CDE
Skolkovo
Institute of Science
and Technology
Institute of Science
and Technology
Skoltech
Intelligent Sensing
Group
Group
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About us
We develop intelligent sensor systems based on wireless sensor networks, wearable systems and UAVs. Intelligent options are implemented using machine learning, deep learning, transfer learning and computer vision implemented in the context of embedded systems. Applications: monitoring, detection and control tasks. In particular biomedicine/telemedicine, cyber sports, agriculture, waste sorting, detection of harmful and explosive gases and gas mixtures.
Our industrial competences include:
-Development of embedded systems: wireless sensor modules, wearable systems, oculographs.
-Energy-efficient sensor measurement methods.
-Implementation of artificial intelligence and computer vision methods as software, including for embedded systems.
-Development of power supplies for low-power sensor systems based on alternative energy sources and methods for efficient energy management.
-Synchronisation methods for sensor networks and multi-sensor systems.
-Analysis of (multimodal) data.
Our industrial competences include:
-Development of embedded systems: wireless sensor modules, wearable systems, oculographs.
-Energy-efficient sensor measurement methods.
-Implementation of artificial intelligence and computer vision methods as software, including for embedded systems.
-Development of power supplies for low-power sensor systems based on alternative energy sources and methods for efficient energy management.
-Synchronisation methods for sensor networks and multi-sensor systems.
-Analysis of (multimodal) data.
The team of the group
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Andrey Somov
Head of Intelligent Sensing Group
Assistant Professor
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Anton Vinogradov
Project Manager
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Anton Stepanov
Research Engineer
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Nikita Stasenko
PhD student
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Sergey Nesteruk
PhD student
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Aleksey Shcherbak
PhD student
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Ekaterina Kovalenko
PhD student
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Arman Petrosyants
PhD student
Publications
A. Menshchikov, A. Somov
Aerial Robotics for Precision Agriculture: Weeds Detection Through UAV and Machine Vision.
pp. 23-51. In: O. Sergiyenko (eds.), Optoelectronic Devices in Robotic Systems. Springer, Cham.