Study and Modeling Based On Motion Sensors for - Guipavas, France - Lineact CESI Brest

Description

Study and modeling based on motion sensors for occupancy number estimation in smart buildings:

• Réf

-
ABG-110336

• Stage master 2 / Ingénieur
• Durée 5 mois
• Salaire net mensuel /01/2023
• Lineact CESI Brest
• Lieu de travail
• Guipavas Bretagne France
• Champs scientifiques
• Electronique
• Science de la donnée (stockage, sécurité, mesure, analyse)

• Mots clés

• Occupancy estimation, Smart Buildings, Motion Sensors, Building Energy, IoT 10/02/2023
  Établissement recruteur:LINEACT CESI (EA 7527), Digital Innovation Laboratory for Companies and Apprenticeships for the Competitiveness of Territories, anticipates and follows technological mutation of field and services linked to industry and Buildings. CESI's historical proximity to companies is a determining factor for our research activities, and has led us to focus our efforts on applied research close to the company and in partnership with them. A humancentered approach coupled with the use of technologies, as well as the territorial network and the links with training have made it possible to build a transversal research; it puts the human, its needs and its uses, at the center of its problems and approaches the technological angle through these contributions.

Theme 1:
"Learning and Innovating", which brings together cognitive, social and management sciences, as well as training and innovation sciences and techniques; The main scientific objectives targeted by this theme are the understanding of the effects of the environment, and more particularly of situations instrumented by technical objects (platforms, prototyping workshops, immersive systems ) on learning and creativity processes.


Description:

Buildings account for 40% of global primary energy consumption [1], and better control over Building Energy Management Systems (BEMS) can reduce energy use.

However, the influence of dynamic occupancy in the building makes it difficult for optimal control, thus occupancy information needs to be integrated [2].

Motion sensors are often used for this purpose, as they provide a direct measurement of occupancy [3].

However, these sensors are not always precise and may not accurately detect all occupants or distinguish between passing and stationary individuals [4, 5].

Additionally, there is limited research on the optimal positioning and solid angle of detection for motion sensors, as well as on the comparison and combination of different types of motion sensors [6, 7].

To address these challenges, this study aims to examine the performance of various motion sensors, determine the most effective sensor in terms of positioning and solid angle, and develop a model to infer occupancy from sensor readings.

The study will also consider the impact of noise on sensor performance and identify potential sources of interference.

By comparing optimal and common positioning of existing motion sensors, this study will contribute valuable insights for sensor fusion and energy management in buildings.

This work may lead to a 3-years Ph.
D. thesis with the funding.


Profil:

• Scientific and technical skills : _
• The applicant must be from an Electrical or Computer Science engineering background.
• Any relevant experience in building physics or IoT would be a plus.
• Experience in data analysis, and management is preferred.
• Experience in programming environments (eg. Python, R, etc).
• Social skills : _
• Be autonomous, have a spirit of initiative and curiosity
• Know how to work in a team and in autonomy, and have good interpersonal skills
• To be enthusiastic and selfmotivated
• To be rigourous.
• NB:_ applicant should study in French College or have an European citizenship._

Prise de fonction:

• 01/03/2023