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Nickolai Samotcvet,
CEO
Alex Kosik,
VP Strategy
Vladimir Lihachev,
CTO
Sergei Panychev,
Chief Scientific Officer
Yevgeni Koucheryavy,
Scientific Adviser
Konstantin Kosiakin,
Legal Adviser
Andrei Vorov,
Project manager
Innovative Center JEWEL
Business Summary:
• "Innovative Center Jewel" ("IC Jewel") is a Skolkovo IT company, creator of a revolutionary
"Jewel Head-Collision Prevention System" (JHCPS), for a long range preventative detection, that
enables self-driving car to "see" up to 2,000 meters ahead under any visibility and weather
conditions.
• Self-driving cars are no longer a futuristic idea. Companies like Google, Mercedes, BMW,
Tesla, Toyota have already released, companies like Apple, Uber and Qualcoom are soon to
release, and giants like GM, Kamaz and Tata announced plans for self-driving features that give
the car ability to drive itself.
• "IC Jewel" developes a proof-of-concept functional prototype of JHPC automotive radar
system designed to become an OEM portable long-range radar for a car driven on common
roads in any weather, in high/low speed traffic and with a projected wholesale price at
around $3,000.
Accident that occurred due to
moving into the oncoming
direction, have the most
serious consequences
The cost of existing safety systems
is very high for an ordinary user
Safe overtaking distance is up
to 2000 meters (Traffic police
statistics)
The market of automobile security
systems needs an import
substitution
It is hard enough to assess the
safety of overtaking in the
opposite lane (determine the
distance and speed of
oncoming vehicle) without any
hardware
It is necessary to reduce the
number and lethality of road traffic
accidents (Federal target program
of road traffic safety improving in
2013-2020)
Customer Problem:
• Google's and other self-driving cars are blind at distances over 300m. It takes 11 seconds for a
car moving at 100 km/h (27,7 m/s) to pass 300m.
• Another car approaching head-on at the same speed leaves just about 5 seconds for an AI to
analyze the dynamic situation and respond precisely to avoid collision. System fails if more than
three moving objects need attention. Existing legislative speed restriction of 40 km/h is a direct
consequence of this.
• Long range lidars, used by Google-cars, are expensive ($70.000). Yet with all their impressive
short/mid range capabilities get partially blind in snowfall, dusty road and light rain and
completely blind in smoke, fog, hail and heavy showers. Google drives its cars in CA because
state experiences historic drought.
• Road crashes cost USD $518 billion globally, costing individual countries from 1-2% of their
annual GDP.
http://www.forbes.com/sites/innovatorsdna/2015/08/19/teslas-secret-formula/
Product/Services: JHCPS: automotive radar system for long range preventive
detection:
• Radar wholesale is about $3,000, its EIRP = -10dBWt
(the resolved noise immunity for licensing and certification);
• JHCPS can be used for direct integration into existing ADAS
systems and AI upgrade;
• JHCPS determines the speed of oncoming objects
(up to 360 km/h), distance to them (up to 2,000
meters) and relative trajectory.
+JEWEL LANE DEPARTURE PREVENTION (JLDPS)
• Show and ice are not a problem!
• Car's radio vision is our solution!
• All in any weather conditions;
• JHCPS and JLDP can potentially be installed behind
the car grille on any car.
Lane Departure Prevention (LDP) and Lane Assist systems don’t work without this lines…..
Lane keeping systems have nothing to keep on the typical provincial road…
Target Market:
• Semi-autonomous: 50+m cars by 2020. Today's premium cars car have features that allow
them to accelerate, brake, and steer a car's course with limited or no driver interaction. JHCPS
would enable the car to avoid head-on collision and prevent deaths.
• Fully-autonomous: 10+m cars by 2020. A fully autonomous vehicle can drive from point A to
point B and encounter the entire range of on-road scenarios without needing any interaction
from the driver. JHCPS would act as a key component for long range car awareness, allowing AI
to detect, follow and take action on numerous moving road objects 2,000m ahead.
• Primary markets: USA, Canada, EU, Japan, Singapore, Korea, Australia
• Costs (World): $7 b/year in direct ADAS costs; $122 b/year in indirect car options costs.
Customers:
Direct: 8 major car companies (Volvo, Porsche, Mercedes, Bentley, GM, Tata etc) who could
offer modern car driver support options. Driverless car makers (Google self-driving car, Apple
Car, Toyota robotic car, Uber, Kamaz trucks, etc.)
Indirect: makers of security, drones and navigations toolkits (Lockheed Martin, Rotax, IAI,
General Atomics Aeronautical Systems). We can offer innovative universal radar for their drone
systems.
Sales/Marketing Strategy:
• Primary strategy: Partner with ADAS system manufacturers.
• Secondary strategy 1: Partner with driverless car makers.
• Secondary strategy 2: Partner with security and navigation tools developers.
Business Model:
• M&A by car maker who would get the system exclusively. Target valuation range: $60-80m
Competitors:
Indirect: Lidars optical stereoscope cameras (Fuji
Heavy Industries "Subaru EyeSight", Google lidar,
etc);
Direct: 76-80 GHz, ultrasonic radars, Car2Car
systems (Volvo CWAB, Bosch BLIS, Acura CMBS,
etc). All have cost/ size/ efficiency/ capability and
other disadvantages
Competitive Advantage:
Long range: 2,000m VS 300m detection range.
All-weather: Any weather conditions VS clear
visibility in dry air.
Price: $3,000 VS $70,000+ for LIDAR's.
Capital received to-date:
$80.000, Skolkovo grant
Investment sought:
$1m: Series A (preferred stock for lead VC) + $500k Skolkovo grant committed.
Series A Milestones: MVP prototype development, possible JV with driverless car company, IP
protection.
$2m: Series B (common stock for 2nd VC) + $1m Skolkovo grant.
Series B Milestones: Industrial prototype development, scenarios for integration into AI software
framework with selected manufacturer to show viability. Further IP protection.
Exit:
Early exit through M&A on development completion and technology validation with
target $60-90m valuation by the end of Y3.
Web:
http://sk.ru/net/1121073/
http://jewel-innovations.ru
Management:
Nikolai Samotcvet, CEO
Alex Kosik, VP Strategy
Vladimir Lihachev, CTO
Sergey Panychev, Chief Scientific
Officer
Yevgeni Koucheryavy, Scientific
Adviser
Konstantin Kosiakin, Legal Adviser
Sergei Naumov, Chief Mass Media
Officer
Contact Info:
Email:
csir.ntc.reb@gmail.com
Phone:
+7 (951) 871-87-04
+1-571-338-0332

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Long Range Radar Enables Self-Driving Cars to "See

  • 1.
  • 2. Nickolai Samotcvet, CEO Alex Kosik, VP Strategy Vladimir Lihachev, CTO Sergei Panychev, Chief Scientific Officer Yevgeni Koucheryavy, Scientific Adviser Konstantin Kosiakin, Legal Adviser Andrei Vorov, Project manager Innovative Center JEWEL
  • 3. Business Summary: • "Innovative Center Jewel" ("IC Jewel") is a Skolkovo IT company, creator of a revolutionary "Jewel Head-Collision Prevention System" (JHCPS), for a long range preventative detection, that enables self-driving car to "see" up to 2,000 meters ahead under any visibility and weather conditions. • Self-driving cars are no longer a futuristic idea. Companies like Google, Mercedes, BMW, Tesla, Toyota have already released, companies like Apple, Uber and Qualcoom are soon to release, and giants like GM, Kamaz and Tata announced plans for self-driving features that give the car ability to drive itself. • "IC Jewel" developes a proof-of-concept functional prototype of JHPC automotive radar system designed to become an OEM portable long-range radar for a car driven on common roads in any weather, in high/low speed traffic and with a projected wholesale price at around $3,000.
  • 4. Accident that occurred due to moving into the oncoming direction, have the most serious consequences The cost of existing safety systems is very high for an ordinary user Safe overtaking distance is up to 2000 meters (Traffic police statistics) The market of automobile security systems needs an import substitution It is hard enough to assess the safety of overtaking in the opposite lane (determine the distance and speed of oncoming vehicle) without any hardware It is necessary to reduce the number and lethality of road traffic accidents (Federal target program of road traffic safety improving in 2013-2020)
  • 5.
  • 6. Customer Problem: • Google's and other self-driving cars are blind at distances over 300m. It takes 11 seconds for a car moving at 100 km/h (27,7 m/s) to pass 300m. • Another car approaching head-on at the same speed leaves just about 5 seconds for an AI to analyze the dynamic situation and respond precisely to avoid collision. System fails if more than three moving objects need attention. Existing legislative speed restriction of 40 km/h is a direct consequence of this. • Long range lidars, used by Google-cars, are expensive ($70.000). Yet with all their impressive short/mid range capabilities get partially blind in snowfall, dusty road and light rain and completely blind in smoke, fog, hail and heavy showers. Google drives its cars in CA because state experiences historic drought. • Road crashes cost USD $518 billion globally, costing individual countries from 1-2% of their annual GDP.
  • 8.
  • 9. Product/Services: JHCPS: automotive radar system for long range preventive detection: • Radar wholesale is about $3,000, its EIRP = -10dBWt (the resolved noise immunity for licensing and certification); • JHCPS can be used for direct integration into existing ADAS systems and AI upgrade; • JHCPS determines the speed of oncoming objects (up to 360 km/h), distance to them (up to 2,000 meters) and relative trajectory. +JEWEL LANE DEPARTURE PREVENTION (JLDPS) • Show and ice are not a problem! • Car's radio vision is our solution! • All in any weather conditions; • JHCPS and JLDP can potentially be installed behind the car grille on any car.
  • 10.
  • 11.
  • 12. Lane Departure Prevention (LDP) and Lane Assist systems don’t work without this lines….. Lane keeping systems have nothing to keep on the typical provincial road…
  • 13. Target Market: • Semi-autonomous: 50+m cars by 2020. Today's premium cars car have features that allow them to accelerate, brake, and steer a car's course with limited or no driver interaction. JHCPS would enable the car to avoid head-on collision and prevent deaths. • Fully-autonomous: 10+m cars by 2020. A fully autonomous vehicle can drive from point A to point B and encounter the entire range of on-road scenarios without needing any interaction from the driver. JHCPS would act as a key component for long range car awareness, allowing AI to detect, follow and take action on numerous moving road objects 2,000m ahead. • Primary markets: USA, Canada, EU, Japan, Singapore, Korea, Australia • Costs (World): $7 b/year in direct ADAS costs; $122 b/year in indirect car options costs.
  • 14. Customers: Direct: 8 major car companies (Volvo, Porsche, Mercedes, Bentley, GM, Tata etc) who could offer modern car driver support options. Driverless car makers (Google self-driving car, Apple Car, Toyota robotic car, Uber, Kamaz trucks, etc.) Indirect: makers of security, drones and navigations toolkits (Lockheed Martin, Rotax, IAI, General Atomics Aeronautical Systems). We can offer innovative universal radar for their drone systems. Sales/Marketing Strategy: • Primary strategy: Partner with ADAS system manufacturers. • Secondary strategy 1: Partner with driverless car makers. • Secondary strategy 2: Partner with security and navigation tools developers. Business Model: • M&A by car maker who would get the system exclusively. Target valuation range: $60-80m
  • 15. Competitors: Indirect: Lidars optical stereoscope cameras (Fuji Heavy Industries "Subaru EyeSight", Google lidar, etc); Direct: 76-80 GHz, ultrasonic radars, Car2Car systems (Volvo CWAB, Bosch BLIS, Acura CMBS, etc). All have cost/ size/ efficiency/ capability and other disadvantages Competitive Advantage: Long range: 2,000m VS 300m detection range. All-weather: Any weather conditions VS clear visibility in dry air. Price: $3,000 VS $70,000+ for LIDAR's.
  • 16. Capital received to-date: $80.000, Skolkovo grant Investment sought: $1m: Series A (preferred stock for lead VC) + $500k Skolkovo grant committed. Series A Milestones: MVP prototype development, possible JV with driverless car company, IP protection. $2m: Series B (common stock for 2nd VC) + $1m Skolkovo grant. Series B Milestones: Industrial prototype development, scenarios for integration into AI software framework with selected manufacturer to show viability. Further IP protection. Exit: Early exit through M&A on development completion and technology validation with target $60-90m valuation by the end of Y3.
  • 17. Web: http://sk.ru/net/1121073/ http://jewel-innovations.ru Management: Nikolai Samotcvet, CEO Alex Kosik, VP Strategy Vladimir Lihachev, CTO Sergey Panychev, Chief Scientific Officer Yevgeni Koucheryavy, Scientific Adviser Konstantin Kosiakin, Legal Adviser Sergei Naumov, Chief Mass Media Officer Contact Info: Email: csir.ntc.reb@gmail.com Phone: +7 (951) 871-87-04 +1-571-338-0332