COMPANY PROFILE

 RegionCampania
 StatusStart-up

 
 PROPOSAL 

TitleAS1000
Project id.5
Reference sectorAEROSPACE
IP Protection LevelPatented - EP3022565 "System and process for measuring and evaluating air and inertial data”
Description of the innovation project By means of our technology some physical probes and vanes are replaced with virtual sensors with the consequent benefits in terms of cost, weight, emission and power consumption guaranteeing the same performance and increasing flight safety. As a generic and universal product, it can be successfully used on any air vehicle without any extra sensor installation or structural changes to the aircraft. In fact, we believe that the AS1000 product will be the new standard on which current and next generation air transport could rely on for low-cost, lightweight, reliable and environmentally friendly ADAHRS solution.
State of dev.Technological Demonstrator
Industrial applicationCivil Aviation
Market segmentGeneral Aviation and Large Airplanes: requiring about 12,000 systems like AS1000 per year up to 2036 in Europe and other 20,000 worldwide. About 1,000 deliveries a year (8% European market share) with about 15 M EUR as revenue.
Advantage factorThe AS1000 guarantees at least the same performance of equivalent systems available on the market, significantly increasing the safety level - Low-Cost. The AS1000 will allow the final user to save about 25% / 70%. - Lightweight. AS1000 assures to save about 50% / 70% - Eco-friendly. The AS1000 will allow the final user to save about 45% / 60% solutions. This will significantly cut emissions CO2 per flight hour w.r.t. those produced today.
Commercial challengeAeronautical Qualification (e.g. DO178, DO254, DO160)
Publications and Customer Refereces1) Advantages of Neural Network Based Air Data Estimation for Unmanned Aerial Vehicles. INTERNATIONAL JOURNAL OF MECHANICAL, AEROSPACE, INDUSTRIAL, MECHATRONIC AND MANUFACTURING ENGINEERING. 2) Test in Operative Environment of an Artificial Neural Network for Aerodynamic Angles Estimation. SFTE-EC 3) “Neural Networks for Air Data Estimation: Test of Neural Network Simulating Real Flight Instruments” ISSN: 1865-0929, 2012. And others

Proposal of cooperation agreementCommercial representative, Venture capital financing, Licensing, Distribution Agreement, Sub-contracting Agreement