PhD Position at IETR - Ecodesign of Embedded Systems applied to Smart Vision

17 May 2024
Job Information

Organisation/Company

INSA Rennes

Research Field

Computer science » Computer architecture
Computer science » Computer hardware
Computer science » Digital systems
Computer science » Systems design
Engineering » Electronic engineering
Engineering » Electrical engineering
Technology » Electrical technology
Technology » Computer technology

Researcher Profile

First Stage Researcher (R1)

Country

France

Application Deadline

24 Jun 2024 - 12:00 (Europe/Paris)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

35

Offer Starting Date

1 Oct 2024

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

INSA Rennes, a founding member of the INSA Group, is the largest public engineering school in Brittany.
It welcomes 2,200 students and apprentices and graduates more than 340 engineers, 60 masters and 40 PhDs per year.
Composed of 10 teaching departments, including 7 specialties and an apprenticeship program, and supervised by 6 research laboratories, INSA employs approximately 500 public employees (research professors, teachers, permanent and contractual employees) and more than 400 temporary employees, particularly from companies.

Like all industrial sectors, the electronics sector must, to be sustainable, drastically reduce its CO2 emissions by 2050, and more globally commit to a logic of circular economy. While environmental impacts of electronics are increasingly understood, the evaluation of impacts in Life Cycle Assessments (LCA) is still an emerging practice that requires complex models, data and insights. Once the impacts are known, ecodesign strategies must be developed and assessed.

The impacts of an electronic system arise from its manufacturing, use and end-of-life. The system itself is composed of printed circuit boards (PCB), semiconductor integrated circuits (ICs), passive components, connectors, sensors, actuators, batteries and displays, each having environmental impacts. In particular, the greenhouse gas (GHG) emissions of semiconductor manufacturing represent an important share of the embodied carbon footprint of electronics systems and must be considered alongside energy consumption and end-of-life [M21][P22][U22].

A smart vision system is a combination of sensors and digital processing that captures, preprocesses and distributes a video or a semantic description of a visual scene. It can take the form of a smart camera, mono-sensor [B14] or multi-sensors [K07], or of a camera module in an embedded system comprising a sophisticated image processing pipeline [M20]. It can also comprise a set of distributed sensors [R10]. Current smart vision systems embed optics, Complementary Metal-Oxide-Semiconductor (CMOS) sensors, color processing, image enhancement, video compression and artificial intelligence for image and video analysis. The sophistication of these systems is increasing, as examplified in smartphones that combine several sensors, dedicated Image Signal Processors (ISPs) and software post-processing to implement computational photography [D21].

This thesis will explore ecodesign of smart vision systems as representative examples of high performance embedded systems. The carbon impact of such systems is currently dominated by the embodied emissions, i.e. the greenhouse gas emissions of system fabrication [G21], but results from a complex and difficult to evaluate combination of fabrication, use and end-of-life impacts of its components and software layers [G21] as illustrated in Figure 1. The thesis will aim at understanding how to model linear and non-linear factors influencing carbon emissions of such a system and developing ecodesign methods to minimize environmental impacts by leveraging on circular economy.

Objectives

1. Novel methods for life cycle analysis of embedded systems. System ecodesign requires precise information of the impacts of system design decisions (types of CPU/GPU, FPGA, memory, busses, connectors, PCBs, etc.) and on the use phase of the system (idle time, workload, etc.). Thus, the first objective of this thesis will be to improve Life Cycle Analyses (LCAs) of embedded systems, especially applied to carbon emissions evaluation of smart vision systems. Different forms of LCAs exist that attribute costs to subsystems and that evaluate costs of modifications. However, environmental impacts of embedded systems are currently very partially known, notably due to lack of manufacturer data and to excessive approximations. In this thesis, new forms of LCA will be designed, adapted to the specific context of smart vision systems, and exploiting the research teams expertise in system design. In particular, real-life smart camera cases will be analyzed, prototyped, and measured for energy consumption, based on the experience of Institut Pascal in smart camera prototype design.

2. Ecodesign for reducing carbon impacts. A second objective will be to analyse the options for modifying such systems towards a more sustainable form while preserving performances. Ecodesign means designing the embedded system with the goal to be part of circular economy, i.e. decreasing the need of new materials, increasing reuse, and avoiding waste. Novel scene observation strategies will be analyzed as well as system downsizing, remanufacture [K06], reuse of recovered or low impact sensors or processing devices, improve repairability, and trade-offs between processing and sensing costs. This study will aim at proposing novel hardware design methods that, for a given level of system service, provably reduce environmental impacts.

 

Environment and Expected Impact

The thesis will be held at IETR (Institut d'Electronique et des Technologies du NuméRique) in the VAADER team and within the context of the ESOS project (Electronique Soutenable, Ouverte et Souveraine - https://esos.insa-rennes.fr ), in collaboration with the DREAM team at Institut Pascal, Clermont Ferrand. The thesis will benefit from the dynamism of the ESOS project (6.4M€ budget, 2023-28) that develops a strong expertise on electronics life cycle analysis and eco-design. Past ESOS seminars can be found here: https://codimd.math.cnrs.fr/s/XBacPiRc9#

The thesis will be co-directed by Dr. Maxime Pelcat and Prof. François Berry, and advised by Dr. Thibaut Marty. Prof. Berry is leader of the DREAM team specialized in smart camera design at Institut Pascal and Professor at Université Clermont Auvergne. Prof. Berry has a long-term research experience on designing and studying smart cameras. Prof. Berry is also scientific advisor at Sma-RTy, an Italian SME designing smart cameras, including near-sensor image processing and deep learning. Dr. Pelcat is leading the ESOS project on sustainable, open and sovereign electronics. His research focuses on studying the physical properties of computational systems. Dr. Marty is specialized on digital architectures design, and member of the ESOS project team.

Location

Vaader teams, IETR laboratory - INSA Rennes, 20 Avenue des Buttes de Coësmes , 35708 Rennes, France

 

Experience to be gained during the PhD

• Sustainability and life cycle analysis

• Vision system design

• Hardware ecodesign

• Research process

• Team work and collaborations

 

The candidate shall hold a master degree in electrical engineering or computer science, with experience or skills in the following areas:

• Skills in C, C++, Python (required),

• VHDL or Verilog (required)

• Statistical models (appreciated)

• Optimization and machine learning (appreciated)

• Life cycle analysis and ecodesign (appreciated)

• English speaking and writing is compulsory

 

References

[B14] Birem, M., & Berry, F. (2014). DreamCam: A modular FPGA-based smart camera architecture. Journal of Systems Architecture, 60(6), 519-527.

[D21] Delbracio, M., Kelly, D., Brown, M. S., & Milanfar, P. (2021). Mobile computational photography: A tour. Annual Review of Vision Science, 7, 571-604.

[G21] Gupta, U., Kim, Y. G., Lee, S., Tse, J., Lee, H. H. S., Wei, G. Y., … & Wu, C. J. (2021, February). Chasing carbon: The elusive environmental footprint of computing. In 2021 IEEE International Symposium on High- Performance Computer Architecture (HPCA) (pp. 854-867). IEEE.

[K06] King, A. M., Burgess, S. C., Ijomah, W., & McMahon, C. A. (2006). Reducing waste: repair, recondition, remanufacture or recycle?. Sustainable development, 14(4), 257-267.

[K07] Klausner, A., Tengg, A., & Rinner, B. (2007, September). Vehicle classification on multi-sensor smart cameras using feature-and decision-fusion. In 2007 First ACM/IEEE International Conference on Distributed Smart Cameras (pp. 67-74). IEEE.

[M20] Mosleh, A., Sharma, A., Onzon, E., Mannan, F., Robidoux, N., & Heide, F. (2020). Hardware-in-the-loop end-to-end optimization of camera image processing pipelines. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 7529-7538).

[M21] Moreau, N., Pirson, T., Le Brun, G., Delhaye, T., Sandu, G., Paris, A., … & Raskin, J. P. (2021). Could unsustainable electronics support sustainability?. Sustainability, 13(12), 6541.

[P22] Pirson, T., Delhaye, T. P., Pip, A., Le Brun, G., Raskin, J. P., & Bol, D. (2022). The environmental footprint of ic production: Review, analysis and lessons from historical trends. IEEE Transactions on Semiconductor Manufacturing.

[R10] Real, F., Berry, F., & Shi, Y. (2010). Smart Cameras: Fundamentals, Technologies and Applications. Smart Cameras, Springer, 10, 978-1.

[U22] Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, and Carole-Jean Wu. 2022. Chasing Carbon: The Elusive Environmental Footprint of Computing. IEEE Micro 42, 4 (July-Aug. 2022), 37–47. https://doi.org/10.1109 /MM.2022.3163226.

Requirements

Research Field

Computer science

Education Level

Master Degree or equivalent

Research Field

Engineering » Electrical engineering

Education Level

Master Degree or equivalent

Languages

ENGLISH

Level

Excellent

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

INSA RENNES/IETR

Country

France

City

Rennes

Postal Code

35708

Street

20 avenue des buttes de Coesmes

Geofield

Where to apply

E-mail

[email protected]

Contact

State/Province

Brittany

City

Rennes

Website

https://www.insa-rennes.fr

Street

20 avenue des buttes de Coësmes

Postal Code

35708

STATUS: EXPIRED