TII_DSRC_Sustainability_vFINALE_ter.pdf

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Sustainability & Climate Change
Ask not what 6G can do for you, but what you can
do for 6G…
IEEE MeditCom 2022
Thierry LESTABLE, Ph.D
Executive Director
Artificial Intelligence & Digital Science Research Center (AIDRC)

TII – Technology Innovation Institute
Combating Climate Change
Everyone is liable and needs to play a role…especially Research!
“By 2050, the Earth’s population is expected to increase from 7
to 10 billion and the world economy is projected to nearly
quadruple, creating a growing demand for energy and natural
resources. This new economy is projected to use 80% more
energy by 2050.” United Nations Intergovernmental Panel
on Climate Change commits to limit
increase in global surface temperature to
1.5 to 2 C by 2050.
Current level is at 1.2 C. finding the global solutions to reduce
emissions by 45% by 2030 and reach net zero
by 2050.

Carbon Footprint Reduction:: 2020 Science-Based Pathway
Towards Net-Zero GHG emissions by 2050
Telecom: [2-3]% consumption of Global Electricity Supply
ICT: [5-9]% consumption likely to rise up to +20% by 2030
Cause: Population increase, IoT, Mobile demand
2020: “Science-Based Pathway” – Net-Zero GHG emissions by 2050
- 29 operators (30% Global Mobile Connections) already committed to
this plan.
- Trajectory for Mobile Network Operators == GHG reduction by 45% by
2030
GHG: Green-House Gas

Mobile Network Traffic Growth Vs consumption
287x Growth in Traffic whilst only 1.6x Growth in Energy Consumption, this gives an indication of the scaling
factor between both phenomenon.
power consumption per bit for 5G is 90%
less than with 4G
(0.14 Watts per Mbps compared to 1.48
W/Mbps).

GHG emissions (indirect) abatement thanks to 5G
By 2030: 550MtCO2 each year = 15% of total EU emission in 2017
“Communications technology, digitalization, and
cloud technologies are central to the transition to
a zero-emissions economy.”
“The avoided emissions that they enable is
substantial.”
Dr Ajay Gambhir,
Grantham Institute for Climate Change
GHG: Green-House Gas
Source: qualcomm

GHG Emissions abatement – dive in
Avoided Carbon Emissions by Category in 2018 (14 countries)
1.44billion MWh elec/gas
521 billion litres fuel
Mobile Technologies Enablement Ratio (Vs footprint of industry)
- 2015: 5:1
- 2019: 10:1
- 2025: 20:1
Dive-in

7
6G KPIs - Purpose Built System
6G KPIs Let’s handle Mobility as
Keystone of Sustainable
Cognitive City
Prioritize

tii.ae
IEEE MeditCom 2022
Smart/Cognitive City
Safer Roads/Infrastructure & Traffic Management

The Top 10 Smart City Use Cases
2020 survey
“ 55% of the world’s population lives in urban areas and this percentage is expected to rise to 68%
by 2050 (.. addition of 2.5 billion people to urban areas worldwide.).
Additionally, freight volumes are expected to grow by 40% during this time period”
traffic congestion cost U.S.
commuters $305 billion in 2017 due
to wasted fuel, lost time and the
increased cost of transporting goods
through congested areas
Source: INRIX
A recent study published in Environmental Research Letters found that 100 cities
drive 18% of global CO2 emissions

Transportation: Carbon Footprint
In Europe, transportation is the main source of carbon emissions:
- It represents 27% of total emissions in the EU
- 45% of these emissions come from cars.
Road transport is the main contributor to these emissions: 77%.
In France: 121 million metric tons of CO2 in 2018.
In the UK in 2017, that number was at 118 million metric tons of CO2.
The European Green Deal aims at reducing the emissions of
the transport sector by 90% by 2050
Road congestion has economic, environmental, and human costs:
• Commuter: time, fuel, quality of life, vehicle maintenance
• Safety: crashes, emergency response times
• Freight: supply chain delays, fuel, shipping costs
• Environmental & Public Health: CO2, fuel, death and illness
• Economic Competitiveness: access to jobs, airport delays
Traffic congestion interferes with emergency vehicles, increases the number
of accidents, increases air pollution, and affects productivity

Global Status Report on Road Safety - 2018
VRU:
Vulnerable Road Users
50 Millions injured

A.I for Road Safety → 2030
« Accelerating the United Nations
Sustainable Development Goals (SDG)»
Road traffic
deaths and
injuries to be
reduced by at
least 50 %
from 2021 to
2030
6G to address UN’s SDG
➔ Contribute to the Quality & opportunities of human Life

Autonomous Vehicle (AV): The Ultimate Sensor Fusion
Source: Waymo
« Space
Odissey »/ « Moonshot »
with some Direct Short
Terms & Affordable
Enhancements for our
Daily Life!

LiDAR + Video Camera Fusion + A.I
80% of all car accidents involve Distraction (rationale for
SAFE act in the USA).
25% of fatal accidents involve distraction

C-V2X services: Keystone of NextGen (NG) Sustainable Mobility
Emergency First Responder priority
Smart Traffic Light
Blind curve: Hazard warning
• Safer Roads, Lower congestion/stops/accidents
• Road Safety: 6% CO2 Reduction
• CACC (Cooperative Adaptive Cruise Control): with controlled
intersections, thanks to C-V2X: 6% CO2 reduction
• Ecodriving
• on Motorways (avoiding congestion): 6% CO2 reduction
• Other roads: 3% - 7% CO2 reduction.
• Highest for [50-80Km/h]
• Intelligent Intersection:
• Avoiding (complete) stops
• Truck: 22% CO2 reduction on provincial intersections
• Car: 13% - 21% CO2 reduction
• VRU (Vulnerable Road Users) Protection
• This would encourage Cyclists
• Public Transportation prioritization
• V2X RSU Traffic light would prioritize public transportation,
thus encouraging its use, then reducing CO2
Source: TNO

Urban Traffic Management :: A.I + 5G & C-V2X
Cross-Working Group Work Item VRU: 2020
A.I combined with 5G & C-V2X is paving the way to disrupting road
traffic Management services, saving and changing lives of citizens.
Heterogeneous Interconnected devices, with Data privacy concerns
make it a perfect playground for Federated Learning & A.I on Edge !

Smart Traffic Analysis
Stereo-vision OTUS3D

Road Side Unit (RSU) – C-V2X + LiDAR + Video & A.I
Road Side Units (RSU) deployment jointly with
LiDAR & Cameras to capture activities & intention
of Vehicles + Pedestrian to improve safety, then
prioritized emergency vehicles, and finally
smooth/efficient traffic.
Smart City :: Security & Safety
Edge Computing (MEC) will also play a Key role within the IT infrastructure,
to secure Low Latency (RTT), gathering/fusion of sensors data & processing power.
MEC: Multi-Access Edge Computing

Traffic Management :: Classifying & counting – Flow control
Fixed Camera Flying Camera onboard Drone
6G Non-
Terrestrial
Networks
(NTN)
Reconfigurable
Intelligent Surface
(RIS)

C-V2X :: Carbon Footprint, Use Cases
Truck: Emission Reduction with and without stopping at intersection
22% CO2 Reduction
Smart Traffic Light
Car: CO2 Emission with and without Congestion (due to accident)
with Congestion (due to accident)
without Congestion (due to accident)
No Stop
~33% CO2 Reduction

Prioritizing Emergency Vehicles flow :: A.I+C-V2X+(NG)eCall
A.I Jointly with C-V2X and (NG)e-Call system, will save lives, by
minimizing time for intervention (first responders),
whilst also increasing global security of cities.

Promising Use cases
smart traffic management systems could save cities $277 billion by 2025 through
reducing emissions and congestion. Over 95% of the savings will be made by
reducing traffic congestion
Smart Intersection Investment to Grow by 78%
Investments into smart intersections will reach $10.2 billion by 2027; rising from
$5.7 billion in 2022

Autonomous Vehicle (A.V) Teleoperation Dispatch Center
A “Must have” for Liability purpose? …
Still in the infancy. Quite some room for improvements in terms
of User/Technician Immersive experience! Needs interaction
mechanisms to maintain perceptual illusions.
Possible thanks to high resolution imaging and sensing, and
5G/6G wireless networks (URLLC)
URLLC
Multisensory Telepresence & Immersion
URLLC: Ultra-Reliable Low Latency Communication

Improving Road Safety via Infrastructure Hazards detection (e.g. Pothole)
Sensor Fusion : Video + Accelerometer (IMU) + GNSS
Potholes are amongst the primary
Road Infrastructure Hazards
jeopardizing safety of drivers
(especially Motorbikes, Cycles).
Thanks to latest Leading Edge
technologies such as Computer
Vision, fusioned with Inertial sensors,
it is now possible to detect and
monitor such hazards, and set-up
efficient repair campaigns via
predictive Maintenance.

Potholes Detection & Mapping: Smart City Cloud Platform Extension
Prioritization & Optimization of Urban investment / Road Maintenance,
whilst cross-referencing with Road Traffic Crashes (RTC) Risk Management.

Motorway Maintenance: Cost efficiency
“The costs of road maintenance in the Netherlands add up to 1.6
Billion euros on an annual basis”
A.I
Driving footage
“a team of specialized technicians to go frame by frame
through the footage in order to recognize anomalies.
These defects are then manually categorized before they
are reported for maintenance”
The past: Costly & Lengthy
Now Semantic segmentation
Cost efficient Maintenance

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Micro-Mobility
Smarter & Safer e-Scooters, e-Bikes
IEEE MeditCom 2022

Micro-Mobility is Key to Sustainable Smart Cities
Faster growth than ride-hailing !
Rebound after Covid-19 crisis.
Reduce
Carbon
Gaz
emission

A.I Taking Fleet e-Scooter safety ( and Business) to the next level (1/2)
• Lane recognition – Is the
scooter riding on the Road,
the Sidewalk or the Bike
lane?
• Pedestrian detection
• Helmet detection
• Camera assisted parking
(using QR code recognition
in designated spaces that
don’t have any GPS signal –
e.g. underground car parks
or ‘urban canyons’)
• Smart City Insights
(Surface conditions,
obstructions, near misses
etc)
Source: Luna & Voi
Sidewalk detection/Protection Parking assistance
Main challenge for business growth:
Sidewalk Protection

A.I Taking Fleet e-Scooter safety ( and Business) to the next level (2/2)

What about Consumer e-Scooters?
Model XI Crash Assist A.I
ADAS Camera sensor, making difference between: stop-light, stop-sign, person, car, or inanimate oject
➔ Audible & visual warnings!!.

Qualcomm & Spoke: Bringing C-V2X to e-Bikes
B2X (Bike to
Everything)

Intelligent Helmets : A.I + A.R
A.R: Augmented Reality
Far beyond « Standard Helmets », however fueling
Innovation towards more Safety.
Potential Concerns with Distraction….likely to require quite
some Feedback Experience from the Field / Real
World…before any commercial launch.

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Smart Agriculture
&
Last Mile Delivery
The « take-off » of UAVs to fight Climate
Change…
IEEE MeditCom 2022

Smart (precision) Agriculture
UAV used for more efficient Pesticide application
UAV with 5G connection allows to
access remote cultivated areas,
together with more accurate
positioning for selection of the
geographical cluster where to
spray the Pesticide.
There is a twofold benefit:
1) Protecting farmers by securing
remote spraying of chemicals
2) Increase efficiency of the
spraying
Agriculture, Forestry and other land uses == 25% of global GHG emissions
Main reason comes from usage of fertilizer, irrigation systems and food waste.
So any action increasing efficiency in those 3 domains will strongly help reducing
the GHG emissions.
50% decrease in
the amount of
pesticide
applied!
By 2050, an additional 2 billion people will need to be
fed. This results in a demand increase of +56% more
crop calories (compared to 2010), that should be
supported by +593 Million hectares of land (=almost
twice India).

Smart Freight - Delivery Drones
Promising Last-Mile delivery
“drones’ greenhouse-gas emissions per kilometre are roughly 2% of those of a medium-duty truck
powered by either diesel fuel or electricity. ”
“greenhouse-gas emissions per parcel were 84% lower for drones than for diesel trucks.”
(small items)
Even though fully automated/autonomous (L4/L5) Drones are being investigated, we need to bear in mind
many of use cases might still get involved remote operation, so called BVLOS (Beyond-Visual-Line-Of-sight)
operation, meaning XR-UAV Control has to get improved. Besides, mobile networks thanks to deployed
infrastructure, enhanced coverage (RIS), C-V2X, accurate 3D positioning, power efficient TRX saving battery
life, etc..are Key enablers for an industrial roll-out at scale of UAV Business.

And many more Use cases/Verticals
It’s critical to embrace many of the Key use cases from Vertical markets involved in the GHG Emissions
and address those operational / pragmatic challenges.
Some of them are starting only to be handled in terms of technology and business maturity thanks to
M2M, then IoT/mMC…
- Smart Grids
- Smart Water
- Smart Buildings
- Logistics & Asset Management
- Zero-Energy devices / Harvesting
This can only be achieved through tight collaboration with Key Stakeholders in those vertical Markets,
and collaborate with them.
They must be more efficiently involved in standardization activities.
Most of the time industry alliances are relevant and efficient complementary approaches.

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Greener Mobile Networks
From Energy Efficiency to Zero-Net Energy…
IEEE MeditCom 2022

Mobile Network Consumption
Power Consumption breakdown: 4G vs 5G Mobile Network
Energy consumption per unit of data
(watt/bit) is much less for 5G than 4G,
but power consumption is much
higher. In the 5G era, the maximum
energy consumption of a 64T64R active
antenna unit (AAU) will be an estimated
1 to 1.4 kW to 2 kW for a baseband unit
(BBU).
Even though Energy Efficiency increases with Cellular Network Generations, for transmitting more data with less power (Watt/bit),
the overall Power consumption increases.
We thus need to be very vigilant, and secure sufficient degrees of freedom to optimize the global network.
RAN is still more than 50% of Energy consumption
%

Cellular sites: Energy saving
20% of
sites
carry
80% of
traffic
Energy Saving Features with AI
Management
reducing the power consumption when no data is
needed to be transmitted and increase hardware
efficiency
Traffic prediction using Machine Learning (ML) for MIMO sleep
ML/AI to predict
6G must keep on improving separation
between “idle mode” and “active
mode” functions, with Elastic approach
Vs traffic/Workload.

TII – Technology Innovation Institute 41
AI for Sustainable Network
Digital Science Research Center
• Smart Green Operation
• Predict traffic, user density, variation
• Power down RAN element, cell zooming
• Detect environment, weather on sensors
• Adaptive cooling, rectifier, battery switch
• Smart Green Protocol
• On-demand beamforming, radiate pattern
• Power control cross carriers, connections
• Discontinuous transmission, reception
• Dynamic clustered D2D communication
BBU RRU RF
Power
On/Off On/Off
FR1
FR2
Tim
e
Power
Baseban
d
AP
AP
AP
AP
AP AP
Fronthau
l
t
traffic
Traffic prediction Environment detection
Adaptive power & coverage RAN & HW component
On-demand beam pattern
Dynamic transmission
Dynamic connectivity
Dynamic topology

AI Accelerators & Processors
The Race to Performance…Not only (anymore)
Efficiency
- New Architectures
- New models needed
- Simplification / trade-offs

Paving the way to Digital Twin
Digital Twin: stepping stone for building Networks with Precision

6G: Ubiquitous Native Sustainability
- RIS
- IoT (AIoT)
- Edge AI
- Distributed AI
- Energy
Harvesting
- Energy transfer
- Native AI
- Semantic
Communication
- “Elastic” Radio
Resources
depending on
traffic

Reconfigurable Intelligent Surface (RIS): 1/3
Main Roll-out advantage
applications
1. Spectrum Efficiency Improvement
2. Coverage Extension
3. Energy Efficiency Enhancement
Standardization, as always is critical for successful Worldwide Market
adoption, and thus cost efficiency.

Reconfigurable Intelligent Surface (RIS): 2/3 - Tip of iceberg
Benefit whole E2E Network & use cases…
RIS/LIS/HMIMOS all meta-material based, will disrupt the
E2E Mobile Network dimensioning & roll-out, improving
dramatically the cost efficiency together with the End User
Experience.
HMIMOS: Holographic MIMOs

RIS Empowered Applications: 3/3
Beyond the hype, towards practical roll-outs…
2020 – NTT Docomo + AGC glass Manufacturer
5G signal @28GHz (FR2)
Positioning: Joint Communication & Sensing

Network for Sustainable AI
• Distributed intelligence
• Shift AI from cloud to network to reduce
communication, computation, sensing
• Energy saving from reduced training,
inference, data and model transfer
• Federated, split, multi-agent
reinforcement learning coordinate for
global optimization
• Emergent communications
• Communicate to learn emerging
protocols to collaboratively perform
targeted tasks
• Reduce communication energy by extract
and compress information with semantics
• Reduce sensing and computation energy
by scaling data and model for tasks
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Thanks for your attention

tii.ae
Let’s make a Difference for a Better World !!
IEEE MeditCom 2022

TII_DSRC_Sustainability_vFINALE_ter.pdf

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