more of those browsers are becoming customers.
Netshoes has reported that, since introducing sponsored data, its app now accounts for 65% of online site visits, up from 10% in 2014. And by creating more browsers, the app has generated more sales. Netshoes conversion rate has increased by a staggering 60% which clearly demonstrates the benefit of being first to offer a sponsored app. Today, Netshoes combines free mobile data in their app with free shipping and makes both integral to their brand.
Sponsored data can even increase customer acquisition via app downloads. Mercado Livre has revealed that introducing sponsored data for its app boosted new installs by more than 10%, an increase which would typically require a high-cost advertising and/or digital marketing campaign. Sponsored data worked out cheaper.

So sponsored data for ecommerce apps encourages more people to browse more frequently, for more time.

And because this allows those people to browse more product—perhaps discovering more things that they like—it is enabling retailers to convert more of those browsers into paying customers. Consumers can’t buy what they can’t see, so anything that improves awareness is essential to driving sales. Sponsored data is a natural fit for online and app-based retail because it throws open the doors and invites app users to browse at their leisure.Apps are at the cutting edge of retail tech but they still depend on long-established retail principles. To paraphrase retail trailblazer Harry Gordon Selfridge:

 “Treat the customers as guests when they come… Give them all that can be given fairly, on the principle that ‘to those that giveth shall be given’.”

Content Written by David Nowicki CMO and Head of Business Development at Datami and published through LinkedIn.

Don’t miss out on a single post. Subscribe to LUCA Data Speaks.

Telefónica and ElevenPaths integrate its digital signature solution and biometric SealSign with Microsoft Azure

ElevenPaths    5 October, 2017
The company presents its latest developments at the 5th Security Innovation Day

TELEFÓNICA INTEGRATES ITS DIGITAL SIGNATURE SOLUTION AND BIOMETRIC SEALSIGN WITH MICROSOFT AZURE
  • This integration of the SealSign platform with Microsoft Azure Key Vault, thanks to the Gradiant technology, will provide users with improved storage, scalability and availability with a saving of implementation costs of up to 80%.
  • A large number of Telcos around the world are joining together to tackle cybersecurity threats. This supplements the 2016 collaboration announcements with Fortinet, Symantec, McAfee, Cisco, Check Point Software Technologies, RSA, Microsoft o Palo Alto Networks.
  • Mikko Hyppönen, Chief Research Officer at F-Secure, and creator of various patents such as the US patent 6577920 “computer virus screening”, is the invited star of the event.
  • It is possible to follow the 5th Security Innovation Day via streaming at https://securityinnovationday.elevenpaths.com/streaming.

Madrid, Thursday October 5th, 2017. – ElevenPaths and Telefónica celebrate its 5th Security Innovation Day, an event of national and international note about innovation and security. Pedro Pablo Pérez, CEO of ElevenPaths, shared his vision and strategy regarding cybersecurity, based on the fundamental premise that “this world requires a holistic vision, so as to cover the complete cycle of prevention, detection and solution as well as making both large companies and individual users more secure”.
Chema Alonso, Chief Data Officer at Telefónica and Chairman of ElevenPaths, presented the most relevant security innovations that the company endorses as one of the key figures in the world of cybersecurity. Among the most important new developments is the integration of the SealSign platform of digital and biometric signatures with Microsoft Azure Key Vault which, thanks to the PKCS#11 connector developed by Gradiant, can permit the safe storage of passwords and digital signatures online without the need to install a specific hardware.
This integration results in improved storage, scalability and availability with a saving of implementation costs of up to 80%. In this way, the use of digital and biometric signature platforms (previously limited to large corporations), is made available to organizations of all sizes and budgets.
With the aim of offering clients more innovative cybersecurity solutions, thanks to the creation of intelligence networks about the threats that develop on the Web, ElevenPaths, -the Cybersecurity unit of Telefónica-, looks each year for the best partners at a global level with which they can create new alliances. An example of this is the agreement recently agreed with Telcos around the world, including Etisalat and Singtel, which supplements the collaboration announcements of 2016 with Fortinet, Symantec, McAfee, Cisco, Check Point Software Technologies, RSA, Microsoft o Palo Alto Networks.
Other new cybersecurity solutions that ElevenPaths presented during the day were:
  • SS-WIFI, a solution that allows organizations to know what users connect to their Wi-Fi, identifying them through their mobile telephone number thanks to the merger of Mobile Connect, a service that allows secure access to apps and online services without the need to remember passwords, with the Fortinet equipment. 
  • Improvements in navigation security for users though the high-quality Telefonica routers, thanks to the integration of new security software from McAfee which also reaches IoT (Internet of Things) components which are connected to it. 
  • The Faast solution for WordPress, persistent pentesting which allows organizations to reduce the time needed to detect security breaches within WordPress (software for the creation of web pages, blogs or applications). 
  • Signbox, a solution which allows, amongst other things, the definition of signature flows when many individuals take part, the grouping of recorded documents to ease management, signatures through various mechanisms (biometric handwritten signature, signature with digital certificate and through OTP) and it can be used from any device, as well as from mobile applications such as a web browser. 
  • ElevenPaths presented “Codename Path8”, a solution for the protection of organization’s sensitive documentary information, adding a layer of traceability which allows online visibility of the complete life cycle of each document, at any moment.
The Security Innovation Day also saw the vision of the future of cybersecurity of Mikko Hyppönen, the invited standout speaker. Hyppönen has been named the greatest evangelist of the industry and one of the most influential people on the internet according to prestigious journals in the sector, and he believes that “we are seeing the beginnings of our problems on the Internet. We need to act now if we want to keep the internet free and open”.
For Pedro Pablo Pérez “Telefónica continues with the process of digital transformation by firmly backing the End-to-End encryption, investing in infrastructure and allowing the creation of new cybersecurity operation centers in Latin America. In addition, it is building new partnerships to shape expansion in this area. It is creating four new patents in order to develop solutions and invest in human capital that allows not only for the growth of skills, but also to continue to see double-digit growth”.
More information:

A data-driven football season

AI of Things    2 October, 2017


A game of football lasts 90 minutes, features 2 teams, each with 11 players, and it will hopefully (from a fan’s perspective) contain some goals. In recent seasons, an increasing number of clubs are making the most of the fact that each game will also contain millions of data points and events. Sports such as baseball and American football have a long history of using data. Now, soccer (or football as it will be called in this blog) appears to be the latest sport to become data-driven. In this post, we will see how data is driving teams from the summer transfer window until the final game of the season.

Data-Driven transfers

For fans, one of the most exciting days of the season is transfer deadline day. Although last minute deals can happen, the vast majority of signings are the result of months of scouting. Historically, this would involve assigning a scout to watch a player, to write reports on their performances, and then provide feedback to the club. For the majority of clubs this is still a vital job for the scouting team, but data-driven scouting is on the rise. For example, Arsenal paid over £2million for the US company
StatDNA, whose data has since been used to advise their signings.


Figure 1 : Data can help clubs make better signings
Figure 1 : Data can help clubs make better signings



Perhaps
the poster boy of this new approach is Matthew Benham, the owner of London’s Brentford
FC and Danish club FC Midtjylland. Benham made his millions using an analytical
approach to bet on football matches and he brought the same mindset to running
a club. The data collected on players is used to build a database within which
the club can search for a player who can better suit the team’s playstyle. Brentford
signed both Andre Gray and Scott Hogan using this approach, and both signings were very successful. The huge
profits made on these players shows that the data-driven approach also has financial benefits.
Additionally, signings are not made on ‘hype’, which arguably means that
decisions are more rational.
  
Wage
negotiations can often be an obstacle to transfer talks, as the various
interested parties often disagree on a ‘fair’ wage. A report from the International Journal of Computer
Science in Sport reveals how Big Data can be used to analyze the salaries of
top players in Europe. The data scientists computed the salaries of players
based on 55 metrics (from goals scored, to aggression and ball control) and
compared this to the actual salaries from the previous year to reveal overpaid
and underpaid players. Arguably, this method could be used in any industry
where there are identifiable attributes in order to determine fairer wages.


Training using wearable technologies


Figure 2 : Training with connected equipment
Figure 2 : Training with connected equipment










  
TSG
1899 Hoffenheim having been playing in the German Bundesliga since 2008 and
data science from their partner SAP forms a vital component of their training
sessions. The players use wearable technologies and balls are fitted with
sensors to provide real time performance statistics. Information can include
distance covered on the pitch, passes completed, tackles made and much more.
These insights can help managers to decide who has performed well enough to
earn a place in the starting eleven for the next match. The power of Big Data is
the sheer volume of events it can analyze – “in just 10 minutes, 16
players with 6 balls can produce almost 13 million data points”, according to Hoffenheim’s Director for
Sports and Youth Training, Bernhard Peters. Data collected during training
sessions can also prevent injuries (through the detection of metrics as
detailed as stress levels) which is likely to improve the team’s chances of a
successful season. One of the keys to a data-driven club is that data-driven
training methods are instilled into the squads from the youth teams to the
first XI, as is the case at Hoffenheim.

Real-time tactical approaches


Data insights from training sessions can be used alongside statistics from previous games to aid tactical decisions before and during the match. Many clubs work with data from not just their past matches but also data collected from their next opponent’s performances. Big Data solutions are also extremely powerful during the match itself. Coaches can receive a half-time report thanks to real-time analysis.

Figure 3 : Tactics can benefit from data insghts
Figure 3 : Tactics can benefit from data insghts






  
Another
benefit of a club becoming more data-driven is that algorithms can reveal
insights that human statisticians would most likely miss. Many fans of FC
Midtjylland point to Matthew Benham’s takeover of the club as one of key
reasons why the club managed to win the first league title in 2015. Analysis of
the data of previous seasons revealed the team’s strength from set pieces. This
insight was used to turn this strength into a vital part of how the team played. In
that title-winning season, “The Wolves” scored almost half of their goals from
set pieces! 

The future

Given
the success stories of these football clubs who use a data-driven approach, it
is likely that an increasing number of clubs will follow suit. One could argue
that the question is no longer “how can a football club rely on data?”, and is
now “how can a football club not rely
on data?”. At LUCA, we believe that Big Data will become increasingly
important for sports teams. If you would like to read more about this, you can
read about our partnership with Movistar Team on the recent Vuelta a España
(article in Spanish).

Don’t miss out on a single post. Subscribe to LUCA Data Speaks.

Big Data – Driving the Future of the Automobile Industry

AI of Things    29 September, 2017
Are we already living in the future? Take one look at the technology being used in self-driving cars and you would certainly think so. Once only an unrealistic ideology, self-driving cars have burst onto the scene with various automobile companies, such as Tesla, offering the technology to the general public. But how do they work and what role is Big Data playing?

The cars are fitted with various sensors that analyze their surroundings. Google cars have the ability to build a 3D map of the area so in effect, the cars have eyes. Through radar abilities, they can analyze moving objects around them (other vehicles). This all results in a safer experience for the user. There are three main elements that make up the driverless cars. Firstly, the aforementioned sensors, secondly processors that understand and assess the information and finally actuators that convert the computer algorithms into physical actions such as breaking or steering.

An automated vehicle will produce approximately 4000 GB of data every single day. This data will be cleaned and useful extracts uploaded to the cloud service, thus improving the capabilities of driverless cars. This technology truly harnesses the power of the cloud; the cars inform each other of the smallest changes in the environment such as a new stop sign or speed camera.
Sensors are always collecting data
Figure 1: Sensors are always collecting data and improving the cars of the future

  
But what is the importance of Big Data here? The cars rely on stored information to make decisions in the current moment. Google, for example, have a data bank of around 3 million miles of real world experience in addition to 1 billion simulated miles from 2016. This previous data is stored in enormous data banks covering almost every driving possibility. So the more the cars drive, the more they will learn.
The storage of data has been built up over time. The car manufacturer Ford has gathered information from over 4 million cars dating back as far as 2004 when they equiped their Aston Martin DB9 with a network capable of optimizing engine performance and changing settings to suit driving styles. Clearly it has been a long road to reach where we are today. But what is the future for the industry? McKinsy and Co., an international management consultancy firm, predicts that the Big Data in cars industry will be worth an estimated $750 billion by 2030. It is growing at an alarming rate and Big Data is at the heart of it.
Some car manufacturers are scared of the introduction of self-driving cars and the inclusion of Big Data in the automobile market. They are under the impression that tech companies such as Google will have the upper hand and some traditional automobile manufacturers will be left in the dust. A comparative example of this is Nokia, once a leader in the mobile telephone market, but now a smaller player due to Apple and the iPhone revolution. However, Ford made intelligent decisions. They have invested in the industry for many years and aim to have a fleet of autonomous vehicles on the road by 2021.

Google´s self-driving car is beginning public trials
Figure 2: Google´s self-driving car is beginning public trials in Pheonix, AZ

  
Furthermore, self-driving cars can help to reduce our carbon footprint. They will maximize fuel efficiency thus helping consumers to save fuel and consequently money. Less fuel means fewer CO2 emissions and a reduced impact of vehicles on the environment.
People will always be skeptical of self-driving cars. Areas such as safety and long term reliability will be called into question time after time. But the facts are clear. The cars are always alert and the probability of machine-error is considerably smaller than the possibility of human error. it is undeniably the best option in the future of the automobile industry. Here at LUCA we are excited by the developments in the automobile industry. This shows the true power of Big Data.

Don’t miss out on a single post. Subscribe to LUCA Data Speaks.

GSMA Announces new developments in BD4SG Initiative

AI of Things    28 September, 2017
Last week, September 19th, the GSMA announced, at the United Nations General Assembly Week in New York, new developments in its Big Data for Social Good Initiative. Eduardo Navarro, President and CEO of VIVO (Telefónica Brazil), took part in the panel where the main focus was on finding new ways to use technology for the benefit of sustainable devlopment. 

What is the GSMA?

The GSMA represents the interests of mobile operators worldwide, uniting nearly 800 operators with more than 300 companies in the broader mobile ecosystem, including handset and device makers, software companies, equipment providers and internet companies, as well as organizations in adjacent industry sectors. The GSMA also produces industry-leading events such as Mobile World Congress, Mobile World Congress Shanghai, Mobile World Congress Americas and the Mobile 360 Series of conferences.

Announcements in last United Nations General Assembly Week

The first good news announced this week is that Megafon, Telenet and Safaricom have signed on to the initiative, joining previously announced operators Bharti Airtel, Deutsche Telekom, Hutchison, KDDI, KT Corporation, Millicom, MTS, NTT DOCOMO, INC., Orange, SK Telecom, Telefónica, Telenor, Telia, Turkcell, Vodafone and Zain. Therefore, today, The “Big Data for Social Good” initiative is now backed by 19 companies with a presence in 124 markets around the world.

Additionally, the GSMA has established an Advisory Panel to provide guidance to the initiative, as well as coordination and integration with the broader ecosystem. The Panel is comprised of the Global Partnership for Sustainable Development Data (GPSDD), the Digital Impact Alliance (DIAL) and Data2X, as well as leading big data experts from UN agencies including Be Healthy Be Mobile, a joint initiative by WHO and ITU, OCHA, UN Global Pulse, UNDP, UNHCR and WFP. The Advisory Panel will play a fundamental role in identifying where, when and how mobile big data can best support health and humanitarian efforts.

United Nations General Assembly
Figure 1: United Nations General Assembly

Telefónica believes in sustainable innovation

In Telefónica, we believe that it is possible to invest in a model of innovation squarely focused on addressing the most pressing social and environmental issues in a way that contributes to the success of the business. This is what we call “sustainable innovation”.

We also believe that the best way of building value for our Company in the long term is ensuring in parallel a positive impact on the society or the environment. For that reason, from the beginning, Telefónica has embraced the Sustainable Development Goals initiative as a tool to structure our contribution to global development, actively contributing to widespread key goals with internal and external initiatives and supporting projects, which aim to tackle these targets.

During the last 10 years, Telefonica has been working on proving that data can be used to improve, not only business capabilities, but also the society. A data-driven approach can be taken for each and every one of the Sustainable Development Goals, using data to measure how the public and private sector are progressing, as well as helping policy makers to shape their decisions and have the greatest social impact possible.

With billions of mobile devices and internet connections around the world and new data analytic capabilities, we can use our own internal data together with external information to give back the value of data to our customers and contributing simultaneously to achieving the Sustainable Development Goals set by the UN for 2030.

Telefónica and Big Data for Social Good

That is the reason why , in 2016, Telefonica proposed to GSMA the initiative Big Data for Social Good in alignment with GSMA project ‘Connecting everyone and everything to a better future’. Its aim is to engage mobile operators to work together and collaborate in accelerating the industry impact in the United Nations Sustainable Development Goals.

Within this initiative, Telefonica during MWC17, jointly with GSMA committed to run a trial in Brazil to showcase the potential of mobile data to face with these global challenges.

Other initial trials of Big Data for Social Good for epidemics and environmental pollution are currently underway with Bharti Airtel in India, and Telenor in Bangladesh, Myanmar and Thailand. The GSMA expects to publish the results of these trials at Mobile World Congress in February 2018.

 Project Sao Paulo – Big Data for Social Good

The goal of this project is to run a pilot in a large city in Brazil (Sao Paulo) to demonstrate that our data can be turned into social value, analyzing the city air quality.

The pilot is being run from the Big Data for Social Good Unit (LUCA) in collaboration with Telefonica Sustainable Innovation  Global Direction (Telefonica S.A),  Telefonica Brazil Sustainability Direction (VIVO), Sao Paulo Municipality and GSMA. Other partners will be also invited to collaborate and provide resources and data.

Pilot Project in Sao Paulo
Figure 3: Pilot Project in Sao Paulo

To reach the project objectives, it is required to collect and analyze mobile and environment data from sensors, as well as, any other data source that could provide valuable information for this purpose.

The project expects to show that correlation of mobile device data location with other datasets will allow to uncover insights and valuable information for local administration about how to improve traffic distribution. Moreover, the trial could come up with additional social and environmental policies that can improve citizen lives.

In addition, this project gives Telefonica a stronger “right to play” in the commercial big data space: we don’t use our customer data only for our own benefit, but we use that same data to help improve the world, “giving the data back” to society.

Don’t miss out on a single post. Subscribe to LUCA Data Speaks.

Data Science – Helping consumers to save money and travel for less

AI of Things    27 September, 2017
Have you ever purchased a train or plane ticket online? If so, you will know how hundreds of different website display different prices. Also, you will be aware that prices fluctuate, generally increasing the later they are booked. So when is the best time to book? Can Big Data give us the answers?

Obviously, train operators and airlines do not want to inform people of when their prices are set to increase. They predict when demand will be high and inflate prices accordingly – the higher the predicted demand, the higher the price. If they were to release insights into their price change schedule, it would alter consumer behavior. People will rush to buy tickets before inevitable price increases and in turn save money.



Helping you to save money
Figure 1: Helping you to save money


 
An independent train ticket seller, The Trainline, believes it has solved the pricing mystery through the power of Big Data. As a massive corporation operating primarily in the United Kingdom, they have access to billions of past data points relating to train ticket prices and demand fluctuations. Now they are in a position where they can accurately predict when prices are due to increase. On their mobile app, there is a feature known as the “Price Prediction Tool” and it will show a user when a journey is likely to sell out and how the price will change depending on the booking date. They also claim that the system will become increasingly accurate as time passes and their data bank grows (however, they believe the current system will still save users on average 6% on the price of advanced tickets). It will learn from all future searches, benefitting consumers in the long run. In addition to aiding users to save money, The Trainline has also manipulated its data to make journeys more comfortable for their clients. They are doing this by suggesting areas of the train which are likely to have empty seats based on previous data information.
This is an incredible example of how Big Data has been used to help consumers, but is there any more potential to explore in this industry? In theory, any large comparison site has the power to manipulate its data for the benefit of its consumers.

Helping you to save on your next holiday
Figure 2: Helping you to save on your next holiday

  
Let´s take the example of Skyscanner, a site which provides comparisons on plane ticket prices. The aim of Skyscanner is to display the lowest possible price to consumers and the inclusion of Big Data analysis will surely aid this. Skyscanner has already conducted some basic research into its potential. A tool on their website informs users of the best time to book but it is extremely limited; with only 10 departure airport locations (all situated in the UK) and only 19 destination airports (presumably the most popular destinations with the largest amount of data). This tool certainly has space for innovation and development. Firstly, as more data is collected, they could display information for more routes. In addition, it is currently separate from the flight search tool; a coming together of these two would result in a more informative consumer experience.
It is clear to see that the world of Big Data is growing and here at LUCA we will always strive to be at the forefront of innovation. It is only a matter of time before more companies unlock their true potential with Big Data. Businesses will take advantage of the information to maximize their revenues but as discussed, consumers will benefit from the increased ease of operation. Big Data is the future of business.

Don’t miss out on a single post. Subscribe to LUCA Data Speaks.

LUCA Talk 7: Using Mobile Data in the Transport Sector

AI of Things    25 September, 2017
The next webinar in our series takes place on the 3rd of October. In this LUCA Talk, you will get the opportunity to hear about how Mobile Data can be used in the Transport Sector, as well as some LUCA Transit case studies. In this blog post, you can read more about the solutions we provide at LUCA, as well as information about the speakers.

With an estimated annual usage in excess of 1.065 billion users, the London Underground only finds itself 11th in the list of busiest metro systems. This example shows the importance of mobility planning in major cities as well as the potential congestion if these users drove instead. The daily movement in our cities generates enormous amounts of data. LUCA Transit is the solution that harnesses this data (particularly mobile data) to provide insights for the transport industry. These insights can improve safety, congestion and event planning, among many others. You can see an example of LUCA Transit at work here. 

In our seventh LUCA Talk, you will have the chance to hear from Tom Brealey and Oscar Garcia Costa, senior analysts at Telefonica Smart Steps. Tom specializes in the uses of mobile data to infer travel patterns around the UK. Oscar’s work is focused on transit projects in the areas of transport planning and international people movement. Their talk will introduce the opportunities given by mobile data in the area of transport analysis and will showcase the solutions and insights that LUCA Transit offers to this sector. You will get to hear about case studies of these solutions from Highways England, Spain and Latin America, which shows the global power of data. There will be a chance for questions at the end of the talk.
Tom Brealey (l) and Oscar Garcia Costa (r)
Figure 2 : Tom Brealey (l) and Oscar Garcia Costa (r)

The webinar will take place on the Tuesday 3rd of October at 4pm and you can register here!

How did the temporary closure of Line 5 affect the users of Madrid’s Metro?

AI of Things    21 September, 2017

The Madrid Metro is undertaking important improvements on their transport network. This year, Line 5 which links the southeast-northeast zones to the capital, is the third to display the notice of “closed for network improvements”

So that those publically responsible for the sector can make better decisions about how and when to undertake this type of improvement work in an informed and transparent way, it is essential to understand the impact that these actions have on citizens and their economic repercussions.

Today, thanks to location data generated by technological devices, such as IoT (internet of things) sensors and smartphones, it is possible to measure how these maintenance projects affect the population. Therefore, we decided to investigate what type of response we would obtain from the system of location intelligence, combining public open data with data insights from mobile phones.

A summer closure of 62 days

As with what they achieved on line 8 at the start of the year, the Madrid Metro worked to offer a better service to citizens, by carrying out maintenance works as well as improvements in signposting and lighting. But making the decision to close an infrastructure like this in such a heavily populated area is never easy. In this instance, the decision on the best time to undertake the works was based on seasonality. Therefore, the closure of the line took place in the summer months as there is less demand in this period due to summer holidays. 

Nevertheless, how can those responsible of making decisions in the city truly know the best time for the closure? How can they make use of previous closure experiences on other lines to optimize future maintenance works? 

Making decisions based on Intelligent Location data is the first safe step to minimize the negative impact on the public transport system. 

The residents of the suburbs and outskirts are most affected

Line 5 of the metro is the 4th most popular line for the residents of Madrid, transferring passengers from the outskirts of the city (areas such as Carabanchel and Ciudad Lineal) to the city center. The closure of the line is most detrimental to the residents of these zones, as those who live in more central zones have access to a greater variety of transportation alternatives. 

In order to analyze movement patterns in a city, it is fundamental to know where the people who are moving live and where they work. This data can be found in different ways. For example, according to the “Atlas de la Movilidad”, in the district of Carabanchel the greatest number of workers live (followed by Vallecas, Latina, Fuenlabrada and Móstoles, all of which are located in the southern zone). Nevertheless, the area of Julián Camarillo (also on Line 5, station Sauces) is the most used area of offices and work places (after AZCA, Barajas, Gran Via and Valportillo in Alcobendas). 

This shows that the majority of the workers reside in the south of the city, but have their workplace in the north. Therefore, workers in the zone of julián Camarillo will be the most affected by the closure of the line. 

Nevertheless, in order to offer high quality location intelligence, our partner Carto decided to go one step further and make contact with one of their partners, us. Here are LUCA we were able to bring a greater granularity and understanding, thanks to our platform LUCA Transit which uses aggregated and anonymized data from mobile clients, allowing a better understanding of how groups of people move.  

The Smart Steps technology allows the identification of particular “points of interest”, based on recurring locations of mobile telephones (offering movement trends that cover approximately 40% of the Spanish population). In this particular case, the points of interest to study were the place of residence and the place of work. 

One of the most relevant insights that reflects the data (as you can see below) is that Line 5 journeys covering areas outside of M30 ring-road carry more than 50% of the passengers that use the line. This highlights the fact that the residents of the outskirts are the ones who suffered the greatest impact from the closure. 

Figure 2: effect on residents living in the outskirts.

Geomarketing campaigns and the promotion of vehicle sharing

Once the first challenge of using location data to generate Insights has been overcome, it is fundamental that those publically responsible receive investment for projects based on data to make better decisions for the benefit of the city. 

For example, this information can be used to choose suitable routes and time frequencies for the replacement bus service. The passengers who live in the center may have 2 or 3 bus routes that can be used as an alternative. However, passengers in the outskirts of the city, that we are analyzing in this study, do not have many other options. 

The local authorities can also decide to launch geomarketing campaigns in order to raise awareness for the available transport alternatives during the works, or to promote the use of shared vehicles in suburban areas. This has the objective of alleviating the negative impact on transport during the works. 

In summary, it is clear that the use of location data for the optimization of decisions on infrastructure and movement is of great value to the authorities who want to bring transparency to their decision making process. Citizens want to live in more intelligent and efficient cities. Location intelligence is a powerful tool for leaders who want to make data the cornerstone of their strategy and public service. 

If you want to know more about this topic, visit LUCA´s website. 

Creating smarter fire services using data science

AI of Things    19 September, 2017
Here at LUCA, we are passionate about Big Data for Social Good, or BD4SG. In our previous post, published during the first ‘Big Data for Social Good in Action’ week, one could see the power of data science in analyzing the Zika outbreak of 2016, fighting deforestation and aiding hurricane relief. This article focuses on the world of firefighting and explores some of the problems firefighters face, data-driven solutions to these issues, and the wider implications of these solutions.

The Challenges

Firefighters work in a highly pressurized environment where time is short and lives are often at stake. During the journey from the station to the site of the fire, information arrives from many sources including tablets, Sat-Navs, manuals and radios. Bart van Leeuwen, a Dutch firefighter and founder of Netage, suggests that this information overload is one of the main problems that fire services face. He often uses the example of the Anne Frank house in Amsterdam to highlight this point. The average journey time is 59 seconds, and in this time, the team must read five pages of reports on the building.

Even if we assume that a human being can absorb this quantity of information in such a short timeframe, no amount of preplanning can make you 100% prepared. The Black Swan Theory refers to Western explorers who, having discovered black swans in Western Australia, decided that they were not in fact swans, because they understood all swans to be white. The subsequent theory that Nassim Nicholas Taleb developed describes a surprising event that is rationalized in hindsight. ‘Black Swans’ are commonplace for firefighters, as well as doctors and police officers.

The Solutions

How can we overcome these issues in order to create smarter emergency services? Van Leeuwen argues that harnessing data is the key. Data is being created and collected at an exponential rate but an app that simply contains this information is no longer sufficient. Rather, access to the data is what is needed, so that data scientists with a passion for Social Good can work with the data to discover insights that the emergency services themselves may not see. ‘Open Data’ would facilitate this, and van Leeuwen argues that it must be a two-way transfer. As such, the Amsterdam fire department publishes their data in an open format at the same time as requesting access to data. One example is the ‘Firebrary’, a library of technical terms developed so that everyone can be on the same (web)page.

Amsterdam, the city using data to create smarter fire services
Figure 1 : Amsterdam; the city using data to create smarter fire services.



‘Open Standards’ for data would bring consistency and make working with Open Data even easier. If the world were to adopt Open Standards, ‘Linked Data’ would become an even more powerful tool. A great example of Linked Data is Wikipedia, where one link on a page leads to another page, containing more information and more links. Put simply, Linked Data unlocks information. In Amsterdam, the fire department posted live tweets of fire incidents which contained links to detailed data of the event and key terms on the Firebrary. Firefighters could therefore know the full details of the incident in a matter of seconds, and could even be warned if they were about to face a ‘Black Swan’


Mapping the environment in which the
emergency services operate is also possible using Big Data. In the case of the
fire department in Amsterdam, this involved using data of all past fires to map
high-risk areas and using metrics such as economic background to develop
insights on these patterns. These insights can help with performance
measurement as well as deciding where stations should be located. Data science
such as this can be equally applicable to the police and ambulance services. In each of these sectors, traffic mapping is vital since reaching the site of the issue in
the fastest time possible is key. Tools such as LUCA Transit (which analyzes over 7 billion daily events to provide
insights on traffic routing, volume and more) use Big Data to achieve this. You can read about some case studies here.


Protecting people from fires arguably
starts with prevention. Fire alarms, carbon monoxide detectors and sprinkler
systems are common ways of keeping our homes and offices safe and all of
these pieces of equipment emit data signals. “Nest” is a company that develops
tools for smart homes and their “Nest Protect” is an example of ‘Connected Data’ in action. The key
selling point is that the device can send an alert to your phone even if you are not at
home. 

The Nest Protect
Figure 1 : The Nest Protect

The potential uses of Big Data in the
emergency services are not limited to these examples, but they provide a
snapshot of the amazing potential that data has in benefiting society. The UN
has set 17 Sustainable Development Goals for the year 2030, and at LUCA, we
fully expect data science to play an important role in achieving them.

Don’t miss out on a single post. Subscribe to LUCA Data Speaks.