droptag drive: fresh thinking - cambridge consultants · gps confirmation requests, not the more...

CONNECTED DEVICES

DropTag®DRIVE: fresh thinking

WHITE PAPERDropTag®DRIVE: fresh thinking

01

Executive summary The Internet of Things (IoT) has radical implications for the insurance telematics industry. IoT is no longer just machine to machine infrastructure for businesses operations. It is disposable electronics for consumers – ubiquitous, low-cost “appcessories” that measure everything about anything and connect to the mobile phone and beyond.

Cambridge Consultants has developed DropTag®, a new disruptive, low-cost service and technology platform, comprising small, inexpensive, adhesive Bluetooth Smart sensor nodes, smart-device apps and a secure back-end server for handling data analytics, reporting and alerting. DropTag®DRIVE bridges the gap between smartphone-only solutions and dedicated black-box/on-board diagnostics

solutions. It represents a truly disruptive solution to the mass-market telematics challenge, bringing reliability and transparency to consumer and fleet managers alike.

Attachment of DropTagDRIVE to a car’s windscreen allows the construction of a detailed driver profile over time, and allows the usage of the car to be recorded. An example of a journey fingerprint is shown in Figure 1. The principle tool for this is the correlation of longitudinal and lateral acceleration of the car (indicative of a cars manoeuvring) and the vibrational information (engine speed or windscreen crack) which can be cross referenced and fused with GPS and other data from the phone such as road type, time of day and weather conditions.

Parked

When the car is parked,the device goes to sleep

to save power

High accelleration off the longitudinaland lateral axes detected, indicating

an extreme manoeuvre

Uneconomical driving detected,alert generated to give driverguidance on reducing fuel

Sustainedhigh engine

revs detected

Alert caused dueto strong decelerationinvolving ABS braking

Bump detected while parked,alert generated, customer

informed when back in range

Driving fast down a narrow country road

with sharp/blind corners

Major impact/crashgenerates and emergency

services notified with location

Idling

Driving

Figure 1 – Example of a typical Journey Fingerprint™, demonstrating the type of events that the DropTag platform can detect. Events are graded as normal (green), moderate (yellow)

or severe (red).

Benefits to the insurer � Zero installation cost, works without app

� Ultra-low-cost disposable device

� Small form factor / annual renewal – post to customer with renewal paperwork

� Accurate notification of engine/vehicle status – can be used to auto-start app

� Accident Fingerprint – instant classification and proof, including door close events

� Accident Alert – a mass-market solution for crash-event notification

� Secure service platform for provisioning, automated analytics and data management

� Fraudulent claim detection using DropTag Journey Fingerprint™ technology

Benefits to the consumer � Lower premiums

� Annual renewal cycle

� Data privacy – contextual data (location and speed) shared at driver discretion

� Driving-style and eco-driving coaching

� Park Guardian – car-park prangs are logged and driver alerted on return

� Accident Assist – a mass-market solution for crash-event notification

� Windscreen chip/crack alert

� Vehicle vibration diagnostics – tyre under-inflation, suspension problems

� Coaching and logging apps for families, businesses and shared vehicles

DropTag®DRIVE: fresh thinkingWHITE PAPER

02

Introduction to the DropTag proposition

Market background

Vehicle insurance is an extremely competitive and cost-sensitive market. Currently all players in the insurance trade use historical data and customer details to calculate a suitable annual premium quote. The consequences of getting this model wrong are exceedingly costly – not only from a loss-ratio perspective but also in terms of gaining or losing (both good and bad!) drivers. The cost for an insurer/underwriter to acquire a new customer is high, yet the web-based comparison sites try to cause exactly this behaviour to generate their own fees.

Telematics is a technique involving on-vehicle electronics to assess actual driver behaviour (and hence risk). Typically the cost of adding such equipment to a car is about £300, once the box and installation cost has been considered. This cost means current solutions are only typically offered to very high-risk drivers, where the financial model stacks up (eg this cost can be written into their quote, and still allow a reduction in their premium). Plug-in dongles and smartphone apps are lower-cost alternatives, and bring their own benefits – but they have limitations in terms of performance and installation.

What is needed is a totally new approach to enable the market to offer a reliable, black-box equivalent telematics solution to a truly mass-market audience. This needs a new proposition at its core, starting with a clear consumer-win offering, perhaps even outside the typical telematics context. DropTag is potentially this solution and, if successful, would form the basis of a full (but carefully staged) telematics rollout, which in the future would include ever-more-capable smartphone apps (and their associated benefits and savings to the consumer).

The DropTag proposition

DropTag is designed to work in conjunction with a smartphone. DropTagDRIVE has local memory and, once attached to the vehicle, it is ‘always on’ throughout the year; its function independent of the smartphone. DropTag simply logs events as they occur and shares them when the smartphone is next within range. This means the insurer

can be confident of recording all journeys and the driver has access to services such as Park Guardian (where they are notified if the car has been damaged whilst parked).

DropTag connects securely to apps on multiple phones for vehicles used by various family or staff members. This means variations of the app can be tailored for different users, be they driver, parent, fleet manager or a multi-vehicle insurance policy owner. And policy owners will be able to see in detail the behaviour of their drivers and what effect this has on insurance premiums.

DropTagDRIVE is a breakthrough in telematics based insurance (see Figure 2). It complements the black-box solutions as there will always be a need for insurance policies for high-risk cars and drivers that require built-in tracking. DropTagDRIVE provides the same integrity of insurance with better customer acceptance at a fraction of the cost.

Ser

vice

inte

grit

y

DropTag®DRIVE

Apps

OBDII+BT 4.0

OBDII+GSM

OEMAfter market

Standaloneblack box

GSMmodules

Size of opportunity

Cost

Figure 2 – Market overview to highlight the relative position of the DropTag proposition;

low-cost, high-integrity service integrated with smartphone apps


03

DropTag architecture

DropTag is based around a three-tier architecture; providing a value-add, pragmatic big-data approach:

1. DropTag deviceThe tag is able to locally establish what events have occurred. It hosts a number of algorithms that are constantly looking for events, and logs these with time stamp, as a simple characterised bit-long statement – eg event type #32 ‘hard braking’ occurred at 12:30pm 12th Jan 2014.

The device itself is designed to be updated whilst in the field, using over-the-air (OTA) techniques. To aid the robustness of its event statements, it also considers local context – eg an acceleration trace could be a kerb strike, a car-park prang or the slamming of a car door. By analysing the Journey Fingerprint™ around this key impact (eg checking for vehicle motion, engine status etc) an internal state-machine model is implemented to give an improved certainty around the on-device analysis.

2. Smartphone app DropTag works best in conjunction with an app. There are some low-level (hidden) APIs and library files that sit within the app to enable the secure communication of DropTag data through the app and, in addition to

these, local contextual information from the phone can be added to further enhance the value of the information generated. It also provides a real-time interface to the driver, eg to enhance a smooth-driving app interaction.

For example, GPS data can be added to an event statement to give it greater meaning (was that severe acceleration event outside a school at 3:30pm?). Other appropriate data streams include the weather that day, the level of traffic congestion etc.

3. Back-end server All DropTag data is decrypted and amalgamated at the server level. This data is then passed on to clients, who are able to add the final contextual element – their own customer details – to enable the true power of the information to be unlocked.

Even without any knowledge of customer details, however, we’re still able to generate a myriad of value-add service propositions, ranging from road-condition information for maintenance services to geographical modelling of car usage etc. By creating a multi-tag data analytics service based on this pre-classified, pre-contextualised data, we’re able to offer a platform upon which many users can all co-operate and benefit, making data analytics quicker and more effective.

Kerb strikeevent

App addsGPS context

Server addsmulti-tag clarity


04

The benefits

The benefits of the DropTagDRIVE approach over the smartphone-only approach are:

� Auto-startAs DropTag can very accurately determine engine and vehicle motion status (down to a few RPM and 0.8km/h), it can be used to auto-start (and stop) the telematics app

� Service integrityEvery moment is measured in high resolution, even those journeys with no smartphone in the car or where the app is not running, and even when the driver is no longer present

� Crash and impact analysisWe accurately detect a crash and analyse the data at high resolution, eg severity, type and activity immediately prior to the crash

� Driver characterisation We can recognise key driver traits and verify who is driving at any time. We reassess this whenever we believe a driver change could have taken place, eg vehicle becomes stationary and we detect a door opening or closing. We are also able to detect typical behaviours of key demographics, eg the elderly and young drivers

� Vehicle characterisationWe can verify if the insured car is consistent with the type of car that the DropTagDRIVE sensor is attached to. For example, we can detect if the car has a manual or automatic gearbox, and if it is a diesel or petrol engine. We can also detect individual cylinders firing, and hence determine the engine RPM, max revs at gear change and wheel speed

� Vehicle diagnosticsWe can measure changes in the way the car is set up. Is the suspension worn out and in need of service? Do the tyre pressures need checking? Has the car been modified in some way?

� Journey characterisationWe can reliably detect road data, such that we can effectively learn a normal route via the vibrational and impact signature of the road surface. This enables an enhanced total service to the customer, whereby the smartphone battery can be prolonged with only minimal GPS confirmation requests, not the more common 1Hz refresh needed to accurately track speed

� Data privacyWe can measure significant activity and behaviour without the need for location and speed, allowing the driver and insurer to determine the value of sharing this sensitive information

The benefits of DropTagDRIVE over an on-board diagnostics dongle approach are:

� Low costDropTag is an order of magnitude cheaper than the current on-board diagnostics solutions

� Independent from the vehicle manufacturersDropTag works in 100% of vehicles and without the need for continued catch-up and work-arounds needed to keep up with changes made by the original equipment manufacturers

� No electrical connection to the vehicleDropTag only needs its own coin-cell battery to work, therefore it can be considered a consumer device, without needing to comply with AEC-Q100 and similar automotive standards

� Ease of installation DropTag only needs to be fitted to the windscreen of a vehicle. It needs no training, no locating of hidden vehicle sockets, no installation hassle

� Annual upgrade cycleDropTagDRIVE is replaced every year, removing legacy management problems and making sure that the very latest algorithms, sensors and power management tools are implemented


05

Journey fingerprintingJourney Fingerprints are an output from our software algorithm analytics. They represent both an abstraction from the raw sensor data and a visualisation technique. Journey Fingerprints are visualised using simple graphical representations relevant to particular users, eg the administrator of a multiple driver family can quickly view who has been driving which cars when (bringing real context to the event triggers). Typically, the data is initially shown as a continuous data plot (see Figure 4) which can then be expanded in unique ways to better characterise the data.

Expansion of this information is done both in terms of detail and in terms of criteria (see Figure 4). For example, we typically classify the characteristics of the fingerprint in terms of:

A. Activity: What is happening?

B. Behaviour: Who is responsible for how well that is happening?

C. Context: What is the context in which this is taking place? This may take various formats, eg when is the event happening? Or where? Or during what environmental context?


06

City centre

Dangerous B-Road

Motorway

Day

Dusk

Night

>5°C

0<4°C

<0°C

Context, eg location, time, ambient temperature

Unknown

Named driver Y

Named driver X

Behaviour

Driver X identified here so accountability can be back-tracked to journey start

Driver Y identified. Driver swaphappened at door open/close detection

Vehicle parked for the night – no clear‘ownership’ other than policy holder

Driving - moving

Driving - stationary

Parked

Activity

Event: excessiveacceleration and speed

Event: repeated high engine revs

Event: car-park bump detected – driver not at fault

Event: crash. Emergency services called – location/crash severity shared via app

Figure 4 – Expansion of the same DropTag event data feed, creating new Journey Fingerprint views

Figure 3 – example of a typical Journey Fingerprint, demonstrating the type of events that the DropTag platform can detect. Events are graded as moderate (yellow) or severe (red).

No movement detected

DropTag Journey Fingerprint

Door openedor closed

Vehicle speeddetected

Engine running Significant event detected


07

Crash analysisDropTagDRIVE self-learns its orientation as soon as the vehicle starts to move off; it can be fixed to the windscreen in any orientation. It then monitors and stores high-fidelity accelerometer data in the longitudinal (forward/backward), lateral (left/right) and vertical axes of the vehicle.

The fixed mount on the vehicle’s windscreen provides data with far greater provenance than similar data from the accelerometers within a smartphone, which is typically loose in a pocket and free to move around and change orientation. The fixed mount provides superior coupling to the car which, combined with a significantly higher data rate, reveals vibrations in high resolution. The windscreen itself also helps here, both by acting as an amplifier of vehicle vibration and giving direct access to events such as windscreen chips.

The performance of DropTag compares favourably with industry standard reference logging devices during a real (lab-based) crash. DropTag’s combination of accelerometers and clever wake-up algorithms are more than sufficient

at accurately capturing the impact pulse shape, duration, direction and severity.

Figure 5 shows how accurate acceleration data can be used to create a reliable fingerprint of bumps, impacts and crashes. DropTagDRIVE knows its orientation and wakes up instantly, using a rolling buffer to capture every detail of the event. Algorithms built from real-world data then establish the nature, severity and sequence of events, forming a reliable record for both immediate action and subsequent review.

DropTagDRIVE thus supports a range of valuable customer services, such as crash event notification – Accident Assist – where the insurance company is automatically alerted to call the driver to verify they are OK and to confirm the nature of the crash. We are also able to offer an after-market alternative to the future eCall function, whereby the DropTagDRIVE device instigates an automated outbound call from the customer’s own smartphone, either to the insurance company helpline or perhaps even to the emergency services.

Car not at fault

0

1

2

Car at fault

0

1

2

1) Clear negative acceleration as red car stops when it collides with the blue car in front.

2) Judder when second blue car subsequently runs into the suddenly stationary red car.

1) Clear positive acceleration when the first blue car ploughs into the back of the stationary green can and pushes it along.

2) Negative acceleration when the green car is subsequently brought to a halt by collision with second blue car.

Figure 5 – The sequence of impacts in a crash can clearly be seen. This enables correct assessment of where the fault may lie. Such confirmation is available in near-real time,

enabling proactive crash event notification and accurate ring-fencing of claim costs.


08

Smaller impact analysis As the DropTag platform is exceedingly light and rigidly mounted to the car, it can see a huge variety of smaller bumps and prangs, not just high-energy impacts.

Kerb strike

Wing mirror clipping

Door close

200 220 240 260 280 300 320 340 360 380 4000

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Time / s

Jer

k / g

s−1

LongitudinalLateralVertical

Rate of change of lateral acceleration is shown as the green line in this plot – it indicates a strong kerb strike at 281 seconds

Spectral density plots shows clear wing mirror strikes down to very low speed

Time / s

Freq

uenc

y / H

z

950 1000 1050 1100 1150 1200 1250 1300

0

50

100

150

200

250

300

350

400

450

500

log 1

0[

Pow

er /

g2H

z−1 ]

−5

−4.5

−4

−3.5

−3

−2.5

5mph

10mph

15mph

7mph

20mph

Driver door signal is repeatable and clearly different from passenger door- enabling some knowledge of likely number of occupants

0 0.05 0.1 0.15 0.2 0.25 0.3−0.05

−0.04

−0.03

−0.02

−0.01

0

0.01

0.02

0.03

0.04

0.05

late

ral v

eloc

ity

/ ms

− 1

Front driverRear driverRear passengerFront passenger

Time / s


Driver behaviour & vehicle characterisation

Acceleration correlation

A plot of the correlation of the longitudinal versus the lateral acceleration of the car indicates aspects of a driver’s behaviour. In ‘normal’ driving, the data is largely clustered around the axes themselves, with the driver only performing a braking or steering manoeuvre in isolation. In normal driving, we would expect to see only occasional excursions during more vigorous manoeuvres where, for example, a sudden steering input is combined with significant braking effort, ie perhaps a sudden lane change etc. Figure 6 shows this behaviour, with the vehicle spending most time at a constant speed (indicated by the red data peak at the origin of the plot at 0,0). The majority of the manoeuvres are clustered along the axes, where the driver is either accelerating or steering but rarely both.

Various factors are at play in this correlation, but at the forefront are journey type (motorways or city centre traffic), the car (the power and traction available) and driver behaviour (how safe or how risky a driver is). In isolation, this is not sufficient to rate risk – but it is a reliable source of high-integrity information which can be fused with other data about the car, the driver and the context of the journey to feed into the underwriting model.

Acceleration data also allows us to assess driver characteristics. We are able to determine the type of driver and match them to the insured parties, eg differentiating a young, confident driver (heavy acceleration and braking) from an elderly uncertain driver (low acceleration with sporadic steering and braking inputs). Not only can

09

Figure 6 – Correlation density plot showing longitudinal and lateral accelerations for a

complete journey. The most data plots are clustered around the (0,0) origin – where the

vehicle is at a constant speed, with no accelerations, eg it is stationary or travelling on a

motorway. Strong peaks can be seen along the axes where driver inputs are isolated, eg

the driver is only braking or only steering.

Figure 7 – On the left is a density plot of the acceleration correlation of an example driver. The contours give an indication of the safety of manoeuvres in different regions of the plot.

This driver appears to be relatively reserved with little off-axis activity. On the right is a 20-minute subsection of the data plotted as a line plot, allowing individual manoeuvres to be

seen more clearly.

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

Lateral Acceleration (left/right) /g

Long

itud

inal

Acc

eler

atio

n (f

orw

ard/

back

war

d) /g

−10

−9

−8

−7

−6

−5

−4

−3

−2

−1

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

Long

itud

inal

Acc

eler

atio

n (f

orw

ard/

back

war

d) /g


Most accelerationconducted while movingin a straight line

A couple of harshright-hand turns


10

these driver characteristics be used to determine who is driving the vehicle, but the same characteristics can then effectively be removed from the data to help to establish the type (and hence capabilities) of the vehicle, thereby enriching the overall risk model picture.

Figures 7 and 8 present acceleration correlation plots of two different drivers which demonstrate quite different patterns. Risk contour plots have been added which approximate to a perceived risk factor – for example, we would expect most drivers to typically achieve higher longitudinal accelerations due to hard braking, with less severe steering inputs, hence the risk contour shape reflects this.

Vibration analysis

Figure 9 illustrates the sort of information that can be found by analysing the vibrations of the vehicle. The spectrogram shows a clear progression through the gears. The engine speed repeatedly ramps up before dropping back down when the driver changes gear. Comparison with a plot of the acceleration shows that the discontinuity in the engine RPM is accompanied by a break in the acceleration.

The vibrations logged can be broadly split into wheel/road vibrations and engine vibrations. In ideal circumstances it is possible to determine the car speed from the wheel vibrations (given a known wheel diameter), although it

is assumed that a fusion of accelerometer data and GPS signal is preferred for such speed-based analysis. Again, the system is self-calibrating – comparing the wheel speed with GPS-based vehicle speed from the smartphone. Not only would this provide a back-up vehicle speed signal but it could also potentially be used to detect tyres that are inflated with insufficient pressure (ie their rotational speed differs from the other wheels).

The engine idle frequency can be clearly identified from the engine vibrations when the car is stationary. The actual signal detected is the physical ‘explosions’ of each cylinder, and hence logic must be applied to establish how many cylinders the vehicle actually has. Such information allows us to validate that the insured car matches that actually being driven.

Perhaps of more value is the additional information that can be inferred from the vibrational data, once the engine type/number of cylinders has been established. As shown in Figure 9, once the engine RPM at idle is known, the RPM of the engine at the point of gear changes can be analysed, which gives further indication of how hard the vehicle/engine is being driven. The lower part of Figure 9 further highlights this behaviour, by aligning the vibrational plot with that of the longitudinal acceleration plot. Here, clear peaks in acceleration can be seen, coupled with substantial drops in acceleration during gear change. This plot shows very reasonable maximum revs of just 3,150 RPM, for example.

Figure 8 – On the left is a density plot of the acceleration correlation of a second driver. This driver exhibits more off-axis behaviour (example red area highlighted), indicating the car

is being driven closer to its limits. On the right is a 20-minute subsection of this as a line plot, allowing individual manoeuvres to be seen.

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8


Long

itud

inal

Acc

eler

atio

n (f

orw

ard/

back

war

d) /g

−10

−9

−8

−7

−6

−5

−4

−3

−2

−1

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

Long

itud

inal

Acc

eler

atio

n (f

orw

ard/

back

war

d) /g


This driver is muchless confined to thelongitudinal axis


11

Figure 9 – Extract of the orientated and smoothed (unwanted engine vibrations removed) accelerometer data and the spectrogram of vibrations for a test vehicle. This extract

demonstrates some engine idling before the car pulls away with a particularly aggressive progression through the gears. The gear changes are clearly visible as both a break in the

acceleration and as a discontinuity in the engine frequency.

Time / s

Freq

unec

y / H

z

0 5 10 15 20 25 30 35 40

0

20

40

60

80

100

120

log

10[

Pow

er /

g2 H

z−1 ]

−5

−4.8

−4.6

−4.4

−4.2

−4

−3.8

−3.6

−3.4

−3.2

−3

0 5 10 15 20 25 30 35 40−0.2

−0.1

0

0.1

0.2

0.3

0.4

Time / s

Wheel / roadvibrations

Engine vibrationswhen idling

Engine vibrationswhen driving

Gear changes as seen inspectrogram of vibrationpower and in the acceleration

Acc

eler

atio

n / g

LongitudinalLateral


12

ConclusionDropTagDRIVE is a disruptive technology platform for telematics-based insurance.

� DRIVE bridges the gap between smartphone-only solutions and dedicated black-box/on-board diagnostics solutions

� DRIVE is a revolution to pay/manage-how-you-drive (PHYD, MHYD) industries, bringing affordable ease-of-use, reliability and transparency to consumer and fleet managers alike

� DRIVE provides detailed usage and crash data usually only possible via dongle and black-box solutions, and it does so at a fraction of their cost and with no installation hassle

DropTagDRIVE is a ‘one-size-fits-all’ platform, significantly enhancing the current app-only solutions – adding value to existing black-box propositions and providing a realistic mass-market telematics solution. The small form factor means the DropTag solution can be offered to all drivers, with the device shipped with the annual renewal documentation.

By embracing such a low-cost, robust, risk-analysis solution, a car insurer can offer their customers potentially game-changing value added services (VAS) features and premium cost savings, without exposing themselves to any additional/unacceptable risk.

DropTagDRIVE sidesteps the common issues of:

� Electrical connectivity to a car We don’t need to comply with complex and costly vehicle standards (eg AEC-Q100) as we’re not connecting to any of the vehicle’s diagnostic or network systems. Product development and improvement of CE-marked consumer devices is fast and the product itself low cost

� Data privacy DropTag performance is enhanced with occasional GPS data but it is not dependent on a constant stream of GPS speed and location data. It therefore offers a unique take on data privacy laws – we only access the data we need, and sharing location and speed can be an option offered at the discretion of the driver

� Installation cost and hassle Anyone can fit and use DropTag. There is no installation cost and the annual renewal cycle means there are no legacy issues with old equipment

� Expensive product development and rollout The components used in the DropTagDRIVE device are an order of magnitude cheaper than any other hardware solution on the market. This means expensive trials can be largely avoided – the sensor can be rolled out to the mass market fast, with the sheer quantity of data collected in use sufficient to drive further feature enhancements and improve accuracy

For further information or to discuss your comments, please contact:

Tom Lawrie-Fussey, DropTag Product Manager [email protected]

About Cambridge ConsultantsCambridge Consultants is a world-class supplier of innovative product development engineering and technology consulting. We work with companies globally to help them manage the business impact of the changing technology landscape.

With a team of more than 400 staff in Cambridge (UK), Boston (USA) and Singapore, we have all the in-house skills needed to help you – from creating innovative concepts right the way through to taking your product into manufacturing. Most of our projects deliver prototype hardware or software and trials production batches. Equally, our technology consultants can help you to maximise your product portfolio and technology roadmap.

We’re not content just to create me-too products that make incremental change; we specialise in helping companies achieve the seemingly impossible. We work with some of the world’s largest blue-chip companies as well as with some of the smallest, innovative start-ups who want to change the status quo fast.

The DropTag technology platform represents one of our recent strategic investments. We are currently exploiting this solution in a range of sectors ranging from monitoring the condition of parcels in logistics, through to assessing machinery health. The DropTag proposition includes a family of low-cost, low-power tag products which, combined with smartphone apps and data decryption servers, enables a truly innovative way of harnessing the power of the Internet of Things.

DropTag is yet another example of our fresh thinking, and it demonstrates how we’re able to help our clients by delivering disruptive, groundbreaking technology in a very real and value-add manner.

Cambridge Consultants is part of the Altran Group, a global leader in innovation. www.Altran.com

Cambridge Consultants is part of the Altran group, a global leader in innovation. www.Altran.com

www.CambridgeConsultants.com

Cambridge UK • Boston USA • Singapore

droptag drive: fresh thinking - cambridge consultants · gps confirmation requests, not the more...

Documents