Tarik Hammadou:"Shifting the Security Pradigm"

The AVISTA Smart Imaging Device:Intelligence, Business, Decision "tool" -- "NOT CCTV"

2010-08-29T07:46:00.000-07:00

Law enforcement agencies are under mounting pressure to provide a safe and secure environment for their citizens. Cities are increasingly using video surveillance as a tool to fight crime, prevent terrorism, and increase the personal safety of citizens. Visual surveillance for urban surveillance is currently a highly active research area in image processing and pattern recognition. The number of studies published in the last 10 years out numbers all previous related literature three-fold.

Commercial products/solutions are limited to specific class of analytic

Behavior analysis algorithms rely heavily on the core technology available. There are many limiting factors to the usability of these core technologies in real urban surveillance environment. Implementing analytic on some videos may not be feasible or could be restricted to only a subset of the algorithms available. There are many hardware-related problems such as poor resolution, low frame-rates, or insufficient processing hardware. For instance, crowd monitoring algorithms usually rely on the calculation of optical flow, which requires a moderately high frame-rate and significant processing power.

Most requirements today are around digital IP cameras, high megapixel resolution imaging. However the limitation of centralized processing push operators and integrators to down scale the megapixel image to 4CIF some times to 1CIF. In fact if you have 300 units of 3megapixel cameras streaming at 20fps you will need super machines to do any type of computation. Of course another factor is the recording cost So why megapixel IP cameras then?

Most vendors today limit their offering to the following applications: Object tracking, Breach (trip wire), loitering, crowd analysis, stance change, object left, object removed. The following table highlight the main vendors marketing those applications on their web sites.

I can see those classes of analytic working very well for infrastructure protection in a controlled environment that what companies like Nice systems learned very early and were successful when they focused on specific markets to target specific environments. Urban surveillance and intelligent transportation however offer different challenges and complexity. The uncontrolled nature of the environment, unpredictable behaviors require advanced algorithms and techniques requiring huge computational power causing a scalability problem.

Video analytic using distributed AVISTA smart sensor networks are emerging today as an alternative to CCTV and existing video analytic technologies, both in the field of surveillance (airports, train stations, museums, public spots) and intelligent transportation.

Aligning operational requirements and building winning strategies using existing technologies and cutting edge technology and most focusing on ROI will be the key today in building leadership in this area. The vendor driven video analytic strategies proved not working and today a clear understanding is built around customer driven video analytic and services.

No doubt that traditional centralized approaches offer several drawbacks, due to limited communication bandwidth, computational requirements and thus also limited spatial camera resolution and frame rate.

Some integrators/solution providers start moving the processing to the edge, and putting a PCB DSP boards at the pole where the camera is installed….it is a natural evolution and eventually intelligence will move to the edge.

A network-enabled AVISTA Smart Imaging Sensors for real time distributed intelligence is capable of tracking objects and extracts key video features in real-time and offers a very bandwidth-conservative approach, as it only transmits XML meta data results of the On- sensor processing which are of a higher level of abstraction.

Conventional computer vision systems typically see cameras only as simple damp CAMERAS. The processing is performed after transmitting the complete raw video stream via a costly and often distance-limited connection to a centralized processing unit (SERVER).

The AVISTA smart imaging sensors are built on the concept that it is more natural to physically embody the processing in the imaging sensor itself: what algorithmically belongs to the camera is also physically performed in the camera.
The idea is to compute the raw sensory data where it becomes available – directly at the sensor – The computation is pure feature extraction and tracking parameters.

Once the processing performed transmit only results in a format of XML metadata that are on a higher level of abstraction. This follows the emerging trend of self contained and networking capable smart sensors.

We were able to deliver some outstanding solutions as part of our DST analytic library in the last few months. The latest functionality was near miss pedestrian/vehicle detection at an intersection. Transportation agencies are looking to enhance pedestrian safety by enhancing traffic light systems. The data we provide to our clients is around traffic flow and specific incidents. The best article describing the problem appeared in the NY time recently.
Recently DigiSensory has been engaged by RTA in NSW to deliver the near miss detection technology. The following video show case th performance of the system at an intersection in Wolongong (NSW):

From video algorithms to business intelligence: the Avista Smart Agent is a powerful web based platform allowing real time traffic monitoring and incident detection.

Furthermore the Avista Smart Agent (ASA) correlates information and intelligence between different AVISTA smart sensors and provide the end user and operator a high level of intelligence.
In real time over a web based application platform that can easily integrate intelligence visually on google map or any GIS mapping technology. The user can access the real time sensory driven intelligence, traffic flow and will be notified of any incident.

For RTA and department of transportation around the world a simple application like near miss detection or crash detection will allow the traffic management operator to plan better and build more advanced system to reduce fatalities and incidents at intersections. More applications related to smart intersections are being build with partnership with different developers and R&D institutions. By offering the ASA on a open platform we are working towards building a community of AVISTA application developers working towards building speciffic rules and applications to meet different business objectives. While the image processing core is built at the sensor level the ASA server use simple XML programing to define speciffic rules to build different applications.

The following images demonstrate also the easy access to any data by a structured video/image indexing. The operator will be able to access any video/imaging data just by event ID. In a city like London with 4 million CCTV (1 camera per 15 citizens) video search will take hours and hours of intensive labor.

The Avista smart imaging sensors platform is more then what conventional CCTV, IP cameras, and analytic can offer. It is a management intelligence driven platform and a business operation tool where visual data is protected and processed by advanced image processing technique at the sensor level coding all visual information to XML meta data. The following video example shows visual sensory meta data information sent from the Avista smart sensor and the ASA predicts an assault.

As I mentioned in a different post the Avista smart sensor platform features a high level of privacy protection and the technology without any doubt will be the next generation public safety solution.
I have been for the last 4 weeks working with our partner in the UK Videcom on different projects and I will have very soon some update on how we are positioning DigiSensory as an important partner at the 2012 London Olympics.

The Community Safety Information Grid and Real-Time Crime Prevention Center

2010-03-24T09:41:00.000-07:00

The last time I wrote on this blog was almost 2 years a go.. We had a vision we spoke about a concept, we took two years to make this concept a reality. And I am writing today to report and share with you our achievement. And what next.

Most important is the unique approach we are taking in developing technology--the unique relationship between the user and the technologist--as technologists we started thinking like the end user, we eat, sleep, think like the end user...we are committed to deliver technology that respond effectively to the operational requirements. In my career I saw so many projects starting with a white paper called requirements....never worked. When you start learning a language, you go over many stages, once you start dreaming in that language means you achieved your goal...same thing with technology development, when you start understanding end user's problem...you feel the same pain. you are ready to innovate and start thinking of a solution. I have never understood why some organizations keep great engineers in labs, and the sales people are in the street...fundamental mistake...

And our MOTO:

"Our objective is to think beyond new products. Our aim is to imagine, innovate and create products and services that have the power to profoundly change customers’ expectations"

A successful technology/product development need to start by a marriage: end user-developer...

I have been on the road, in the lab, the streets testing what probably is the most significant advance in smart image sensor technology. The City of East Orange and the vision we shared with Director Jose Corderro is a reality. People ask me when do you sleep...the answer I don't need to, I am too excited.. a good friend of mine recently wrote:

Tarik is very much like my late father: brilliant engineer from a backwoods area, speaks half a dozen languages, he has the metabolism of a mongoose, and he only needs a few hours sleep every night. He also has a wide circle of friends..... "HA HA HA...this is cool, and it i an honor to be compared to Peter Petroff, the adventurous inventor, an engineer at the National Aeronautics and Space Administration (NASA) and an inventor whose enterprises developed a heart monitor and the digital wristwatch 30 years ago.

What make me more excited and motivated is the relationship I have with my clients. Last week I spent 7 days at the East Orange Police Department almost 24 hours/day, police car takes be back to my hotel at 1am and comes back to pick me up at 5am.

We finalized: "The Community Safety Information
Grid and Real-Time Crime Prevention Center"
Where Smart Image Sensor Technology, Enhanced Police Information Platforms, and Systems Integration Paves the Way for Law Enforcement to Seize and Sustain a Marked Competitive Edge in the Fight Against Crime

People ask what is it? Lets get to the definition:

The primary mission of the Real-Time Crime Prevention Center (RT-CPC) is to prevent crime and to mitigate threats to public safety. RT-CPC personnel operate and monitor a chain of interconnected and networked digital, virtual, and image sensory devices which provide law enforcement with crime prevention superiority. The RT-CPC proactively collects, fuses, assesses, and converts raw information from multiple sources into actionable intelligence in real-time. Intelligence fusion is a revolutionary approach that dramatically improves the ability to defuse threats to public safety before they occur and to optimize resources for timely and effective surveillance or incident response. In addition, crime prevention and incident mitigation plans are electronically transmitted to police patrols, virtual patrollers, and image sensory agents to prevent, not just react to criminal activity. Moreover, police responses are electronically synchronized and assessed in real-time.

The following video posted on Youtub, shows the 4 parallel screens in the control room, and how in just one second we close the loop, Smart sensor operator-triggered automated emergency dispatch of closest available field units to emergency situations. Upon receipt of a verified smart sensor priority alarm, operators trigger an ABAD response. ABAD signals TAC AVL to identify patrol cars closest to the scene; TAC AVL electronically hands over the information to the computer-assisted dispatch (CAD) system which instantly transmits automated dispatch instructions, shaving critical seconds or minutes off police response times.

In summary what we achieved

1. Situation awareness every 30 seconds;

2. Transformation of disparate data sources into a common operating picture for proactive threat identification and prevention;

3. Discovery and exploration of hidden trends, patterns, and relationships among data and identification of the leading indicators of potential threats;

4. Sharing of processes as well as products for efficient collaboration and maximum reuse of intelligence;

5. Creation of cause-and-effect scenarios to determine best course of action, plan for contingencies, and to maximize resource allocation;

6. Streamlining work flow and maximizing time-to-discovery through automated extraction, routing, and processing of data; and

7. Deployment of system-wide policy parameters to control data access, interaction, and processing.

The exciting part is the police definition of our Smart imaging sensor technology:

Programmable high definition cameras embedded with a computer chip that intelligently analyzes images in real-time. Smart sensors are programmed to detect and warn of common and specific elements of street crime (threat profiles) specific to East Orange and help solve crime by providing video footage of completed or potential crimes. Smart sensors track individuals and objects of police interest (e.g. cars) from sensor to sensor and store object information, such as the characteristics of a vehicle used in a crime and detects its emergence at a future point in time. Smart sensors alert law enforcement to criminogenic elements or conditions that often result in serious criminal activity. Importantly, this allows the police to intervene and alter the dynamics of crime-producing situations before crime occurs. For example, drug dealing hotspots are notoriously correlated with incidences of violent--particularly firearm-related--crimes. Knowing exactly when and how these activities occur (based on actual threat profiles) allows the police to leverage scarce resources more precisely and meaningfully. The integration of smart sensors with conventional police surveillance cameras allows for the formulation of a virtual surveillance rings around incident locations. The system is integrated with CAD, LEED and TAC AVL to increase agency effectiveness and allow for a more proactive approach. Sensory incident alerts are based on local conditions as specified by local law enforcement, hence are easy for non-technical users to understand and modify as needed. Smart agent analytics can be quickly updated by police operators to recognize specific elements of new threat profiles as they evolve.

We had around 100 people visiting the centre, police department from around the US, the Brazilian federal police looking for solutions to the next soccer world cup and the olympics they are organizing in their country.

What next:
I have a great pleasure to announce that the City of Hoboken is installing our smart imaging devices (65 sensors), the city of North Bergen is following with 50 sensors and we are on target to deliver an advanced technology platform to the Department of transportation in Washington DC, and we will be from next week working with UNISYS as a suplier providing an advanced imaging sensor technology for vehicle classification and tracking for boarder protection.

A UNIFIED SMART CAMERA STANDARD: TECHNICAL- BUSINESS-ETHICAL

2008-08-21T21:01:00.000-07:00

The contribution CCTV has made in protecting the public and assisting the police to investigate crime has occurred despite CCTV systems being developed in a piecemeal fashion with little strategic direction, control or regulation. This approach has failed to maximize the potential of urban CCTV infrastructures and many involved in its operation and management felt there remained a pressing need to examine existing standards, procedures, training and methods of operation. In addition, as local authorities, the police and criminal justice agencies face the challenges associated with the move from VHS technology to digitally recorded images, the lack of a coordinated approach to CCTV development poses significant risks in terms of compatibility of systems, cost of accessing the images and the potential loss of operational effectiveness.

Research has shown a vast range in the quality and usefulness of the business processes employed across all of those involved in CCTV. This includes standard working practices; standard job profiles; standard interfaces / protocols with other agencies; the use of standard performance indicators; evidence to support business cases, and indications of success. This was particularly noticeable in the differences between police forces, local government, and the interfaces between them. This has led to a fragmented approach across the country. Best
practices have not been built upon and there have been strained or less effective interfaces.

In my long discussions with business partners, integrators, end user, law enforcement organizations I have sensed the need of improvement in the technical aspects of CCTV deployment, the potential benefits and impact of digital recording systems, rapidly evolving technology, and the legal background to the operation of CCTV. There is also a constant need to observe data protection, privacy and human rights legislation. Recognizing data protection and privacy rights in the operation of all systems is not only important because the law requires us to do so, but also that it is right that we should do so, with concerns about surveillance so apparent in our everyday lives.

This is mainly what motivates my team at DigiSensory. The Technical, the Business and the Ethical values.

I had long meetings with my R&D group last week in relation to our latest Smart Agent products line, and our effort towards a unified standard. Let me tell you more about it, the Avista Smart Agent; is an XML- Metadata based intelligent video network protocol that standardizes AVISTA™ solution analytic rule, alert and configuration communications. Based on metadata-XML and open communication/web services standards, ASA enables seamless interoperability between any AVISTA™ smart camera device and any video management system to deliver a high level of intelligence and efficient operations. This protocol provides system integrators universal compatibility among any video management system with simple, feature rich API. Similarly, NVR manufacturers, can create analytic rule configuration and data output interfaces into their own software, and immediately communicate with and manage any number of AVISTA™ intelligent edge devices.

While most of the vendors today provide image processing based analytic DVRs and NVRs, it is clear that scalability is one of the main issues. It is impossible to drive more than 16 cameras without a powerful CPU to process images/video.Another issue is compromising the imaging quality by reducing the resolution to allow processing.

This week we have demonstrated at ASIAL 2008 in a life demo, over 100 cameras in a single IT infrastructure and network, delivering analitycs capability (tracking and counting) and an outstanding megapixel imaging quality.
We have also demonstrated that a smart CCTV system based on the ASA protocol and architecture is more than a security and surveillance tool, it is a business tool that drive performance.

As I said before data protection and privacy rights in the operation of all systems is not only important because the law requires us to do so, but also that it is right that we should do so, with concerns about surveillance so apparent in our everyday lives. Let me now talk about the technical link/the innovation and how we can maintain our integrity and ethical values.

Let me give you an example. There are 3 levels in our architecture:

The smart sensor layer
Smart cameras stream video and xml metadata. The xml metadata summarize the image "feature extraction" as specific entities like faces, motion, shapes, colors.

The smart agent layer
Analyze the metadata and communicate with different cameras. When a face is detected a filter is placed on the face in order to hide it. Once there is a specific threat the filter is removed. The smart Agent layer perform a number of services and build a high level of intelligence. And maintain integrity.

The application layer
Recieve video from cameras for view and storage and intelligence from ASA to build a high level applications.

The type of network we are discussing today will enable an extraodinary progress in the world wide web, what we know as "semantic web" where smart machines will drive web content.
But as I stated the main challenge will be: Technical, Business and Ethical for the future.

This is in general the passion driving our R&D team at DigiSensory Technologies. Congratulations for the ASA product launch.

A UNIFIED SMART CAMERA STANDARD: OUR ROLE AS A GLOBAL INNOVATOR. PART1

2008-04-07T04:06:00.000-07:00

I have been asked this question many times: How can we effectively use analytics and smart sensors? How can we make them work?

Let me first share with you some good news, in this quarter we have just delivered one of the most advanced network of distributed smart cameras to the Australian Jockey Club as a first stage of a contract to deliver over 300 distributed smart cameras for autonomous Video Surveillance and Monitoring. The technical approach uses multiple, cooperative video smart sensors to provide continuous coverage of people and vehicles in a cluttered environment.

HOW DID WE GET THEIR?
A Homeland Security objective:
In the last 3 years we have developed an active video understanding technology using distributed XML metadata that enables a single human operator to monitor activities over a complex area using a distributed network of active smart cameras over a web based control and management platform. The goal is to automatically collect and disseminate real-time information ( XML metadata, image descriptors) from the battlefield to improve the situational awareness of commanders and staff. Other military and federal law enforcement applications include providing perimeter security for troops, monitoring peace treaties or refugee movements from unmanned airvehicles, providing security for embassies or airports, and staking out suspected drug or terrorist hide-outs by collecting time-stamped pictures and event description of everyone entering and exiting the area.

A Commercial Application:
Mounting cameras to capture video imagery is cheap, but finding available human resources to sit and watch that imagery is expensive. Surveillance cameras are already prevalent in commercial establishments, with camera output being recorded to tapes that are either rewritten periodically or stored in video archives. After a crime occurs – a store is robbed or a car is stolen – investigators can go back after the fact to see what happened, but of course by then it is too late. What is needed is continuous 24-hour monitoring and analysis of video surveillance data to alert security officers to a burglary in progress, or to a suspicious individual loitering in the parking lot, while options are still open for avoiding the crime.

Keeping track of people, vehicles, and their interactions in an urban or battlefield environment is a difficult task. The role of the AVISTA video technology platform in achieving this goal is to automatically describe people and vehicles from sensor raw data, determine their geolocation, and insert them into a dynamic scene visualization. We have developed camera embedded technology for detecting and tracking moving objects at the camera level. The Camera delivers continuous stream of images with embedded descriptors for moving objects by shape, color, movement pattern... Detected objects are classified into semantic categories such as human, human group, car, and truck using shape and color analysis, and these labels are used to improve tracking using temporal consistency constraints.

Further classification of human activity, such as walking and running, has also been achieved. Geolocations of labeled entities are determined from their image coordinates using two overlapping camera views. These computed locations feed into a higher level tracking module that tasks multiple sensors with variable pan, tilt and zoom to cooperatively and continuously track an object through the scene. All resulting object hypotheses from all smart cameras are transmitted as symbolic data (XML Metadata) packets back to a central operator control unit, where they are displayed on a web based graphical user interface to give a broad overview of scene activities.

The Australian Jockey Club netwotk represent a real example of how the AVISTA smart camera technology platform works.
The AVISTA smart camera acts as an intelligent processor. Its function is to capture and analyze video imagery for the presence of significant entities or events, and to transmit that information symbolically as XML metadata to the management platform. This arrangement allows for many different sensor modalities to be seamlessly integrated into the system. Furthermore, performing as much video processing as possible on each camera reduces the bandwidth requirements of the AVISTA network. Full video signals do not need to be transmitted; only symbolic XML metadata extracted from video signals is distributed.

The AVISTA smart camera has an open platform architecture around one module named the Morpheus processor. The Morpheus is a System on Chip (SoC) solution.
The open architecture allows camera manufacturers, system integrators, IT department, and end users to build advanced and robust cost effective solutions.

I have mentioned in many occasions that video analytics should be Customer driven not vendor driven. Open architecture solutions are the path towards product maturity and SHIFTING THE SECURITY PARADIGM. In the last few years we have witnessed many analytics companies driving applications like Motion detection, left object...Unfortunately we have witnessed a large disappointment from end users and the statement was clear "the technology is not their yet". In my next post I will elaborate more on the methodology to use in order to build advanced smart sensor networks using the AVISTA open architecture. I will also share with you our effort towards a smart camera unified standard and our position as a global innovator.

PERCEPTUALLY AWARE INTELLIGENT SYSTEMS.

2007-10-12T23:06:00.000-07:00

As human we have the ability to sense, analyze and make judgment, abnormal odor, abnormal sound, abnormal action, someone running/screaming, some one you never saw in the building (suspicious) , someone walking in the opposite direction.... That's what we call human intelligence.

How can we build automated systems that will help us to find "THE BAD GUYS", systems, networks and sensors that will effectively contribute to our security and safety? Systems that can make sense and easily contribute to human intelligence.

We spent last week working with one of our partners in the retail industry, setting up a new AVISTA network, it was a very challenging week and in the same time rewarding,. The power of our devices is based on the capability of detection/processing and then distributing sensor metadata. Metadata is used to facilitate the understanding, use and management of data sensors. Let me put this in simple words,

1. A smart camera internally classify what they are seeing against a model set of parameters defining normal behavior, deviation from that norm trigers an alarm, the alarm can be predefined, as visual, message(email,mms, sms), XML message.

2. Each individual smart cameras is networked, each information obtained from each individual camera can be related to information picked up from every other camera in the network, in real time (XML), and in image database and archive. If a camera A indicate abnormal behavior at location A1, that information is potentially meaningful in isolation, but if 3 cameras C, D, and E at location A2,A3, A4, note suspicious loitering activity, it indicates a wider potential pattern of threat.

3. Web based command and management platform, enabling sharing sensory information and human intelligence.This is what I call "PERCEPTUALLY AWARE INTELLIGENT SYSTEMS". Perceptually aware intelligent systems are capable of finding things that are interesting in a manner similar to the way that an analyst might find things that are interesting.

To maintain our commitment towards advances in vision algorithms and massive distributed parallel processors and distributed smart sensors, we released last month our OEM platform that will allow camera manufacturers to build advanced systems and take smart camera technology to the next step of evolution. First quarter 2008 we will be distributing our camera development board in the US, Europe and China, with the latest innovation a web based SDK reducing dramatically time to market and building a strong efficient support and partnership from product specs to first manufacturing run.

The security and surveillance industry has been and is a conservative industry. However, since the 9/11 we are witnessing a gradual change, private businesses, government organization and law enforcement agencies are working together towards building efficient secure cities...For the first time we are talking about "STRATEGIES". This is what I call "VISION" . This is what makes my job at DigiSensory Technologies exciting, listening to private business operators, government leaders, and law enforcement professionals, understanding their strategies, their vision towards: PERCEPTUALLY AWARE INTELLIGENT SYSTEMS.

HOMELAND SECURITY

2007-10-10T00:17:00.000-07:00

I spent the month of September in Washington DC talking with different companies, governement organizations, professionals about one thing: smart camera technology for homeland security and law enforcement.

As the number of installed surveillance cameras increases, and the cost of cameras decreases the CCTV/security industry is facing the prospect of large multimedia archives where it may be very difficult to locate specific content. To be able to get the full benefit of this wealth of multimedia data, based on my discussions with Law Enforcement agencies security and home land security organizations it was clear that the main requirement today in modern surveillance is the need to be able to automatically highlight events of interest to the operator in real-time. Furthermore, past experiences such as the Australian embassy bombing in Jakarta, the London subway bombing showed the urgent need to make it possible to quickly identify and retrieve content which meets particular criteria.

My last stop was Las Vegas to attend ASIS2007. At the expo we have demonstrated and comunicated how advances in distributed smart camera technology can be used to effectively analyze, tag, store, search, alert, distribute and retrieve proactively multimedia content in surveillance systems. AVISTA smart IP cameras are utilized for multimedia compression, analyze in real time, and metadata are automatically generated to describe the multimedia content and distribute intelligence. A simple still effective Description Definition Language (DDL) standard was demonstrated to define application-specific multimedia descriptors and description schemes for multimedia management.

I had a good discussion with our partners from d3data(http://www.d3data.com/), and exciting evenings of ideas...A graphical multimedia retrieval application is needed to provide content-based searching, browsing, retrieval and playback over a web based command & control platform is the "DREAM PRODUCT", the "KILLER APPLICATION".

We are talking TECHNOLOGY let me convert that to Security/homelandsecurity/law enforcement the result is: "Critical Infrastructure Protection".
The Australian governement define "Critical Infrastructure Protections" as: "those physical facilities, supply chains, information technologies and communication networks which, if destroyed, degraded or rendered unavailable for an extended period, would adversely impact on the social or economic well-being of the nation or affect Australia’s ability to ensure national security".

The purpose is clear, I can envision a future where the smart sensors networks and smart cameras will be the driving force of our protection and homeland security. This statement has been reinforced when I attended a security breakfast series sponsored by Crowel Moring and Legend Merchant Group. Let me share with you the important points of the PARADIGM SHIFT:

The convergence of Physical and IT security

The convergence of private sector and gov security solutions

The convergence of technologies to serve both security and business needs

Incorporation of intelligent sensors and analytics into traditional security

Required compliance-driven security software

Security solutions producing positive ROI through operational efficiency

Transfer of technology and services to state, local, and private sector

We will dedicate our effort in the next few years to the smart sensor revolution, this year we have been active and effective in supporting our local police and we have been committed to the private sector in providing real value.
I said it before and said it in Vegas: "Our objective is to think beyond new products. Our aim is to imagine, innovate and create products and services that have the power to profoundly change customers’ expectations"