Mobile Monday Amsterdam: Free To Be Human!David Orban
This document discusses emerging technologies and their implications. It covers the following key points in 3 sentences:
The document explores how sensors and connectivity in everyday objects ("spimes") will create a world where everything is aware and connected. It discusses how these "spime networks" will transform communication and data access between machines and humans. The emergence of these technologies is seen as an ongoing process that will have profound and unpredictable effects on humanity and requires rethinking how groups will interact and what it means to be human.
This document summarizes a project done by a group of 4 students from Sathyabama Institute of Science and Technology. The project is an anti-molestation device that uses IoT technology to send alerts with the victim's location to their guardian when a button is pressed. It lists the group members and their roles. It then describes the motivation for creating such a device due to increasing crimes against women and children. It provides details about the components used, including a NodeMCU microcontroller, GPS module, and push button. It also includes a block diagram, explanations of the technologies used, and a SWOT analysis.
This presentation was provided in 2009 and is certainly temporal, given the nature of the discussion.
Presentation roughly 20 minutes and discussion ensued.
This document describes a system to detect landmines using a robotic arm controlled remotely via GSM. When a landmine is detected, the system uses GPS to identify the location and sends an SMS message with the coordinates to a mobile phone. The system aims to detect and locate landmines safely from a distance to protect human lives. It discusses the technical challenges of landmine detection and describes the implementation of the system using components like a GSM module, GPS, wireless camera, and a printed circuit board integrated into a robotic arm controlled remotely.
A Glance at the Future - the Image as Dr Who's TARDISSimon Tanner
Simon Tanner of King's College London gives a presentation on the future of high resolution images using JPEG2000 and uses the Dr Who TARDIS as a thematic idea as the TARDIS is bigger on the inside than the outside (just like a JPEG2000 image).
Given at Current Trends and Future Directions for Digital Imaging in Libraries and Archives
10/11/2014, Wellcome Trust - London
http://www.dpconline.org/events/details/83-JP2000
This document discusses big data, including definitions and examples. It notes that big data includes activity data, conversation data, photos/videos, sensor data and more. Examples of one second internet statistics are provided. The document discusses that insight is the new currency from big data. It provides examples of using data analytics for sports, elections, recommender systems, and more. The focus is on using data science to study cities, socio-technical systems, and complex networks. Case studies of transportation research and metro systems are outlined.
The emergent opportunity of Big Data for Social Good - Nuria Oliver @ PAPIs C...PAPIs.io
We live in a world of data, of big data. A big portion of this data has been generated by humans, and particularly through their mobile phones. In fact, there are almost as many mobile phones in the world as humans. The mobile phone is the piece of technology with the highest levels of adoption in human history. We carry them with us all through the day (and night, in many cases), leaving digital traces of our physical interactions. Mobile phones have become sensors of human activity in the large scale and also the most personal devices.
In my talk, I will present some of the work that we are doing at Telefonica Research in the area of human behavior understanding from data captured with mobile phones, and particularly our work in the area of Big Data for Social Good. I will highlight opportunities but also challenges that we would need to address in order to truly leverage this opportunity.
Nuria Oliver is a computer scientist and Scientific Director at Telefónica. She holds a Ph.D. from the Media Lab at MIT. She is one of the most cited female computer scientist in Spain, with her research having been cited by more than 8900 publications. She is well known for her work in computational models of human behavior, human computer-interaction, intelligent user interfaces, mobile computing and big data for social good.
Mobile Monday Amsterdam: Free To Be Human!David Orban
This document discusses emerging technologies and their implications. It covers the following key points in 3 sentences:
The document explores how sensors and connectivity in everyday objects ("spimes") will create a world where everything is aware and connected. It discusses how these "spime networks" will transform communication and data access between machines and humans. The emergence of these technologies is seen as an ongoing process that will have profound and unpredictable effects on humanity and requires rethinking how groups will interact and what it means to be human.
This document summarizes a project done by a group of 4 students from Sathyabama Institute of Science and Technology. The project is an anti-molestation device that uses IoT technology to send alerts with the victim's location to their guardian when a button is pressed. It lists the group members and their roles. It then describes the motivation for creating such a device due to increasing crimes against women and children. It provides details about the components used, including a NodeMCU microcontroller, GPS module, and push button. It also includes a block diagram, explanations of the technologies used, and a SWOT analysis.
This presentation was provided in 2009 and is certainly temporal, given the nature of the discussion.
Presentation roughly 20 minutes and discussion ensued.
This document describes a system to detect landmines using a robotic arm controlled remotely via GSM. When a landmine is detected, the system uses GPS to identify the location and sends an SMS message with the coordinates to a mobile phone. The system aims to detect and locate landmines safely from a distance to protect human lives. It discusses the technical challenges of landmine detection and describes the implementation of the system using components like a GSM module, GPS, wireless camera, and a printed circuit board integrated into a robotic arm controlled remotely.
A Glance at the Future - the Image as Dr Who's TARDISSimon Tanner
Simon Tanner of King's College London gives a presentation on the future of high resolution images using JPEG2000 and uses the Dr Who TARDIS as a thematic idea as the TARDIS is bigger on the inside than the outside (just like a JPEG2000 image).
Given at Current Trends and Future Directions for Digital Imaging in Libraries and Archives
10/11/2014, Wellcome Trust - London
http://www.dpconline.org/events/details/83-JP2000
This document discusses big data, including definitions and examples. It notes that big data includes activity data, conversation data, photos/videos, sensor data and more. Examples of one second internet statistics are provided. The document discusses that insight is the new currency from big data. It provides examples of using data analytics for sports, elections, recommender systems, and more. The focus is on using data science to study cities, socio-technical systems, and complex networks. Case studies of transportation research and metro systems are outlined.
The emergent opportunity of Big Data for Social Good - Nuria Oliver @ PAPIs C...PAPIs.io
We live in a world of data, of big data. A big portion of this data has been generated by humans, and particularly through their mobile phones. In fact, there are almost as many mobile phones in the world as humans. The mobile phone is the piece of technology with the highest levels of adoption in human history. We carry them with us all through the day (and night, in many cases), leaving digital traces of our physical interactions. Mobile phones have become sensors of human activity in the large scale and also the most personal devices.
In my talk, I will present some of the work that we are doing at Telefonica Research in the area of human behavior understanding from data captured with mobile phones, and particularly our work in the area of Big Data for Social Good. I will highlight opportunities but also challenges that we would need to address in order to truly leverage this opportunity.
Nuria Oliver is a computer scientist and Scientific Director at Telefónica. She holds a Ph.D. from the Media Lab at MIT. She is one of the most cited female computer scientist in Spain, with her research having been cited by more than 8900 publications. She is well known for her work in computational models of human behavior, human computer-interaction, intelligent user interfaces, mobile computing and big data for social good.
The document summarizes key topics related to the history and development of the Internet. It discusses how (1) the Internet started as a network of networks using TCP/IP and has since converged with mobile technologies, (2) early experiments and games laid the foundations for the Internet as we know it today, and (3) governance and policy issues around content, intellectual property, censorship, access, and privacy have emerged as the Internet has grown globally in scale and importance.
Analysing Daily Behaviours with Large-Scale Smartphone DataNeal Lathia
This document summarizes research using smartphone sensors and data to analyze daily behaviors and activities. It presents three case studies: (1) using WiFi and GPS data to analyze public transportation routes and times; (2) correlating accelerometer and survey data to understand relationships between physical activity and subjective wellbeing; (3) the potential for behavioral interventions using sensor data. It also discusses challenges in working with large-scale smartphone data and opportunities for multidisciplinary research impact.
The document discusses the pros and cons of modern surveillance technology. Experts surveyed expressed concerns about privacy in a world where electronic communications can easily be intercepted. While surveillance helps authorities catch criminals, it can also potentially be used to collect sensitive personal and economic information without oversight. Both opportunities and risks exist as surveillance technology continues to advance. Options discussed include stronger privacy protections through encryption and international agreements, as well as ensuring oversight of surveillance programs to prevent abuse.
The Internet of Things (IoT) comes with great possibilities as well as major security and privacy issues. Although digital forensics has long been studied in both academia and industry, mobility forensics is relatively new and unexplored. Mobility forensics deals with tools and techniques that work towards forensically sound recovery of data and evidence from mobile devices [1]. In this paper, we explore mobility forensics in the context of IoT. This paper discusses the data collection and classification process from IoT smart home devices in details. It also contains attack scenario based analysis of collected data and a proposed mobility forensics model that fits into such scenarios.
Cite: K. M. S. Rahman, M. Bishop, and A. Holt, “Internet of Things Mobility Forensics,” INSuRE Conference, 2016.
The Evolving Data Sphere - David Orban - H+ Summit @ HarvardHumanity Plus
David Orban
Chairman, Humanity+
Advisor, Singularity University
Founder & Chief Evangelist, WideTag, Inc.
Intelligence Augmentation, Decision Power, And The Emerging Data Sphere
Human civilization depends on our ability to manage its increasing complexity. Behaviors, processes, and decisions that in the past were tolerated by the complex adaptive system we call Earth, are now more and more showing unforeseen consequences in unexpected places.
Many of our theories about the workings of the world are hampered in their predictive power by the lack of data, and suffer garbage-in, garbage-out effects. New interconnected sensor networks, fast, and ubiquitous communications, and the parallel power of our massive software systems are the never too soon answer to this need, and promise to revolutionize the way we understand, and act upon the planet.
The data sphere we are building, developing through every traceable action of millions of people, and billions, soon trillions of devices, designs a fine-grained picture of necessary understanding, and empowers us to believe that we can indeed aim to evolve our civilization, and to move it to the next levels of complexity, and achievement of human potential.
David Orban is an entrepreneur and visionary. He is Chairman of Humanity+, Advisor of the Singularity University, a Founder of WideTag, Inc., a high technology start-up company providing the infrastructure for an open Internet of Things. David shapes the strategic vision of its technologies by developing the policies and communication steps necessary to enable constructive progress. He is further a Scientific Advisory Board Member for the Lifeboat Foundation. David cuts across the limits of deep specialization to contribute to the new renaissance. He explains, “My vision is at the crossroads of technology and society as defined by their co-evolution.” David Orban’s personal motto is, “What is the question I should be asking?” This concept is his vehicle to accelerating cycles of invention and innovation in order to build the new world ahead.
Internet of Things, Connected Infrastructure & The Modern Supply ChainJeff Risley
Every market has infrastructure -- physical assets needed for the operation of an enterprise. And every piece of infrastructure will be impacted by the Internet of Things -- physical "dumb" objects, embedded with sensors, connected to the internet, communicating with one another and people. Understanding this collision of the Internet and Infrastructure is important for the future of both. This is a presentation I gave at the CSCMP Annual Conference.
You're traveling through another dimension, a dimension not only of sight and sound but of data; a journey into a wondrous land whose boundaries are that of the imagination. In this talk we will learn the relationship between Big Data, Artificial Intelligence, and Augmented Reality. We'll discuss the past, present and futures of these technologies to determine if we are heading towards paradise or into the twilight zone.
A smartphone is a mighty array of sensors. How to access the data, and get meaningful information from the various readings, like geo-location, gyroscope, accelerometer, or even the magnetic flux.
We also discuss the ehtical implication of mobile tracking: informational self-determination, "other-tracking" vs. self-tracking, and how to do spooky things with apparently innocent measurements.
The document discusses a study conducted by the advertising agency The Works on Twitter usage in Australia, which found that Australians send an average of 234 million tweets per month and most retweets occur on Mondays; it also discusses a software created by Dr. Suresh Sood at UTS that analyzed Twitter data to identify archetypes like lovers, carers and jesters and insights into what Australians are doing on Twitter. The study was the first national Twitter study in Australia and aimed to help marketers communicate more effectively with consumers.
The document discusses how retailers can use Internet of Things (IOT) technology to improve sales. IOT allows physical objects to be connected to the Internet and collect data. This enables applications like inventory management, targeted promotions, customer tracking, and theft prevention. Retailers can gain insights from big data and machine learning to better understand customers and optimize advertising. Dynamic lighting and proximity sensors in stores can further influence shopping behavior and increase sales of high-margin products.
Citizen Science and Crowd-sourcing Biological SurveysSimon Price
Presentation at Digital Research 2013, Oxford University. We report on the NatureLocator programme of digital research projects centred around the development and use of mobile applications to collect crowd-sourced data for biological surveys.
With high-profile coverage by the BBC and other media, the initial NatureLocator project, "Leaf Watch: Conker Tree Science", used a bespoke smartphone app to gather geo-located observational data from members of the public and created the most comprehensive information on the UK distribution of the Leaf-Mining Moth (Cameraria Ohridella) to-date.
Subsequent NatureLocator projects have refined and extended this approach to gather research data and raise awareness of other ecological threats. These include PlantTracker for recording sightings of invasive plant species, SealifeTracker for invasive and climate change indicator marine species, iRecord Ladybirds for the UK Ladybird Survey, and AquaInvaders for invasive freshwater species.
This document provides an overview of Singularity University, an organization focused on accelerating technologies like artificial intelligence, robotics, biotechnology, nanotechnology, medicine, and neuroscience. It summarizes Singularity University's programs, including a 10-week graduate program, 7-day executive programs, and 1-3 day custom programs. It also lists some notable faculty and speakers, including founders of companies like Google, Intel, and Synthetic Genomics.
This document describes an IoT-based smart security system for women. The system uses a smart band connected via Bluetooth to a smartphone. The band monitors vital signs and movement. If signs of distress are detected, the smartphone app uses GPS and GSM to automatically send alerts and location to emergency contacts and authorities without any human intervention. The system aims to address issues like delayed response from existing personal security devices that require manual activation. It provides automated protection using IoT technology for increased safety and security of women.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
The document summarizes key topics related to the history and development of the Internet. It discusses how (1) the Internet started as a network of networks using TCP/IP and has since converged with mobile technologies, (2) early experiments and games laid the foundations for the Internet as we know it today, and (3) governance and policy issues around content, intellectual property, censorship, access, and privacy have emerged as the Internet has grown globally in scale and importance.
Analysing Daily Behaviours with Large-Scale Smartphone DataNeal Lathia
This document summarizes research using smartphone sensors and data to analyze daily behaviors and activities. It presents three case studies: (1) using WiFi and GPS data to analyze public transportation routes and times; (2) correlating accelerometer and survey data to understand relationships between physical activity and subjective wellbeing; (3) the potential for behavioral interventions using sensor data. It also discusses challenges in working with large-scale smartphone data and opportunities for multidisciplinary research impact.
The document discusses the pros and cons of modern surveillance technology. Experts surveyed expressed concerns about privacy in a world where electronic communications can easily be intercepted. While surveillance helps authorities catch criminals, it can also potentially be used to collect sensitive personal and economic information without oversight. Both opportunities and risks exist as surveillance technology continues to advance. Options discussed include stronger privacy protections through encryption and international agreements, as well as ensuring oversight of surveillance programs to prevent abuse.
The Internet of Things (IoT) comes with great possibilities as well as major security and privacy issues. Although digital forensics has long been studied in both academia and industry, mobility forensics is relatively new and unexplored. Mobility forensics deals with tools and techniques that work towards forensically sound recovery of data and evidence from mobile devices [1]. In this paper, we explore mobility forensics in the context of IoT. This paper discusses the data collection and classification process from IoT smart home devices in details. It also contains attack scenario based analysis of collected data and a proposed mobility forensics model that fits into such scenarios.
Cite: K. M. S. Rahman, M. Bishop, and A. Holt, “Internet of Things Mobility Forensics,” INSuRE Conference, 2016.
The Evolving Data Sphere - David Orban - H+ Summit @ HarvardHumanity Plus
David Orban
Chairman, Humanity+
Advisor, Singularity University
Founder & Chief Evangelist, WideTag, Inc.
Intelligence Augmentation, Decision Power, And The Emerging Data Sphere
Human civilization depends on our ability to manage its increasing complexity. Behaviors, processes, and decisions that in the past were tolerated by the complex adaptive system we call Earth, are now more and more showing unforeseen consequences in unexpected places.
Many of our theories about the workings of the world are hampered in their predictive power by the lack of data, and suffer garbage-in, garbage-out effects. New interconnected sensor networks, fast, and ubiquitous communications, and the parallel power of our massive software systems are the never too soon answer to this need, and promise to revolutionize the way we understand, and act upon the planet.
The data sphere we are building, developing through every traceable action of millions of people, and billions, soon trillions of devices, designs a fine-grained picture of necessary understanding, and empowers us to believe that we can indeed aim to evolve our civilization, and to move it to the next levels of complexity, and achievement of human potential.
David Orban is an entrepreneur and visionary. He is Chairman of Humanity+, Advisor of the Singularity University, a Founder of WideTag, Inc., a high technology start-up company providing the infrastructure for an open Internet of Things. David shapes the strategic vision of its technologies by developing the policies and communication steps necessary to enable constructive progress. He is further a Scientific Advisory Board Member for the Lifeboat Foundation. David cuts across the limits of deep specialization to contribute to the new renaissance. He explains, “My vision is at the crossroads of technology and society as defined by their co-evolution.” David Orban’s personal motto is, “What is the question I should be asking?” This concept is his vehicle to accelerating cycles of invention and innovation in order to build the new world ahead.
Internet of Things, Connected Infrastructure & The Modern Supply ChainJeff Risley
Every market has infrastructure -- physical assets needed for the operation of an enterprise. And every piece of infrastructure will be impacted by the Internet of Things -- physical "dumb" objects, embedded with sensors, connected to the internet, communicating with one another and people. Understanding this collision of the Internet and Infrastructure is important for the future of both. This is a presentation I gave at the CSCMP Annual Conference.
You're traveling through another dimension, a dimension not only of sight and sound but of data; a journey into a wondrous land whose boundaries are that of the imagination. In this talk we will learn the relationship between Big Data, Artificial Intelligence, and Augmented Reality. We'll discuss the past, present and futures of these technologies to determine if we are heading towards paradise or into the twilight zone.
A smartphone is a mighty array of sensors. How to access the data, and get meaningful information from the various readings, like geo-location, gyroscope, accelerometer, or even the magnetic flux.
We also discuss the ehtical implication of mobile tracking: informational self-determination, "other-tracking" vs. self-tracking, and how to do spooky things with apparently innocent measurements.
The document discusses a study conducted by the advertising agency The Works on Twitter usage in Australia, which found that Australians send an average of 234 million tweets per month and most retweets occur on Mondays; it also discusses a software created by Dr. Suresh Sood at UTS that analyzed Twitter data to identify archetypes like lovers, carers and jesters and insights into what Australians are doing on Twitter. The study was the first national Twitter study in Australia and aimed to help marketers communicate more effectively with consumers.
The document discusses how retailers can use Internet of Things (IOT) technology to improve sales. IOT allows physical objects to be connected to the Internet and collect data. This enables applications like inventory management, targeted promotions, customer tracking, and theft prevention. Retailers can gain insights from big data and machine learning to better understand customers and optimize advertising. Dynamic lighting and proximity sensors in stores can further influence shopping behavior and increase sales of high-margin products.
Citizen Science and Crowd-sourcing Biological SurveysSimon Price
Presentation at Digital Research 2013, Oxford University. We report on the NatureLocator programme of digital research projects centred around the development and use of mobile applications to collect crowd-sourced data for biological surveys.
With high-profile coverage by the BBC and other media, the initial NatureLocator project, "Leaf Watch: Conker Tree Science", used a bespoke smartphone app to gather geo-located observational data from members of the public and created the most comprehensive information on the UK distribution of the Leaf-Mining Moth (Cameraria Ohridella) to-date.
Subsequent NatureLocator projects have refined and extended this approach to gather research data and raise awareness of other ecological threats. These include PlantTracker for recording sightings of invasive plant species, SealifeTracker for invasive and climate change indicator marine species, iRecord Ladybirds for the UK Ladybird Survey, and AquaInvaders for invasive freshwater species.
This document provides an overview of Singularity University, an organization focused on accelerating technologies like artificial intelligence, robotics, biotechnology, nanotechnology, medicine, and neuroscience. It summarizes Singularity University's programs, including a 10-week graduate program, 7-day executive programs, and 1-3 day custom programs. It also lists some notable faculty and speakers, including founders of companies like Google, Intel, and Synthetic Genomics.
This document describes an IoT-based smart security system for women. The system uses a smart band connected via Bluetooth to a smartphone. The band monitors vital signs and movement. If signs of distress are detected, the smartphone app uses GPS and GSM to automatically send alerts and location to emergency contacts and authorities without any human intervention. The system aims to address issues like delayed response from existing personal security devices that require manual activation. It provides automated protection using IoT technology for increased safety and security of women.
Similar to Euan Mackay Route - MRG Conference 2017 Presentation (14)
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"sameer shah
Embark on a captivating financial journey with 'Financial Odyssey,' our hackathon project. Delve deep into the past performance of two companies as we employ an array of financial statement analysis techniques. From ratio analysis to trend analysis, uncover insights crucial for informed decision-making in the dynamic world of finance."
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
11. 4. Issues with transparency
Img Credit: The Invisible Man (Medium)
12. New MST Devices
•Evolving our devices
•Data – second-by-second to 10x per second
•Better tracks indoor travel / movement
•Greater granularity of data
•Accurate to 2 metres (75x more precise than cellular data)
Magnetometer Accelerometer Barometer GyroscopeThermometerWifi BluetoothGPS
13. What this gives us…
Img Credit: Paddington The Movie (via City
Discovery)
Average time spent in Paddington
Station: 19mins 14
seconds
% who enter Paddington via:
road: 53%
tube: 14%
rail: 33%
% of time in Paddington spent
walking: 8%
waiting : 29%
wending : 63%
71% of visits to Paddington involve switching levels
Average distance walked in
Paddington: 206 metres
14. Summary
•Route rejected the siren call of mobile operator “big” data in favour of:
• Going evidence-first and prioritising rigour over de rigueur
• Ensuring independence and favouring control over convenience
• Safeguarding quality by choosing transparency over black-box
solutions
• Putting people at the heart of the approach
• In essence, following core JIC values while still quietly innovating
15. “Almost everyone is mad,
but some can control their
madness”
Euan Mackay
Route Research
Editor's Notes
Hello, In the next 9 and a bit minutes, I’m going to talk to you about why Route took the seemingly crazy decision to go evidence first and forsake incorporating super trendy mobile operator data into our audience measurement calculations while we were evolving our methods.
Route operates in the out of home advertising market.
To sell out of home advertising there is a need to measure who sees the ads and for how long they see them.
In order to measure advertising exposure, you first need to be able to precisely understand people’s out of home behaviours…
Route has been doing this since 2013.
Last year saw us sign a new contract with Ipsos that will take us through to 2023.
As part of this, we decided to evolve, update and modernise our methodology to ensure that we remain fit for our purpose in providing the best data possible to the industry.
Our final solution required more investment than ever before from our stakeholders.
We opted for a solution that included the best in class technology and a world first in people tracking
Today, there are many ways to measure people’s movements and not all are a po-faced as Craig Revel-Horwood.
Recently, many of the sensors that are typically used for measuring people have been incorporated in your mobile phone.
And, the mobile operators have access to the sensor data and are willing to part with it, at a price.
This makes the mobile data seem like a potentially useful data source in determining who does what when out of home.
On paper, the siren call of mobile operator data has lots going for it…
There’s lots of it – it comes in huge volumes
It’s granular – you can identify individual devices
It’s time stamped – so you know when devices do things
It’s quick – and can offer “real-time” insights
It’s continuous
It’s passive
It’s digital
It’s sexy
It comes from a mobile phone which means it holds a certain trendiness kudos…
Yet we decided against it.
We’re a bit contrary and don’t really go in for fashion.
We’re a JIC.
We’re data purists…
We can’t compromise on the quality of our data just because it might be more convenient to use data already in existence.
Instead, we need to strive to produce the best data possible.
With this, we decided not to choose the easy option.
We chose to collect the data ourselves.
Why have we rejected it? Think for a moment, if you will, about the meat farming industry…
<apologies to any vegetarians, vegans, freegans or fruitarians>
You have a prize cow. It’s all fattened up and ready to be slaughtered.
To make the most of it, you want to turn it into as much of the highest value steak that you possibly can. But you also know that in the butchering process, not everything becomes steak. Some meat may fall by the wayside and onto the floor.
With these offcuts, you have two options.
1. You can bin them.
2. You can sell them onwards as mince.
The mobile operator data is effectively that mince. It’s an offcut, a bye-product of some other core process that has become available by chance. For mobile operators, the steaks are the 24 month iPhone X contracts. The offshoot of these are the data generated showing where the devices connect onto the network.
As with much “big data”, the mobile operator data was not designed specifically for the purpose that we want to use it for. That’s not to say it’s not got value for marketing purposes – it’s just that it’s not necessarily right for us in what we’re doing right now in terms of measuring people. Upon looking at all the evidence we had, there were four core reasons why we opted against using the mobile data…
While the trendiness, volumes and speed of mobile data were certainly appealing to us, fundamentally, the accuracy that it can offer was less precise than we need.
Mobile operators use cell tower triangulation in order to locate devices on the grid. While this is effective in connecting people to their network and can be used to show that devices are near an ad, the evidence we were presented with demonstrated that it was only accurate to a distance of about 150 metres.
It’s not really precise enough for our purposes.
We need to be able to determine whether people are close enough to an ad to see it and we need a solution that works equally for a huge jumbo digital screen or a paper poster stuck on a lamppost.
The mobile operator data also can’t log location as frequently as we’d like as if we were checking for GPS locations every second it would kill battery life. This means that there are black spots in the data and a lack of continuous reporting, so again compromises would need to be made on the quality of our data which we were increasingly uncomfortable with.
In the end, we put evidence first and went with rigour over something a little more de rigueur.
A wise man once said “Never set out on a journey using someone else’s donkey”… While he was certainly a little odd, his words rang true in this instance.
Collecting the data ourselves means we become masters of our own destiny.
It ensures that we can remain independent.
It means that we’re not as reliant on the continued availability of third party data to entirely underpin our currency - (that said, we do still make use of third party data for our Traffic Intensity Model).
Collecting the data ourselves, also ensures that we have control over the data which we produce.
It means that we can collect the exact data which we need and we can design it specifically to fit our purpose rather than bending the currency to fit the data that is already in existence.
This gives us flexibility and capacity to change things if and when we require without being beholden to the data owners and their existing data formats.
In essence we are underpinning the continuity of the data going forwards.
Ultimately, advertising is about selling stuff to people.
And as obsessed as we all are with the latest gadgets and gizmos, devices don’t buy things, people buy things.
So, for us, it’s important to have people at the heart of what we do.
It is vitally important that we know exactly who who we are speaking with.
It’s also important that they know what we are doing too
Mobile operator data falls a little short on this as it gives a measure of where devices are not where people are, which leads to the final stumbling block…
There are issues with transparency in the mobile data.
By this I mean that there are a lot of unknown modelling processes going on behind the scenes in order to convert devices to people and to assign demographics to those people.
The issue is not that there is data modelling happening, but rather, the lack of transparency as to the processes that are being used.
This potentially moves us to a murky world where data quality and validity become difficult or indeed impossible to judge.
Again, in our role as a JIC and arbiters of data quality this puts us in a very uncomfortable position.
By gathering our own data, speaking to real live people, and having full clarity on the data inputs we use, we avoid any black boxes and know exactly how our audience estimates are arrived at.
Given this, the evidence for using mobile operator data just didn’t stack up.
So what did we do instead?
We’ve upgraded our people meters to take advantage of Blade-runner-eque technology.
They may look like a pager from 1992, but they are packed full of the most up-to-date sensors each of which collect data on a second by second basis.
We’re collecting data on where people are, when they pass bluetooth or wifi beacons. We know the direction they are facing, the speed they are travelling, when they twist and turn. We know the air temperature to tell when they are inside or out, we know the air pressure to determine their height and we collect this continuously, second by second.
These measurements enable us to locate participants no matter where they are, even when they are out of GPS range and we can pinpoint them to an accuracy of 2 metres (or 75 times more accurate than the mobile operator data in case you were counting).
This means that we can track people whether they are inside, outside, underground, overground or wombling free.
And with more data being collected, we have more scope to improve the accuracy of our models.
The new devices have been in the field for a year now and we are starting to reap the rewards and beginning to see the first data coming through.
The first environment to benefit from this new data will be railway stations.
Looking at the initial MST data for Paddington station we now know:
That the average time spent in the station is 19minutes 14 seconds
That 8% of this time is spent walking purposefully from A to B, 29% is spent waiting around (looking at the outdoor ads) and the remaining 63% wandering about or shopping (wending).
We can also now tell that 71% of visits to the station involve switching levels, so this may be going down to the tube or up to the shopping areas.
We’re now in the process of building these new data into our audience measurement calculations so as to improve the accuracy of our models.
This will first take effect in Release 28 of Route which will be published in September next year.
So, to summarise,
Route rejected the siren call of mobile operator data, despite it offering huge volumes, offering quick turnaround and also being readily available (at a price).
Instead, we’re collecting our own bespoke data rather than settling for convenience
We’ve upgraded our meters that enable us to track people above and below ground, inside and out to an accuracy far greater than any other means
We’ve prioritised data quality and gone for rigour over de rigueur
And we’re favouring transparency in our method over black box solutions to ensure data validity
In short, we’re placing our JIC values at the heart of everything we do, so as to to ensure that we continue to provide accountable, transparent and objective evidence of who sees OOH ads.
Thanks.