Limitless Timeseries Analysis to open up Big Data applications in Transportation

Informacje na temat projektu

TransDB

Identyfikator umowy o grant: 876711

DOI

10.3030/876711

Projekt został zamknięty

Data podpisania przez KE 23 Lipca 2019

Data rozpoczęcia 1 Sierpnia 2019

Data zakończenia 31 Stycznia 2020

Finansowanie w ramach

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Koszt całkowity

€ 71 429,00

Wkład UE

€ 50 000,00

Koordynowany przez

QUASARDB
France

Periodic Reporting for period 1 - TransDB (Limitless Timeseries Analysis to open up Big Data applications in Transportation)

Okres sprawozdawczy: 2019-08-01 do 2020-01-31

Podsumowanie kontekstu i ogólnych celów projektu

The transportation sector is now being revolutionized by the emergence of new technologies, such as electrification, Big Data, Internet of Things (IoT), Artificial Intelligence (AI) and Analytics. Connected vehicles produce a massive flow of data from their sensors and connected systems. Real time processing of this data will enable predictive maintenance, proactive incident management, transportation planning, and enhanced traffic management, with major environmental, economic and social positive impacts.
Based on its successful experience in Finance, QuasarDB has developed TransDB, a highly resilient Time Series DataBase Management System (TSDBMS) that combines large scale storage and instant querying at both central (cloud) and edged (sensor) levels.
A prototype is running at one of the largest global Tier one suppliers in the automotive industry.
The first part of the project alowed us to identify the different types of customers (described below), benefits for them (such as more efficient operations and more customers), for the Society (safer, faster transportation for all) and for the company itself ( resulting in profitable company with more than 40 new employees within 5 years)

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

"Based on the Global Tier one manufacturing use-case and meetings in Europe and US with actors from connected cars and mobility-as-a-service sectors, the team has identified which new features were required, the different types of customers to target, an estimate of the market size and the most appropriate road to market:
Market assessment:
Customer type # accounts
Automotive Manufacturer and Tier one 50
Large size car sharing/Ride Hailing/Ridesharing cies 30
Insurance cies 20
Major infrastructure / Mass transportation 100
Mid-size car sharing/ride Hailing/ridesharing 200
Large Public Transport/local Government 400
All other Mobility/ Local govt/ Motorways/Services cies 1500

Development needs:
1) Extension of our single database layer system to a multiple layered system (>2 layers) to cope with high loads and variety of data. (includes swarming).
2) Further optimization of data queries for application in transportation. (Geodata)
3) Enhancement of geo-localization capabilities
4) Further adapt to the types of devices on which TransDB will run (ruggedized and embedded versions, transparent edge computing and intermittent connections support).
5) Seamless integration to platforms such as Fiware

Road-to-Market
Step 1: up to 2022: limited number of customers, directly managed by management team in a relational approach.
Step 2: Industrialization of sales process:
- Implementation of a Saas offer for the “small accounts”
- Recruitment of a field salesforce regarding large and medium accounts Syst
- Continuation of the marketing effort including membership of relevant clusters, association as well as participation to relevant tradeshows and events
- Publication in various ecosystem sites"

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

A conservative Business Plan resulting from the assumptions above shows following outputs within 5 years:
- 9% market share
- Positive cumulated EBITDA
- 40 additional employees
Technological and Market Risks have been identified and actions such as dual approach and young talent recruitment are in place to mitigate them. We have not identified any significant evolution in the competitive landscape and TransDB will definitively maintain its first-to-market advantage.
Phase 1 Study has demonstrated that TransDB and its unique features matches with the growing requirements of connected vehicles and mobility-as-a-service needs. Obviously, TransDB is not the only technology brick for these but represents a solid fondation to support IA applications to deliver all the soci-economoic and environmental benefits expected in the people transportation.

Connected vehicles with TransDB