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AMBIENT INTELLIGENCE
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19 Industrial |
28 Patents |
To understand better the environment, extract from it intelligible information and exploit this information into innovative applications.
List, a CEA Tech institute, relies on mature technologies to develop a global approach for ambient intelligence applications including the whole HMI (Human Machine Interface) aspects, from perception to user’s restitution.
Our research addresses various industrial sectors: security (videosurveillance, pedestrian detection…), health, energy, transport and digital economy (data filtering and analysis, search engines…)
170 research engineers work on four fields of application:
- Diamond material and sensors
- Internet of things
- Data analysis
- Knowledge engineering
Find out more about List topics on ambient intelligence research programme
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Diamond material and sensors
List institute develops synthetic diamond-based innovative sensors by making new transducers and equipping them with a specific signal processing electronic technology. Our competences give us the opportunity to develop original solutions implementing physical, chemical, electric and biological measurements etc.
These sensors can work either on liquid or gas phase and they can also adapt to extreme conditions: high temperatures, radiative or chemically aggressive environments, living biological tissues, etc...
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Internet of things
List institute answers internet of things challenges through research work on new human-machine interfaces that aim to be simple, intuitive and reprogrammable according to the application context. The research work focuses also on communication protocols’ adaptation to small communicating objects specific constraints. Our researchers work through a multidisciplinary approach: ergonomics, human factors, signal processing, electronics, communication… They collaborate with industrial companies from transport, energy, building, health and domotics sectors.
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Data analysis
List institute develops algorithms and software tools for a great variety of data analysis and processing. These data can come from measuring equipment for biology, food industry, process control and others or from sensor networks placed in buildings, industrial equipment or vehicles and so on… These data are often difficult to interpret because of their important volume, complexity or variety. Our researchers make them exploitable through advanced raw signal processing methods and automated learning statistical models allowing developing results analysis or decision making support tools.
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