NSF Org:	TI Translational Impacts
Recipient:	REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE
Initial Amendment Date:	February 29, 2016
Latest Amendment Date:	February 29, 2016
Award Number:	1628832
Award Instrument:	Standard Grant
Program Manager:	Steven Konsek TI  Translational Impacts TIP  Directorate for Technology, Innovation, and Partnerships
Start Date:	March 1, 2016
End Date:	February 28, 2017 (Estimated)
Total Intended Award Amount:	$50,000.00
Total Awarded Amount to Date:	$50,000.00
Funds Obligated to Date:	FY 2016 = $50,000.00
History of Investigator:	Sanjit Seshia (Principal Investigator) sseshia@eecs.berkeley.edu
Recipient Sponsored Research Office:	University of California-Berkeley 1608 4TH ST STE 201 BERKELEY CA  US  94710-1749 (510)643-3891
Sponsor Congressional District:	12
Primary Place of Performance:	University of California-Berkeley 566 Cory Hall Berkeley CA  US  94720-1776
Primary Place of Performance Congressional District:	12
Unique Entity Identifier (UEI):	GS3YEVSS12N6
Parent UEI:
NSF Program(s):	I-Corps
Primary Program Source:	01001617DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s):	802300
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.084

ABSTRACT

Cyber-Physical Systems (CPS) tightly integrate computation with physical processes. Examples include modern automobiles, medical devices, toys, drones, robots, smart thermostat and HVAC systems and many more. The commercial potential of these systems has been recognized with the growing buzz around the "Internet of Things (IoT)." As the design of CPS/IoT systems goes mainstream, from a research, hobbyist, and niche industrial activity to a mainstream, large-scale industry, the design challenges are mounting. A primary challenge is to help designers and users gain better insight into their systems: what behaviors the systems must and must not have, why they exhibit certain desired/undesired behaviors, and how to design and implement them to achieve desired behavior. This project proposes to create a software toolkit, VeriSight CPS, and investigate its capabilities to meet this challenge. VeriSight can be used to answer queries about a system at various phases of the design and operation of a system. Industrial impact of the VeriSight toolkit is anticipated in several areas, including transportation, robotics, and medical devices.

The technical goals of this project are to develop a software toolkit to assist in the specification, design, verification, debugging,optimization, and maintenance of cyber-physical systems, and to investigate its effectiveness in a focused set of applications of high impact. The underlying theory is a novel blend of formal methods for design automation and machine learning. Unlike mainstream machine learning and data analytics techniques, VeriSight CPS involves the use of verification technology to analyze models and to answer queries. The envisioned contributions of the project include a general software architecture for VeriSight CPS applicable to multiple application domains, the investigation of various user interaction models, and an exploration of industrial applications in key CPS domains including transportation, medical devices, and robotics. A key part of this Innovation Corps (I-Corps) project will be to interview potential customers, e.g., those from the categories listed above, and determine which options will be the most fruitful.

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Cyber-physical systems (CPS) are integrations of computational processes with the physical world. Examples of CPS abound including modern automobiles,aircraft, robots, medical devices, energy systems, toys, and many more. With the increasing complexity of CPS, the challenges of designing them to be dependable and secure are mounting. While safety and efficiency are top design considerations, they are difficult to attain with increasing complexity. The PI and colleagues have designed, over many years, several theories and software toolkits to address the challenges of CPS design. The objective of this I-Corps project was to evaluate the product-market fit of one of these toolkits, the core VeriSight CPS technology, and to develop a business model for commercializing the technology. To this end, the project included the following main accomplishments:

(i) Intellectual Merit: The technology underlying this I-Corps project is amongst the first efforts to combine formal methods with machine learning in a software toolkit for the design of CPS. This project sought to investigate whether this technology fits the present needs of the CPS industry, particularly to significantly improve the productivity of designers of industrial cyber-physical systems.By interviewing about 100 prospective customers, it was determined that the automotive vertical within the broader CPS industry was the most promising segment for the core VeriSight CPS technology. Important hypotheses on the business model canvas were validated through these interviews, including the value propositions, customer segments,channels, key partners, key activities, and key resources. The project concluded with the formation of a company and initial funds for thecompany obtained via contracts with automotive OEMs.

(ii) Broader Impact: Safety and efficiency are key design considerations for the CPS industry and particularly for the automotive sector. By enabling the formation of a startup company providing design tools to improve the safety and efficiency of cyber-physical systems, this I-Corps project has taken basic, fundamental research results generated in previous NSF projects to the marketplace, and is starting to have important impact on the design of complex automotive systems. 

Last Modified: 06/24/2017
Modified by: Sanjit Seshia

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